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Journal articles on the topic 'Relational pattern'

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Published: 4 June 2025

Last updated: 23 June 2025

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1

Gatterbauer, Wolfgang, and Cody Dunne. "On The Reasonable Effectiveness of Relational Diagrams: Explaining Relational Query Patterns and the Pattern Expressiveness of Relational Languages." Proceedings of the ACM on Management of Data 2, no. 1 (2024): 1–27. http://dx.doi.org/10.1145/3639316.

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Comparing relational languages by their logical expressiveness is well understood. Less well understood is how to compare relational languages by their ability to represent relational query patterns. Indeed, what are query patterns other than "a certain way of writing a query"? And how can query patterns be defined across procedural and declarative languages, irrespective of their syntax? To the best of our knowledge, we provide the first semantic definition of relational query patterns by using a variant of structure-preserving mappings between the relational tables of queries. This formalism allows us to analyze the relative pattern expressiveness of relational language fragments and create a hierarchy of languages with equal logical expressiveness yet different pattern expressiveness. Notably, for the non-disjunctive language fragment, we show that relational calculus can express a larger class of patterns than the basic operators of relational algebra. Our language-independent definition of query patterns opens novel paths for assisting database users. For example, these patterns could be leveraged to create visual query representations that faithfully represent query patterns, speed up interpretation, and provide visual feedback during query editing. As a concrete example, we propose Relational Diagrams, a complete and sound diagrammatic representation of safe relational calculus that is provably (i) unambiguous, (ii) relationally complete, and (iii) able to represent all query patterns for unions of non-disjunctive queries. Among all diagrammatic representations for relational queries that we are aware of, ours is the only one with these three properties. Furthermore, our anonymously preregistered user study shows that Relational Diagrams allow users to recognize patterns meaningfully faster and more accurately than SQL.

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2

Hońko, Piotr. "Relational pattern updating." Information Sciences 189 (April 2012): 208–18. http://dx.doi.org/10.1016/j.ins.2011.12.004.

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3

Gatterbauer, Wolfgang, and Cody Dunne. "Relational Diagrams and the Pattern Expressiveness of Relational Languages." ACM SIGMOD Record 54, no. 1 (2025): 80–88. https://doi.org/10.1145/3733620.3733637.

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Comparing relational languages by their logical expressiveness is well understood. Less understood is how to compare relational languages by their ability to represent relational query patterns. Indeed, what are query patterns other than ''a certain way of writing a query''? And how can query patterns be defined across procedural and declarative languages, irrespective of their syntax? Our SIGMOD 2024 paper proposes a semantic definition of relational query patterns that uses a variant of structurepreserving mappings between the relational tables of queries. This formalism allows us to analyze the relative pattern expressiveness of relational languages. Notably, for the nondisjunctive language fragment, we show that relational calculus (RC) can express a larger class of patterns than the basic operators of relational algebra (RA). We also propose Relational Diagrams, a complete and sound diagrammatic representation of safe relational calculus. These diagrams can represent all query patterns for unions of non-disjunctive queries, in contrast to visual query representations that derive visual marks from the basic operators of algebra. Our anonymously preregistered user study shows that Relational Diagrams allow users to recognize relational patterns meaningfully faster and more accurately than they can with SQL.

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4

Takan, Savas, and Gokmen Katipoglu. "Relational Logging Design Pattern." Computers, Materials & Continua 75, no. 1 (2023): 51–65. http://dx.doi.org/10.32604/cmc.2023.035282.

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5

Almagro-Blanco, Pedro, Fernando Sancho-Caparrini, and Joaquín Borrego-Díaz. "Logical–Mathematical Foundations of a Graph Query Framework for Relational Learning." Mathematics 11, no. 22 (2023): 4672. http://dx.doi.org/10.3390/math11224672.

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Relational learning has attracted much attention from the machine learning community in recent years, and many real-world applications have been successfully formulated as relational learning problems. In recent years, several relational learning algorithms have been introduced that follow a pattern-based approach. However, this type of learning model suffers from two fundamental problems: the computational complexity arising from relational queries and the lack of a robust and general framework to serve as the basis for relational learning methods. In this paper, we propose an efficient graph query framework that allows for cyclic queries in polynomial time and is ready to be used in pattern-based learning methods. This solution uses logical predicates instead of graph isomorphisms for query evaluation, reducing complexity and allowing for query refinement through atomic operations. The main differences between our method and other previous pattern-based graph query approaches are the ability to evaluate arbitrary subgraphs instead of nodes or complete graphs, the fact that it is based on mathematical formalization that allows the study of refinements and their complementarity, and the ability to detect cyclic patterns in polynomial time. Application examples show that the proposed framework allows learning relational classifiers to be efficient in generating data with high expressiveness capacities. Specifically, relational decision trees are learned from sets of tagged subnetworks that provide both classifiers and characteristic patterns for the identified classes.

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Kamiya, Yohei, and Hirohisa Seki. "Distributed Mining of Closed Patterns from Multi-Relational Data." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 6 (2015): 804–9. http://dx.doi.org/10.20965/jaciii.2015.p0804.

