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Journal articles on the topic 'Attribute Database'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Georgieva, Tsvetanka. "Methods for Investigation of Dependencies between Attributes in Databases." Serdica Journal of Computing 3, no. 3 (2009): 319–34. http://dx.doi.org/10.55630/sjc.2009.3.319-334.

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This paper surveys research in the field of data mining, which is related to discovering the dependencies between attributes in databases. We consider a number of approaches to finding the distribution intervals of association rules, to discovering branching dependencies between a given set of attributes and a given attribute in a database relation, to finding fractional dependencies between a given set of attributes and a given attribute in a database relation, and to collaborative filtering.

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Zhu, Yongjie, and Shenzhan Feng. "A Matching Method of Heterogeneous Database based on SOM and BP Neural Network." International Journal of Circuits, Systems and Signal Processing 15 (April 22, 2021): 383–92. http://dx.doi.org/10.46300/9106.2021.15.42.

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In the process of data integration among heterogeneous databases, it is significantly important to analyze the identical attributes and characteristics of the databases. However, the existing main data attribute matching model has the defects of oversize matching space and low matching precision. Therefore, this paper puts forward a heterogeneous data attribute matching model on the basis of fusion of SOM and BP network through analyzing the attribute matching process of heterogeneous databases. This model firstly matches the heterogeneous data attributes in advance by SOM network to determine

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RANDALL, D. J., H. J. HAMILTON, and R. J. HILDERMAN. "TEMPORAL GENERALIZATION WITH DOMAIN GENERALIZATION GRAPHS." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 02 (1999): 195–217. http://dx.doi.org/10.1142/s0218001499000124.

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This paper addresses the problem of using domain generalization graphs to generalize temporal data extracted from relational databases. A domain generalization graph associated with an attribute defines a partial order which represents a set of generalization relations for the attribute. We propose formal specifications for domain generalization graphs associated with calendar (date and time) attributes. These graphs are reusable (i.e. can be used to generalize any calendar attributes), adaptable (i.e. can be extended or restricted as appropriate for particular applications), and transportable

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Chen, Ganlang. "Research on Big Data Attribute Selection Method in Submarine Optical Fiber Network Fault Diagnosis Database." Polish Maritime Research 24, s3 (2017): 221–27. http://dx.doi.org/10.1515/pomr-2017-0126.

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Abstract At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper, a large data attribute selection method based on support vector machines (SVM) for fault diagnosis database of submarine optical fiber network is proposed. Mining large data in the database of optical fiber network fault diagnosis, and calculate its attribute weight, attribute classification is completed according to attribute weight

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Kolesnikova, V. M., I. O. Alyabina, L. A. Vorob’eva, E. N. Molchanov, S. A. Shoba, and V. A. Rozhkov. "Soil attribute database of Russia." Eurasian Soil Science 43, no. 8 (2010): 839–47. http://dx.doi.org/10.1134/s1064229310080016.

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Su, Wei, Xue Zhang, and Jia Jing Xu. "A Fuzzy Clustering Algorithm Based on Parameter Optimization in Large Transaction Database." Advanced Materials Research 989-994 (July 2014): 2431–37. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2431.

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In view of the discretization of continuous attributes of civil aviation radar intelligence data, this paper proposes a fuzzy partition algorithm of continuous attributes based on weighted index and optimization of clustering number, and its automatic determination of optimal weighted index m and optimal clustering number c overcomes the shortcomings of current attribute fuzzy methods of manual determination of classification number and no consideration of geometry data. The experimental results verify the validity and feasibility of fuzzy attribute discretization of civil aviation radar intel

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Mohamad Hassin Azeez, Naofal. "Data Mining Approach for Predicting Learner's Achievement." University of Thi-Qar Journal of Science 6, no. 2 (2017): 104–12. http://dx.doi.org/10.32792/utq/utjsci/v6i2.23.

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Student achievement variables that may be included into student database can be classified into three main categories, student variables. Instructor variables and general variables. This paper presents a new machine-learning model for extracting knowledge From student attributes in a given database. This knowledge can be used for determining the relative importance and effectiveness of student's attributes for the prediction of their college academic achievement, and the relationship between these attributes and their achievement. The model includes three main algorithms namely: preprocessing

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Liu, Kaiping, Hee Beng Kuan Tan, and Xu Chen. "Aiding Maintenance of Database Applications Through Extracting Attribute Dependency Graph." Journal of Database Management 24, no. 1 (2013): 20–35. http://dx.doi.org/10.4018/jdm.2013010102.