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In multi-relational data mining (MRDM), there have been proposed many methods for searching for patterns that involve multiple tables (relations) from a relational database. In this paper, we consider closed pattern mining from distributed multi-relational databases (MRDBs). Since the computation of MRDM is costly compared with the conventional itemset mining, we propose some efficient methods for computing closed patterns using the techniques studied in Inductive Logic Programming (ILP) and Formal Concept Analysis (FCA). Given a set oflocaldatabases, we first compute sets of their closed patterns (concepts) using a closed pattern mining algorithm tailored to MRDM, and then generate the set of closed patterns in the global database by utilizing themergeoperator. We also present some experimental results, which shows the effectiveness of the proposed methods.

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Ray, K. S., and T. K. Dinda. "Pattern classification using fuzzy relational calculus." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 33, no. 1 (2003): 1–16. http://dx.doi.org/10.1109/tsmcb.2002.804361.

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8

Huet, B., and E. R. Hancock. "Line pattern retrieval using relational histograms." IEEE Transactions on Pattern Analysis and Machine Intelligence 21, no. 12 (1999): 1363–70. http://dx.doi.org/10.1109/34.817414.

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9

Riedewald, Mirek. "Technical Perspective: Relational Diagrams and the Pattern Expressiveness of Relational Languages." ACM SIGMOD Record 54, no. 1 (2025): 79. https://doi.org/10.1145/3733620.3733636.

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When a database researcher or user hears the word ''expressiveness,'' they most likely think about what kind of query some language or formalism supports. For instance, can a given version of SQL express recursion or computation of the transitive closure of a graph? For what fragment of relational calculus can we decide query containment? Can relational algebra express every relational-calculus query and vice versa? The following paper by Gatterbauer and Dunne may forever change the discourse on expressiveness in the context of relational languages by prompting the follow-up question: ''Do you mean logical expressiveness or pattern expressiveness?''

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10

Fauzi, Arwin Happy Nur, and Masduki Masduki. "Student’s Anomaly Reasoning in Solving Number Pattern in terms of Gender." Jurnal Didaktik Matematika 9, no. 2 (2022): 328–42. http://dx.doi.org/10.24815/jdm.v9i2.27146.

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Relational reasoning plays an important role in helping students to understand mathematical concepts. The student's ability to distinguish patterns or objects is one of the understandings of mathematical concept indicators. The anomaly dimension is part of the relational reasoning that students need to be able to determine a pattern or object in mathematics. This study aims to reveal the student's relational reasoning ability of anomaly dimension in solving number pattern problems in terms of gender differences. The subjects of this study are 52 grade-8 students in one of Muhammadiyah Junior High Schools in Kartasura. We used two similar problems on number patterns to disclose the student's ability to identify the pattern deviation in solving problems. The two selected students had relatively similar in their mathematical abilities. The finding showed that female subject met the three anomaly dimension indicators: identification, interpretation, and adaptation. Conversely, male student cannot fulfill the anomaly indicators. He cannot recognize pattern deviation in the formed mathematical model. He also failed to identify a pattern different from the two problems. Although the subjects interviewed were limited, the finding provided the insightful into the differences in anomaly reasoning abilities in male and female students

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Sengupta, Tuhin, Ashokkumar Devaraj, Varshini Karthik, Huda Altaf, and Mansi Gupta. "TRACE: TRACKING RELATIONAL AXES AND COMPARATIVE EVALUATION." Biomedical Engineering: Applications, Basis and Communications 33, no. 02 (2021): 2150008. http://dx.doi.org/10.4015/s1016237221500083.

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Autism is one of the developmental disorders which make major behavioral and communication changes in the individual and induce a major drawback in the walking pattern. The main aim of this study is to analyze and compare the stride patterns of an autistic patient and a healthy individual. With the help of the proposed device, the yaw, pitch and roll of the limbs can be easily measured and analyzed. These parameters will identify the lacking movement patterns and help the physiotherapists in improving the walking pattern of the autistic patients by adopting the correct approach of remedial actions/treatment. It can also be used by the people who have undergone hip replacements or knee replacements and have an abnormal gait pattern. This device is a simple accumulation of sensors and memory storage unit. Two gyroscope sensors have been used, one each for the knee and the ankle. These sensors are strapped onto the knee and ankle with the help of free-sized elastic bands. The data received by the sensors are stored in the storage device automatically and are evaluated in a specially designed Web application. However, the raw data from the gyroscope sensors have not been used directly and various filters have been used to remove the errors. The results have been compared between an autistic patient and a normal healthy subject and showed a higher degree of angle difference for the autistic patient than the normal individual.

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12

HU, YI-CHUNG. "A NOVEL FLOW-BASED METHOD USING GREY RELATIONAL ANALYSIS FOR PATTERN CLASSIFICATION." International Journal of Information Technology & Decision Making 12, no. 01 (2013): 75–93. http://dx.doi.org/10.1142/s0219622013500041.