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Database is a major component of many software systems. This paper proposes a novel graph called the attribute dependency graph to reveal the dependencies between attributes in a database application and also the programs involved. The authors propose an approach to automatically extract the attribute dependency graph out of a database application from its source code through inter-procedural static program analysis. The extracted information is a straightforward indicator that benefits the maintenance process, particularly for impact analysis on the modifications in a database application. A

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Ulybyshev, Denis, Michael Rogers, Vadim Kholodilo, and Bradley Northern. "End-to-End Database Software Security." Software 2, no. 2 (2023): 163–76. http://dx.doi.org/10.3390/software2020007.

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End-to-end security is essential for relational database software. Most database management software provide data protection at the server side and in transit, but data are no longer protected once they arrive at the client software. In this paper, we present a methodology that, in addition to server-side security, protects data in transit and at rest on the application client side. Our solution enables flexible attribute-based and role-based access control, such that, for a given role or user with a given set of attributes, access can be granted to a relation, a column, or even to a particula

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Chua, Cecil Eng H., Roger H. L. Chiang, and Ee-Peng Lim. "Instance-based attribute identification in database integration." VLDB Journal The International Journal on Very Large Data Bases 12, no. 3 (2003): 228–43. http://dx.doi.org/10.1007/s00778-003-0088-y.

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Zhang, Jie, Yuping Wang, and Junhong Feng. "Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm." Scientific World Journal 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/259347.

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In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective pro

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Kumar, Manoj, and O. P. Verma. "Content characteristics based robust watermarking for relational database: a new approach to database security." International Journal of Engineering & Technology 7, no. 1.9 (2018): 234. http://dx.doi.org/10.14419/ijet.v7i1.9.10003.

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Digital data such as text, relational database, audio, video and software are intellectual property of creators/ writers/owners. The database services have become easily available and economical since the booming of internet. However, their outsourcing through the internet accompanies multiple threats like copying, modifying as well as unauthorized distribution. Relational Database has a wide-spread use in many real-life applications, hence, it is essential to maintain integrity and provide copyright protection. To counter the threats, watermarking techniques have been playing a vital role sin

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Kumar, Manoj, and O. P. Verma. "Content Characteristics Based Robust Watermarking for Relational Database: A New Approach to Database Security." International Journal of Engineering & Technology 7, no. 1.9 (2018): 302. http://dx.doi.org/10.14419/ijet.v7i1.9.12694.

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Digital data such as text, relational database, audio, video and software are intellectual property of creators/ writers/owners. The database services have become easily available and economical since the booming of internet. However, their outsourcing through the internet accompanies multiple threats like copying, modifying as well as unauthorized distribution. Relational Database has a wide-spread use in many real-life applications, hence, it is essential to maintain integrity and provide copyright protection. To counter the threats, watermarking techniques have been playing a vital role sin

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Rajasekar, Devaraj, and Lourdusamy Robert. "Unsupervised Word Embedding with Ensemble Deep Learning for Twitter Rumor Identification." Revue d'Intelligence Artificielle 36, no. 5 (2022): 769–76. http://dx.doi.org/10.18280/ria.360515.

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In social networks, rumor identification is a major problem. The structural data in a topic is applied to derive useful attributes for rumor identification. Most standard rumor identification methods concentrate on local structural attributes, ignoring the global structural attributes that exist between the source tweet and its responses. To tackle this issue, a Source-Replies relation Graph (SR-graph) has been built to develop an Ensemble Graph Convolutional neural Net (EGCN) with a Nodes Proportion Allocation Mechanism (NPAM) which identifies the rumor. But, the word vectors were trained by

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Jiang, Feng, Yuefei Sui, and Cungen Cao. "Formal Concept Analysis in Relational Database and Rough Relational Database." Fundamenta Informaticae 80, no. 4 (2007): 435–51. https://doi.org/10.3233/fun-2007-80405.

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Since its foundation in the early 1980's, Formal ConceptAnalysis (FCA) has been used in many applications in data analysis, information retrieval, and knowledge discovery. In this paper, we suggest to exploit the framework of relational database model (RDM) and rough relational database model (RRDM) for Formal Concept Analysis. The basic idea is as follows. We firstly treat any relation (R,A) of RDM as a many-valued context of FCA. But for the rough relations of RRDM, we define a special kind of many-valued context – rough-relational context in FCA (In this kind of context, every attribute val

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Post, Gerald, and Albert Kagan. "Database management systems: design considerations and attribute facilities." Journal of Systems and Software 56, no. 2 (2001): 183–93. http://dx.doi.org/10.1016/s0164-1212(00)00096-0.

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Tian, Jianwei, Shijun Li, and Xiaoyue Tang. "Web database sampling approach based on attribute correlation." Wuhan University Journal of Natural Sciences 15, no. 4 (2010): 297–302. http://dx.doi.org/10.1007/s11859-010-0655-1.

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Huang, Wenmin, Weiqi Luo, Jiwu Huang, and Xiaochun Cao. "SDGAN: Disentangling Semantic Manipulation for Facial Attribute Editing." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (2024): 2374–81. http://dx.doi.org/10.1609/aaai.v38i3.28012.

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Facial attribute editing has garnered significant attention, yet prevailing methods struggle with achieving precise attribute manipulation while preserving irrelevant details and controlling attribute styles. This challenge primarily arises from the strong correlations between different attributes and the interplay between attributes and identity. In this paper, we propose Semantic Disentangled GAN (SDGAN), a novel method addressing this challenge. SDGAN introduces two key concepts: a semantic disentanglement generator that assigns facial representations to distinct attribute-specific editing

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Demetrovics, Janos, Nguyen Long Giang, Vu Duc Thi, and Pham Viet Anh. "On the Problem Related to Reductive Attributes in the Incomplete Decision Tables." Serdica Journal of Computing 16, no. 1 (2022): 24–38. http://dx.doi.org/10.55630/sjc.2022.16.24-38.

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Attribute reduction is a key problem in the process of data mining and knowledge discovery. Up to now, many attribute reduction algorithms in incomplete decision tables have been proposed. However, the research results related to conditional attributes and reduct of incomplete decision tables are still limited. By relational database approach, this paper investigates some properties of conditional attributes and proposes an algorithm to determine all reductive attributes of consistent incomplete decision tables in polynomial time. The proposed algorithm is an effective tool to eliminate all re

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Hyun, Changhun, Jeongin Seo, Kyeong Eun Lee, and Hyeyoung Park. "Multi-Attribute Recognition of Facial Images Considering Exclusive and Correlated Relationship Among Attributes." Applied Sciences 9, no. 10 (2019): 2034. http://dx.doi.org/10.3390/app9102034.

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Multi-attribute recognition is one of the main topics attaining much attention in the pattern recognition field these days. The conventional approaches to multi-attribute recognition has mainly focused on developing an individual classifier for each attribute. However, due to rapid growth of deep learning techniques, multi-attribute recognition using multi-task learning enables the simultaneous recognition of more than two relevant recognition tasks through a single network. A number of studies on multi-task learning have shown that it is effective in improving recognition performance for all

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Nguyen, Hoa. "A probabilistic relational database model and algebra." Journal of Computer Science and Cybernetics 31, no. 4 (2015): 305. http://dx.doi.org/10.15625/1813-9663/31/4/5742.

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This paper introduces a probabilistic relational database model, called PRDB, for representing and querying uncertain information of objects in practice. To develop the PRDB model, first, we represent the relational attribute value as a pair of probabilistic distributions on a set for modeling the possibility that the attribute can take one of the values of the set with a probability belonging to the interval which is inferred from the pair of probabilistic distributions. Next, on the basis representing such attribute values, we formally define the notions as the schema, relation, probabilisti

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Mosteiro-Sanchez, Aintzane, Marc Barcelo, Jasone Astorga, and Aitor Urbieta. "Trustworthy Users: Using IOTA and IPFS for Attribute Validation in CP-ABE and dCP-ABE Schemes." Smart Cities 6, no. 2 (2023): 913–28. http://dx.doi.org/10.3390/smartcities6020044.

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Attribute spoofing is a major security threat in information exchange solutions based on Ciphertext-Policy Attribute-Based-Encryption (CP-ABE) and distributed CP-ABE (dCP-ABE), which can compromise privacy and security. This threat occurs when an attacker forces the Attribute Authorities to generate keys for attributes they do not possess. This paper analyzes the threat of attribute spoofing and identifies the primary attack vectors, including direct interference with the Attribute Authority and compromise of the shared attribute storage database. The authors propose a solution based on IOTA,

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Apiletti, Daniele, Giulia Bruno, Elisa Ficarra, and Elena Baralis. "Data Cleaning and Semantic Improvement in Biological Databases." Journal of Integrative Bioinformatics 3, no. 2 (2006): 219–29. http://dx.doi.org/10.1515/jib-2006-40.