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Flow-based methods based on the outranking relation theory are extensively used in multiple criteria classification problems. Flow-based methods usually employed an overall preference index representing the flow to measure the intensity of preference for one pattern over another pattern. A traditional flow obtained by the pairwise comparison may not be complete since it does not globally consider the differences on each criterion between all the other patterns and the latter. That is, a traditional flow merely locally considers the difference on each criterion between two patterns. In contrast with traditional flows, the relationship-based flow is newly proposed by employing the grey relational analysis to assess the flow from one pattern to another pattern by considering the differences on each criterion between all the other patterns and the latter. A genetic algorithm-based learning algorithm is designed to determine the relative weights of respective criteria to derive the overall relationship index of a pattern. Our method is tested on several real-world data sets. Its performance is comparable to that of other well-known classifiers and flow-based methods.

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13

Wen, Cheng, Chih-Hung Huang, and Ming-Feng Yeh. "GRAY RELATIONAL ALGORITHM FOR ECG PATTERN RECOGNITION." Biomedical Engineering: Applications, Basis and Communications 19, no. 05 (2007): 313–21. http://dx.doi.org/10.4015/s1016237207000410.

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The paper proposes a gray relational analysis based learning algorithm, called gray relational algorithm, for the recognition of ECG beats. Without analyzing relations between the input ECG beat and every beat in the database for the recognition, several training beats are chosen for learning from an ECG waveform database with patient diagnosis information, and then the learning result is used to analyze the test ECGs. The resulting similarity measurement is further identified as the diagnosis of the test ECG. This algorithm is capable of reducing the computational procedure of gray relational analysis as it is directly used for the analysis. The experiment shows that the proposed method can achieve a good classification result.

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14

Spyropoulou, Eirini, Tijl De Bie, and Mario Boley. "Interesting pattern mining in multi-relational data." Data Mining and Knowledge Discovery 28, no. 3 (2013): 808–49. http://dx.doi.org/10.1007/s10618-013-0319-9.

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15

Silva, Andreia, and Cláudia Antunes. "Multi-relational pattern mining over data streams." Data Mining and Knowledge Discovery 29, no. 6 (2014): 1783–814. http://dx.doi.org/10.1007/s10618-014-0394-6.

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16

Nie, Hua Bei, and Yi Wang. "Minimal Query Algorithm of XML Document Based on Unconstrained Tree Pattern." Advanced Materials Research 430-432 (January 2012): 1677–81. http://dx.doi.org/10.4028/www.scientific.net/amr.430-432.1677.

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XML document structure uses the tree structure to express the document structure model that is different from the traditional two-dimensional relational table structure and XML query patterns mainly for tree query. Tree pattern always divided into constrained type and unconstrained type. This paper based on unconstrained tree pattern query, provide a mini algorithm of unconstrained tree pattern query, and prove the correctness of algorithm theoretically.

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17

Li, Jiwen, Mei Zeng, Mingyan Liu, et al. "Multivariable pattern classification differentiates relational self-esteem from personal self-esteem." Social Cognitive and Affective Neuroscience 16, no. 7 (2021): 726–35. http://dx.doi.org/10.1093/scan/nsab053.

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Abstract Relational self-esteem (RSE) refers to one’s sense of self-worth based on the relationship with significant others, such as family and best friends. Although previous neuroimaging research has investigated the neural processes of RSE, it is less clear how RSE is represented in multivariable neural patterns. Being able to identify a stable RSE signature could contribute to knowledge about relational self-worth. Here, using multivariate pattern classification to differentiate RSE from personal self-esteem (PSE), which pertains to self-worth derived from personal attributes, we obtained a stable diagnostic signature of RSE relative to PSE. We found that multivariable neural activities in the superior/middle temporal gyrus, precuneus, posterior cingulate cortex, dorsal medial Prefrontal Cortex (dmPFC) and temporo-parietal junction were responsible for diagnosis of RSE, suggesting that the evaluation of RSE involves the retrieval of relational episodic memory, perspective-taking and value calculation. Further, these diagnostic neural signatures were able to sensitively decode neural activities related to RSE in another independent test sample, indicating the reliability of the brain state represented. By providing a reliable multivariate brain pattern for RSE relative to PSE, our results informed more cognitively prominent processing of RSE than that of PSE and enriched our knowledge about how relational self-worth is generated in the brain.

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18

Dinda, Tapan Kr, Kumar S. Ray, and Mihir Kr Chakraborty. "Fuzzy relational calculus approach to multidimensional pattern classification." Pattern Recognition 32, no. 6 (1999): 973–95. http://dx.doi.org/10.1016/s0031-3203(98)00133-2.

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19

Ngo, Chi T., Nora S. Newcombe, and Ingrid R. Olson. "The ontogeny of relational memory and pattern separation." Developmental Science 21, no. 2 (2017): e12556. http://dx.doi.org/10.1111/desc.12556.

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20

Hassevoort, Kelsey M., Naiman A. Khan, Charles H. Hillman, and Neal J. Cohen. "Differential development of relational memory and pattern separation." Hippocampus 30, no. 3 (2019): 210–19. http://dx.doi.org/10.1002/hipo.23146.

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21

Utomo, Dwi Priyo. "The pattern of a relational understanding of fifth-grade students on integer operations." JRAMathEdu (Journal of Research and Advances in Mathematics Education) 5, no. 2 (2020): 119–29. http://dx.doi.org/10.23917/jramathedu.v5i2.9545.

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Relational understanding constitutes students’ awareness of appropriate procedures to solve problems along with logical reasoning. Itis pivotal to help students solve problems in mathematics. It is necessary that the teaching of mathematics be directed to achieve relational understanding. Accordingly, students are capable of solving complicated problems in mathematics. This current research aims at analyzing and describing relational understanding and the patterns of answering questions of the fifth graders on integer operation. This study used a qualitative approach with a case study as the research design. Further, three students belonging to the fifth grade of Elementary School in Malang City, Indonesia, were set up as the research subjects. A test was administered to measure the subjects' relational understanding. All collected data were analyzed using an interactive technique. The result has indicated that the highly-proficient student was able to show excellent relational understanding. Besides, it was shown that the fairly-proficient student could show good relational understanding. The lowly-proficient student was shown to be able to achieve only half of the holistic criteria set for relational understanding. The patterns of answering the questions demonstrated by all students in all levels included jotting down the models, completing the models, and answering the questions. The highly-proficient student understood the information and wrote it down. Whilst the fairly-proficient student understood the information without translating it into the written form. At last, the lowly-proficient student did not pronounce any signals of understanding of the information

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Zhang, Yihong, Yisu Remy Wang, Max Willsey, and Zachary Tatlock. "Relational e-matching." Proceedings of the ACM on Programming Languages 6, POPL (2022): 1–22. http://dx.doi.org/10.1145/3498696.

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We present a new approach to e-matching based on relational join; in particular, we apply recent database query execution techniques to guarantee worst-case optimal run time. Compared to the conventional backtracking approach that always searches the e-graph "top down", our new relational e-matching approach can better exploit pattern structure by searching the e-graph according to an optimized query plan. We also establish the first data complexity result for e-matching, bounding run time as a function of the e-graph size and output size. We prototyped and evaluated our technique in the state-of-the-art egg e-graph framework. Compared to a conventional baseline, relational e-matching is simpler to implement and orders of magnitude faster in practice.

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Yin, Jiang, Yun Li, Cen Cheng Shen, and Bo Liu. "Multi-Relational Sequential Pattern Mining Based on Iceberg Concept Lattice." Applied Mechanics and Materials 109 (October 2011): 729–33. http://dx.doi.org/10.4028/www.scientific.net/amm.109.729.

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Multi-Relational Sequential mining is one of the areas of data mining that rapidly developed in recent years. However, the performance issues of traditional mining methods are not ideal. To effectively mining the pattern, we proposed an algorithm based on Iceberg concept lattice, adopting optimization methods of partition and merger to just mining the frequent sequences. Experimental results show this algorithm effectively reduced the time complexity of multi-relational sequential pattern mining.

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24

Elói, Martins Senhoras. "Covid-19, Brazil and Canada: a relational and compared analysis." Revista Intellector XVIII, no. 35 (2021): 20–33. https://doi.org/10.5281/zenodo.5515555.

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The widespread of the COVID-19 pandemic has brought significant impacts on human relations, generating ample repercussions characterized by certain patterns of national and international relations. Taking this theme as a reference this paper is aimed to analyze the patterns of socio-political interaction in relation to the securitization of the COVID-19 pandemic in Canada and Brazil through a constructivist approach. The methodological basis of this research is characterized by an exploratory and descriptive nature according to its ends and as well as quali-quantitative to its means which is instrumentalized by the use of a comparative method and a discursive historical-theoretical-deductive logic. The results of the research indicate that the dynamics of national and international relations have become permeated during the pandemic by Lockean (competitive), Hobbesian (conflictive) and Kantian (consensual) the patterns of interaction due to an asymmetrical field of power that turns out to be more complex.  It is concluded based on the results presented in the text that the interactional dynamics reported by Canada and Brazil demonstrate the convergence towards a negative apprehension of the COVID-19 pandemic in the social structure despite the different historical trajectories constructed on a Kantian pattern of relative consensus related to the decision-making processes in Canada in comparison to the Hobbesian pattern of intranational and international conflicts materialized in Brazil.

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Huff, Mark J., and Glen E. Bodner. "Item-specific and relational processing both improve recall accuracy in the DRM paradigm." Quarterly Journal of Experimental Psychology 72, no. 6 (2018): 1493–506. http://dx.doi.org/10.1177/1747021818801427.

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Using the Deese–Roediger–McDermott (DRM) paradigm, Huff and Bodner found that both item-specific and relational variants of a task improved correct recognition, but only the item-specific variants reduced false recognition, relative to a read-control condition. Here, we examined the outcome pattern when memory was tested using free recall, using the same item-specific versus relational task variants across three experiments as our previous study (processing instructions, pleasantness ratings, anagram generation). The outcome pattern in recall was similar to recognition, except relational processing at study actually reduced the DRM illusion, though not as much as item-specific processing. To reconcile this task difference, we suggest that the memory information laid down during relational encoding enhances the familiarity of the critical items at test. To the extent that familiarity is used less as a basis for responding in free recall than in recognition, relational processing ironically reduces rather than increases the DRM illusion in recall.