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Summary Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors). We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and inte

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Quek, Jia Yi Vivian, Ying Han Pang, Zheng You Lim, Shih Yin Ooi, and Wee How Khoh. "Customer Churn Prediction through Attribute Selection Analysis and Support Vector Machine." Journal of Telecommunications and the Digital Economy 11, no. 3 (2023): 180–94. http://dx.doi.org/10.18080/jtde.v11n3.777.

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An accurate customer churn prediction could alert businesses about potential churn customers so that proactive actions can be taken to retain the customers. Predicting churn may not be easy, especially with the increasing database sample size. Hence, attribute selection is vital in machine learning to comprehend complex attributes and identify essential variables. In this paper, a customer churn prediction model is proposed based on attribute selection analysis and Support Vector Machine. The proposed model improves churn prediction performance with reduced feature dimensions by identifying th

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Nguyen, Hoa. "Extended Relational Database Model for Interval Probability Set-Valued Attributes." International Journal of Information Technology and Computer Science Applications 3, no. 1 (2025): 11–24. https://doi.org/10.58776/ijitcsa.v3i1.174.

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In this paper, we introduce a new probabilistic relational database model as an extension of the classical relational database model for interval probability set-valued attributes to represent and handle uncertain and imprecise information in practice. To develop the new model, we use extended probabilistic values for representing interval probability set-valued relational attributes and the probabilistic interpretation of binary relations on sets for computing uncertain degree of functional dependencies, keys and relations on attribute values, and propose the new combination strategies of ext

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Sokolova, A. V., E. V. Login, G. A. Mashkovtsev, and I. S. Grishanov. "Package for data management of a telecommunication device in a monitoring system." E3S Web of Conferences 549 (2024): 08026. http://dx.doi.org/10.1051/e3sconf/202454908026.

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In order to identify the role of data storage in the monitoring system of a telecommunications device, a conceptual design method was used, which was based on the basic principles of the Telecommunication Management Network concept, which is a network management system for telecommunication operators. Based on this concept, it was possible to design a data storage model in the monitoring system of a telecommunications device, which clearly reflects the separation of databases involved in the telecommunications network at different levels of the concept. A description of the differences between

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Abdul Rahman, A., H. Rashidan, I. A. Musliman, G. Buyuksalih, S. Bayburt, and P. Baskaraca. "3D GEOSPATIAL DATABASE SCHEMA FOR ISTANBUL 3D CITY MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 11–16. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-11-2019.

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Abstract. This paper describes the development of 3D database for Istanbul 3D city models. The schema is based on object-relational technology and also called spatially-enhanced relational database management system (SRDBMS). The 3D city models were generated based on LiDAR points cloud with other several typical GIS datasets like terrain, orthophoto, Point of Interests (POIs), and other attribute data. The database is based on PostGIS schema and CityGML schema (3DCityDB). Two major datasets, namely, terrain data (with several formats), and 3D city models were populated in the database. Terrai

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Camara, Lancine, Junyi Li, Renfa Li, and Wenyong Xie. "Distortion-Free Watermarking Approach for Relational Database Integrity Checking." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/697165.

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Nowadays, internet is becoming a suitable way of accessing the databases. Such data are exposed to various types of attack with the aim to confuse the ownership proofing or the content protection. In this paper, we propose a new approach based on fragile zero watermarking for the authentication of numeric relational data. Contrary to some previous databases watermarking techniques which cause some distortions in the original database and may not preserve the data usability constraints, our approach simply seeks to generate the watermark from the original database. First, the adopted method par

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Wastl, Ralf. "Linear Derivations for Keys of a Database Relation Schema." JUCS - Journal of Universal Computer Science 4, no. (12) (1998): 883–97. https://doi.org/10.3217/jucs-004-12-0883.

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In [Wastl 1998] we have introduced the Hilbert style inference system K for deriving all keys of a database relation schema. In this paper we investigate formal K-derivations more closely using the concept of tableaux. The analysis gives insight into the process of deriving keys of a relation schema. Also, the concept of tableaux gives a proof procedure for computing all keys of a relation schema. In practice, the methods developed here will be usefull for computing keys or for deciding whether an attribute is a key attribute, respectively non-key attribute. This decision problem becomes relev

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J. Mokadam, Ms Pragati. "Data attribute security and privacy in distributed database system." IOSR Journal of Computer Engineering 16, no. 2 (2014): 27–33. http://dx.doi.org/10.9790/0661-16252733.