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26

Park, Uchang. "SQL Based Graph Pattern Query Performance on Relational DBMS." Journal of Korean Institute of Information Technology 17, no. 4 (2019): 9–20. http://dx.doi.org/10.14801/jkiit.2019.17.4.9.

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Caelli, Terry, Geoff West, Mike Robey, and Erol Osman. "A relational learning method for pattern and object recognition." Image and Vision Computing 17, no. 5-6 (1999): 391–401. http://dx.doi.org/10.1016/s0262-8856(98)00132-2.

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28

Lisi, Francesca A. "AL-QuIn." International Journal on Semantic Web and Information Systems 7, no. 3 (2011): 1–22. http://dx.doi.org/10.4018/jswis.2011070101.

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Onto-Relational Learning is an extension of Relational Learning aimed at accounting for ontologies in a clear, well-founded and elegant manner. The system -QuIn supports a variant of the frequent pattern discovery task by following the Onto-Relational Learning approach. It takes taxonomic ontologies into account during the discovery process and produces descriptions of a given relational database at multiple granularity levels. The functionalities of the system are illustrated by means of examples taken from a Semantic Web Mining case study concerning the analysis of relational data extracted from the on-line CIA World Fact Book.

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Zhu, Erkang, Silu Huang, and Surajit Chaudhuri. "High-Performance Row Pattern Recognition Using Joins." Proceedings of the VLDB Endowment 16, no. 5 (2023): 1181–95. http://dx.doi.org/10.14778/3579075.3579090.

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The SQL standard introduced MATCH_RECOGNIZE in 2016 for row pattern recognition. Since then, MATCH_RECOGNIZE has been supported by several leading relation systems, they implemented this function using Non-Deterministic Finite Automaton (NFA). While NFA is suitable for pattern recognition in streaming scenarios, the current uses of NFA by the relational systems for historical data analysis scenarios overlook important optimization opportunities. We propose a new approach to use Join to speed up row pattern recognition in historical analysis scenarios for relational systems. Implemented as a logical plan rewrite rule, the new approach first filters the input relation to MATCH_RECOGNIZE using Joins constructed based on a subset of symbols taken from the PATTERN expression, then run the NFA-based MATCH_RECOGNIZE on the filtered rows, reducing the net cost. The rule also includes a specialized cardinality model for the Joins and a cost model for the NFA-based MATCH_RECOGNIZE operator for choosing an appropriate symbol set. The rewrite rule is applicable when the query pattern's definition is self-contained and either the input table has no duplicates or there is a window condition. Applying the rewrite rule to a query benchmark with 1,800 queries spanning over 6 patterns and 3 pattern definitions, we observed median speedups of 5.4X on Trino (v373 with ORC files on Hive), 57.5X on SQL Server (2019) using column store and 41.6X on row store.

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Duin, Robert P. W., Elżbieta Pȩkalska, and Dick de Ridder. "Relational discriminant analysis." Pattern Recognition Letters 20, no. 11-13 (1999): 1175–81. http://dx.doi.org/10.1016/s0167-8655(99)00085-9.

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Hasu, Mervi, and Mikko Lehtonen. "Leadership with care – Constructing responsibility as ‘shared caring’ in a complex public service." Scandinavian Journal of Public Administration 18, no. 4 (2014): 9–28. http://dx.doi.org/10.58235/sjpa.v18i4.15643.

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   The article investigates the pattern of influence enacted by shop-floor service workers and line managers in a public sector organisation which have been affected by New Public Management changes. Applying the concepts of care (caring) and trust, we expand the concept of the relational influence pattern originating from leadership theory. We supplement our analysis with the sensitive methodology of studying activities in shop-floor work, namely experiences of transitions on the micro-level among a group of employees, managers and clients. The results show that the caring observed in the group is shared among the individuals, it supports their collective responsibility, and exhibits trust relationships that have been created through shared experiences. Qualitative evidence illustrates that shared caring can be a pattern of relational, embodied leadership influence, directed to nurture, improve or help the situation of others in the work community. The pattern had evolved naturally through shared and expected, foreseeable experiences. We suggest the notion of leadership with care to describe this type of relational leadership influence.  

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32

Cao, Yan Jiao, Zhao Lu, and Song Mei Cai. "Relational Similarity Measure: An Approach Combining Wikipedia and WordNet." Applied Mechanics and Materials 55-57 (May 2011): 955–60. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.955.

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Relational similarities between two pairs of words are the degrees of their semantic relations. Vector Space Model (VSM) is used to measure the relational similarity between two pairs of words, however it needs create patterns manually and these patterns are limited. Recently, Latent Relational Analysis (LRA) is proposed and achieves state-of-art results. However, it is time-consuming and cannot express implicit semantic relations. In this study, we propose a new approach to measure relational similarities between two pairs of words by combining Wordnet3.0 and the Web-Wikipedia, thus implicit semantic relations from the very large corpus can be mined. The proposed approach mainly possesses two characters: (1) A new method is proposed in the pattern extraction step, which considers various part-of-speeches of words. (2)Wordnet3.0 is applied to calculate the semantic relatedness between a pair of words so that the implicit semantic relation of the two words can be expressed. Experimental evaluation based on the 374 SAT multiple-choice word-analogy questions, the precision of the proposed approach is 43.9%, which is lower than that of LRA suggested by Turney in 2005, but the suggested approach mainly focuses on mining the semantic relations among words.

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33

He, Wentao, Jialu Zhang, Jianfeng Ren, Ruibin Bai, and Xudong Jiang. "Hierarchical ConViT with Attention-Based Relational Reasoner for Visual Analogical Reasoning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (2023): 22–30. http://dx.doi.org/10.1609/aaai.v37i1.25072.

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Raven’s Progressive Matrices (RPMs) have been widely used to evaluate the visual reasoning ability of humans. To tackle the challenges of visual perception and logic reasoning on RPMs, we propose a Hierarchical ConViT with Attention-based Relational Reasoner (HCV-ARR). Traditional solution methods often apply relatively shallow convolution networks to visually perceive shape patterns in RPM images, which may not fully model the long-range dependencies of complex pattern combinations in RPMs. The proposed ConViT consists of a convolutional block to capture the low-level attributes of visual patterns, and a transformer block to capture the high-level image semantics such as pattern formations. Furthermore, the proposed hierarchical ConViT captures visual features from multiple receptive fields, where the shallow layers focus on the image fine details while the deeper layers focus on the image semantics. To better model the underlying reasoning rules embedded in RPM images, an Attention-based Relational Reasoner (ARR) is proposed to establish the underlying relations among images. The proposed ARR well exploits the hidden relations among question images through the developed element-wise attentive reasoner. Experimental results on three RPM datasets demonstrate that the proposed HCV-ARR achieves a significant performance gain compared with the state-of-the-art models. The source code is available at: https://github.com/wentaoheunnc/HCV-ARR.

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Aytimur, Mehmet, Theodoros Chondrogiannis, and Michael Grossniklaus. "SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–26. https://doi.org/10.1145/3725355.

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Cardinality estimation is a central task of cost-based database query optimization. Accurate estimates enable optimizers to identify and avoid expensive plans requiring large intermediate results. While cardinality estimation has been studied extensively in relational databases, research in the setting of graph databases has been more scarce. Furthermore, recent studies have shown that machine-learning-based methods can be utilized for cardinality estimation in both relational and graph databases. In this paper, we focus on the problem of estimating the cardinality of path patterns in graph databases, and we propose the Sequence-based Path Pattern Cardinality Estimator (SPACE). Our approach treats path patterns as sequences of node labels and edge types and assign similar cardinalities to path patterns with similar node and edge order. SPACE uses a dual approach: it encodes the sequence of nodes and edges to capture structural characteristics of the path pattern, while also incorporating a cardinality-based encoding to integrate cardinality information throughout learning. In a comprehensive experimental evaluation, we show that our method outperforms the state of the art in terms of both accuracy ( Q -error) and training time.

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Artioli, Giovanna, Luca Ghirotto, Sara Alquati, and Silvia Tanzi. "Behavioral Patterns in Breaking Bad News Communication: An Ethnographic Study with Hematologists." International Journal of Environmental Research and Public Health 19, no. 5 (2022): 2585. http://dx.doi.org/10.3390/ijerph19052585.

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Hematologists adequately disclosing bad news is a critical point precluding patient-centered communication. Specific courses on communication for hematologists seem to be rare, as well as research exploring their communicative skills and patterns. We aim at describing the hematologists’ behavior during difficult conversations to account for behavioral patterns in communication and provide new insights regarding teaching skills to communicate bad news. We employed a focused visual ethnography to answer the following research: “what are hematologists’ behavioral patterns in communicating bad news to patients and families?” The collected data included (1) video recordings, (2) observational field notes, (3) interviews with hematologists. The analysis highlighted four patterns: (1) a technical-defensive pattern, (2) an authoritative pattern, (3) a relational-recursive pattern, and (4) a compassionate sharing pattern. Hematologists seem to have difficulty expressing compassionate caring and empathetic comprehension. Communication skills remain a challenge for hematologists. The study of behavioral patterns can lead to increasingly targeted training interventions for this specific learner population.

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Song, Heng, Lun Zhao, Zi Fei Fan, Xue Lin Wu, and Jian Xin Li. "Optimizing Well Spacing Using Srkachef Relational Expression." Advanced Materials Research 616-618 (December 2012): 891–97. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.891.

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With the remarkable improvement in recognition concerning the feature of the reservoir, a comprehensive adjustment is required to be made during the process of field development. Among currently prevalent methods, well pattern thickening is regarded as the most effective way to maintain or boost the oil productivity. However, to avoid the consequent high development cost of this method, optimizing a reasonable well spacing becomes a necessity to ensure a desirable effect of exploitation as well as an advanced level of economic effectiveness. In this paper, the author sets Zhanazhol Oilfield as an example and uses Srkachef relational expression to provide an accurate method, in which gives a detailed illustration about optimizing economic limit well spacing and economic optimal well spacing in different thickness reservoirs. Given its favorable adaptability, this method will become a valuable reference for the oilfield development in relation to well pattern deployment and thickening in late period.

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Kim, Jinhyung, Dongwon Jeong, and Doo-Kwon Baik. "Query Pattern-based Relational Data to XML Data Translation Algorithm." Journal of Computer Science 3, no. 4 (2007): 212–17. http://dx.doi.org/10.3844/jcssp.2007.212.217.