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Gervais, Frédéric, Marc Frappier, and Régine Laleau. "Generating relational database transactions from eb 3 attribute definitions." Software & Systems Modeling 8, no. 3 (2008): 423–45. http://dx.doi.org/10.1007/s10270-008-0104-1.

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Gexu, Tan, Jing Xu, Liu Zhengnan, and Qiao Bin. "Sharing Attribute Names based LSH across Cloud Relational Database." International Journal of Database Theory and Application 9, no. 4 (2016): 247–58. http://dx.doi.org/10.14257/ijdta.2016.9.4.23.

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De, Soumitra, and Jaydev Mishra. "Neutrosophic Logic - A Better Approach to Execute Imprecise Queries Through the Neutrosophic Database Model." Indian Journal Of Science And Technology 17, no. 29 (2024): 2981–91. http://dx.doi.org/10.17485/ijst/v17i29.673.

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Objectives: The neutrosophic set has a more powerful ability to process imprecise information compared to the vague set. The objective of the authors is to process the uncertain query using vague as well as neutrosophic logic and compare the result. Methods: Authors have designed a new architecture to process uncertain queries using vague as well as neutrosophic sets. In the architecture at first, the imprecise query has been taken as input. From the inputted imprecise query uncertain data and fuzzy attributes are identified. Next, using the truth membership algorithm the truth membership valu

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Cristofor, Dana, and Dan Simovici. "Finding Median Partitions Using Information-Theoretical-Based Genetic Algorithms." JUCS - Journal of Universal Computer Science 8, no. (2) (2002): 153–72. https://doi.org/10.3217/jucs-008-02-0153.

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In a database with categorical attributes, each attribute defines a partition whose classes can be regarded as natural clusters of rows. In this paper we focus on finding a partition of the rows of a given database, that is as close as possible to the partitions associated to each attribute. We evaluate the closeness of two partitions by using a generalization of the classical conditional entropy. From this perspective, we wish to construct a partition (referred to as the median partition) such that the sum of the dissimilarities between this partition and all the partitions determined by the

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SHAN, NING, HOWARD J. HAMILTON, and NICK CERCONE. "GRG: KNOWLEDGE DISCOVERY USING INFORMATION GENERALIZATION, INFORMATION REDUCTION, AND RULE GENERATION." International Journal on Artificial Intelligence Tools 05, no. 01n02 (1996): 99–112. http://dx.doi.org/10.1142/s0218213096000079.

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We present the three-step GRG approach for learning decision rules from large relational databases. In the first step, an attribute-oriented concept tree ascen sion technique is applied to generalize an information system. This step loses some information but substantially improves the efficiency of the following steps. In the second step, a reduction technique is applied to generate a minimalized information system called a reduct which contains a minimal subset of the generalized attributes and the smallest number of distinct tuples for those attributes. Finally, a set of maximally general r

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Al-Saraireh, Jaafer, and Majid Hassan. "A New Attribute-Based Access Control Model for RDBMS." Cybernetics and Information Technologies 22, no. 4 (2022): 3–22. http://dx.doi.org/10.2478/cait-2022-0036.

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Abstract One of the challenges in Attribute-Based Access Control (ABAC) implementation is acquiring sufficient metadata against entities and attributes. Intelligent mining and extracting ABAC policies and attributes make ABAC implementation more feasible and cost-effective. This research paper focuses on attribute extraction from an existing enterprise relational database management system – RDBMS. The proposed approach tends to first classify entities according to some aspects of RDBMS systems. By reverse engineering, some metadata elements and ranking values are calculated for each part. The

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Qaosar, Mahboob, Asif Zaman, Md Siddique, Annisa, and Yasuhiko Morimoto. "Privacy-Preserving Secure Computation of Skyline Query in Distributed Multi-Party Databases." Information 10, no. 3 (2019): 119. http://dx.doi.org/10.3390/info10030119.

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Selecting representative objects from a large-scale database is an essential task to understand the database. A skyline query is one of the popular methods for selecting representative objects. It retrieves a set of non-dominated objects. In this paper, we consider a distributed algorithm for computing skyline, which is efficient enough to handle “big data”. We have noticed the importance of “big data” and want to use it. On the other hand, we must take care of its privacy. In conventional distributed algorithms for computing a skyline query, we must disclose the sensitive values of each objec

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Hui, Guo. "Management of Water Quality Information in Mining Subsidence Waterlogged Area." Advanced Materials Research 726-731 (August 2013): 3702–5. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.3702.