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Held, James P., and John V. Carlis. "MATCH—a new high-level relational operator for pattern matching." Communications of the ACM 30, no. 1 (1987): 62–75. http://dx.doi.org/10.1145/7885.7889.

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Ackerman, C. M., and S. Courtney. "fMRI Pattern Classification of Visual Relational and Item-Specific Information." NeuroImage 47 (July 2009): S135. http://dx.doi.org/10.1016/s1053-8119(09)71323-0.

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Wang, Lian Sheng, Ting Jun Li, Tao Sun, Zhi Yong Liu, and Xiao Dong Sun. "The Database Design Based on Native XML Database Technology." Applied Mechanics and Materials 241-244 (December 2012): 2561–64. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2561.

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IETM database standardized on S1000D consists of XML documents. In view of former relational database treat XML documents defectively, design storage and index pattern of IETM database which is based on features of module and information object standardized on S1000D with relational XML database technology. There is a certain significance to broaden.

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Yan, Weidan, and Yongsheng Dong. "Local Directional Difference and Relational Descriptor for Texture Classification." Mathematics 12, no. 21 (2024): 3432. http://dx.doi.org/10.3390/math12213432.

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The local binary pattern (LBP) has been widely used for extracting texture features. However, the LBP and most of its variants tend to focus on pixel units within small neighborhoods, neglecting differences in direction and relationships among different directions. To alleviate this issue, in this paper, we propose a novel local directional difference and relational descriptor (LDDRD) for texture classification. Our proposed LDDRD utilizes information from multiple pixels along the radial direction. Specifically, a directional difference pattern (DDP) is first extracted by performing binary encoding on the differences between the central pixel and multiple neighboring pixels along the radial direction. Furthermore, by taking the central pixel as a reference, we extract the directional relation pattern (DRP) by comparing binary encodings representing different directions. Finally, we fuse the above DDP and DRP to form the LDDRD feature vector. Experimental results on six texture datasets reveal that our proposed LDDRD is effective and outperforms eight representative methods.

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López Hernández, Francisca, and Socorro Bernardos Galindo. "A relational adjective and a noun semantic binding in the specialized language of Information and Communication Technology." Revista Española de Lingüística Aplicada/Spanish Journal of Applied Linguistics 31, no. 1 (2018): 197–223. http://dx.doi.org/10.1075/resla.15037.lop.

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Abstract This study reports on a semantic analysis of a terminology pattern formed by a relational adjective Radj and a noun n, found in specialized texts written in English and Spanish from the Information and Communication Technology (ICT) field. This research is first based on a terminology perspective to later focus on a recurring multi-word lexical unit pattern in which the specialized concept is realized by a relational adjective. The syntactic pattern [Radj+n] will be referred to as Specialized Lexical Combination (SLC). The study presents a step forward to previous terminology research. We argue that the semantic analysis of the adjective-noun relationship will help understand the underlying knowledge organization of this ICT subject area. The analysis is approached from the framework of the Generative Lexicon specially focusing on the qualia structure of this recurring multi-word lexical unit pattern.

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Horne, L. Chad. "INSURANCE AND EQUALITY REVISITED." Public Affairs Quarterly 32, no. 3 (2018): 205–26. http://dx.doi.org/10.2307/26909994.

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Abstract Theorists of the welfare state increasingly recognize that social insurance programs are not well-justified by distributive egalitarianism, meaning concern for equality considered as a pattern in the distribution of some good. However, recent work by several relational egalitarian theorists suggests that these programs may be justified on relational egalitarian grounds. Relational egalitarians hold that the proper object of egalitarian concern is the way that citizens relate to one another. In this paper, I review the problems facing a distributive egalitarian justification for social insurance before considering and rejecting three relational egalitarian justifications. I close by offering a justification for these programs grounded in efficiency, not equality.

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Li, Jianfeng, and Dexiang Yang. "Research on Financial Fraud Detection Models Integrating Multiple Relational Graphs." Systems 11, no. 11 (2023): 539. http://dx.doi.org/10.3390/systems11110539.

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The current fraud risk in digital finance is increasing year by year, and the mainstream solutions rely on the inherent characteristics of users, which makes it difficult to explain fraud behaviors and fraud behavior patterns are less researched. To address these problems, we propose an integrated multiple relational graphs fraud detection model Tri-RGCN-XGBoost, which analyzes the impact of user association patterns on fraud detection by mining the behavioral associations of users. The model builds a heterogeneous information network based on real transaction data, abstracts three types of bipartite graphs (user–device, user–merchant, and user–address), aggregates the information of the user’s neighbor nodes under the three types of behavioral patterns, and integrates the graph convolution classification results under the three behavioral patterns with the XGBoost model to achieve fraudulent user detection with integrated multiple relational graphs. The results show that the performance of this model in fraud identification is significantly improved, especially in reducing the fraudulent user underreporting rate. Further, the behavioral associations that play a key role in fraud user identification are analyzed in conjunction with shape value to provide a reference for fraud pattern mining.

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Linnell, Karina J., and David H. Foster. "Dependence of Relational Colour Constancy on the Extraction of a Transient Signal." Perception 25, no. 2 (1996): 221–28. http://dx.doi.org/10.1068/p250221.

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Human observers can correctly attribute changes in the appearance of a scene either to changes in the incident light or to changes in the spectral-reflectance properties of the scene. This ability was assessed as a function of the time course of illuminant and spectral-reflectance changes. Observers were presented with computer simulations of Mondrian patterns of 49 randomly selected Munsell papers. On each trial a Mondrian pattern was presented for 1 s; the pattern then changed either instantaneously or gradually into another Mondrian pattern, also presented for 1 s, which was related to the first either by an illuminant change or by an illuminant change accompanied by additional changes in the spectral-reflectance functions of the individual papers. Illuminant and spectral-reflectance changes were applied linearly in time (with respect to CIE coordinates) over intervals ranging from 0 to 7 s. Observers indicated whether there was a spectral-reflectance change. They were able to make reliable discriminations between illuminant and spectral-reflectance changes both when the changes were applied instantaneously and when they were applied gradually over time, but performance worsened progressively as the duration of the changes increased, that is, as their rate decreased. It is suggested that discrimination in this task depends on the extraction of a low-level transient signal which is generated in response to rapid changes in scene appearance and which is progressively attenuated as changes occur more and more gradually.

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KUNER, PETER, and BIRGIT UEBERREITER. "PATTERN RECOGNITION BY GRAPH MATCHING—COMBINATORIAL VERSUS CONTINUOUS OPTIMIZATION." International Journal of Pattern Recognition and Artificial Intelligence 02, no. 03 (1988): 527–42. http://dx.doi.org/10.1142/s0218001488000303.

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A generalization of subgraph isomorphism for the fault-tolerant interpretation of disturbed line images has been achieved. Object recognition is effected by optimal matching of a reference graph to the graph of a distorted image. This optimization is based on the solution of linear and quadratic assignment problems. The efficiency of the procedures developed for this objective has been proved in practical applications. NP-complete problems such as subgraph recognition need exhaustive computation if exact (branch-and-bound) algorithms are used. In contrast to this, heuristics are very fast and sufficiently reliable for less complex relational structures of the kind investigated in the first part of this paper. Constrained continuous optimization techniques, such as relaxation labeling and neural network strategies, solve recognition problems within a reasonable time, even in rather complex relational structures where heuristics can fail. They are also well suited to parallelism. The second part of this paper is devoted exclusively to them.

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Palagashvili, A. M., and S. A. Stupnikov. "Reversible Mapping of Relational and Graph Databases." Pattern Recognition and Image Analysis 33, no. 2 (2023): 113–21. http://dx.doi.org/10.1134/s1054661823020098.

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Uğur, Ayşegül Altay. "Textures and dynamic relational systems." International Journal of Machine Learning and Cybernetics 9, no. 5 (2016): 881–91. http://dx.doi.org/10.1007/s13042-016-0616-x.

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Jager, Justin. "Convergence and nonconvergence in the quality of adolescent relationships and its association with adolescent adjustment and young-adult relationship quality." International Journal of Behavioral Development 35, no. 6 (2011): 497–506. http://dx.doi.org/10.1177/0165025411422992.

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With the aim of identifying and examining both convergence (matched relationship quality across one’s set of relationships) and nonconvergence (mixed relationship quality across one’s set of relationships), the present study used a pattern-centered approach to examine the different ways adolescent relationships pattern together among a large, national sample of U.S. adolescents (aged 13–19). The study also examined how adolescent adjustment and young-adult relationship quality varied across the different relationship patterns or constellations. The current study used latent class analysis and data from Add Health ( n = 4,233), a national U.S. longitudinal study that spans adolescence and young adulthood, to uncover heterogeneity in adolescent relations with parents, friends, romantic partners, peers, and teachers. As predicted, patterns of both convergence and nonconvergence were found, though patterns of nonconvergence were more common than expected. Some patterns of nonconvergence appear more stable (i.e., similar pattern found during both adolescence and young adulthood) than others. Also, no “high” converging pattern was found, indicating that few adolescents have “first-rate” relations in every relational domain.

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Yang, Fan, and Cai Li Zhang. "Research on Rough Set Based Weighted Grey Fault Diagnosis Algorithm and Practical Application." Applied Mechanics and Materials 65 (June 2011): 272–75. http://dx.doi.org/10.4028/www.scientific.net/amm.65.272.

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Considering the poor accuracy of grey relational analysis method in fault diagnosis field, a rough set based weighted grey fault diagnosis algorithm is provided. The algorithm extracts the core characteristic parameters described the fault description and calculate their weight with rough sets and its attribute reduction method, the possible fault pattern of the unknown pattern is judged by the relation degree which calculated quantitatively with each typical fault pattern in history diagnosis record based on weighted grey relational analysis method. Experiment result of recognizing a diesel engine working state indicates that rough set based weighted grey fault diagnosis algorithm find effectively the optimization characteristics parameter for fault description, emphasize the importance of the different characteristics parameters, improve the accuracy of grey diagnose algorithm, and can play significant performance in actual application.

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