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Based of the technology of CAD VBA and Access database, the program of water quality monitoring information management in mining subsidence area is developed; it mainly includes functions of attribute query, attribute edition, visualization of water monitoring point. The table structure in monitoring point attribute database is designed, and problem of dynamic linkage between drawing data and attribute data is solved. The key code about them is given in the paper. The program can provide some decision support for reasonable use of water resources and environment protection in the mine area, an

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Nadkarni, Prakash M. "QAV: querying entity-attribute-value metadata in a biomedical database." Computer Methods and Programs in Biomedicine 53, no. 2 (1997): 93–103. http://dx.doi.org/10.1016/s0169-2607(97)01815-4.

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Patterson, Genevieve, Chen Xu, Hang Su, and James Hays. "The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding." International Journal of Computer Vision 108, no. 1-2 (2014): 59–81. http://dx.doi.org/10.1007/s11263-013-0695-z.

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Kim, Byungwook, and Songchun Moon. "A flexible indexing structure supporting multi-attribute database applications: MAIN." Microprocessing and Microprogramming 39, no. 2-5 (1993): 177–80. http://dx.doi.org/10.1016/0165-6074(93)90083-w.

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Yager, Ronald R., Naif Alajlan, and Yakoub Bazi. "Uncertain database retrieval with measure-based belief function attribute values." Information Sciences 501 (October 2019): 761–70. http://dx.doi.org/10.1016/j.ins.2019.03.074.

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Kim, Byungwook, and Songchun Moon. "A new indexing scheme supporting multi-attribute database applications: MAX." Journal of Systems Architecture 42, no. 2 (1996): 144–62. http://dx.doi.org/10.1016/1383-7621(96)80001-m.

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Yu, Yong Hong, and Wen Yang Bai. "Enforcing Data Privacy in Outsourced Database Services." Advanced Materials Research 255-260 (May 2011): 2224–28. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2224.

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Advances in networking technologies and the continued growth of the internet have triggered a new trend towards outsourcing data management and information technology needs to external service providers, and privacy requirements have an increasing impact on such real-world applications. In this paper, we propose a solution to enforce data privacy over outsourced database services. The approach starts from a flexible definition of privacy constraints on a relational schema, applies encryption on information in parsimonious way and mostly relies on attribute partition to protect sensitive inform

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Nguyễn, Hòa. "EXTENDING RELATIONAL DATABASE MODEL FOR UNCERTAIN INFORMATION." Journal of Computer Science and Cybernetics 35, no. 4 (2019): 355–72. http://dx.doi.org/10.15625/1813-9663/35/4/13907.

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In this paper, we propose a new probabilistic relational database model, denote by PRDB, as an extension of the classical relational database model where the uncertainty of relational attribute values and tuples are respectively represented by finite sets and probability intervals. A probabilistic interpretation of binary relations on finite sets is proposed for the computation of their probability measures. The combination strategies on probability intervals are employed to combine attribute values and compute uncertain membership degrees of tuples in a relation. The fundamental concepts of t

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El-Haggar, Nahla, Elkhouly Mahmoud M., and Abu El Alla Samah S. "Blind Watermarking Technique for Relational Database." COMPUSOFT: An International Journal of Advanced Computer Technology 02, no. 05 (2013): 121–26. https://doi.org/10.5281/zenodo.14602835.

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Recently, using of relational database system in many real life applications is increased. Therefore watermarking is considered as a vital technique for copyright protection of relational database. In this paper, we embedded watermark into some non numeric attribute. The generation of watermark depends on hash function and secret key to increase the security and the difficulty to guess by attackers. Our proposed technique is fully blind, which means that no need for the original tables to detect the watermark. 

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HOSAIN, MD SHAZZAD, and MUHAMMAD ABDUL HAKIM NEWTON. "MULTI-KEY INDEX FOR DISTRIBUTED DATABASE SYSTEM." International Journal of Software Engineering and Knowledge Engineering 15, no. 02 (2005): 433–38. http://dx.doi.org/10.1142/s0218194005002075.

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In this paper we present a multi-key index model that enables us to search a record with more than one attribute values in distributed database systems. Indices provide fast and efficient access of data and so become a major aspect in centralized database systems. Most of the centralized database systems use B + tree or other types of index structures such as bit vector, graph structure, grid file etc. But in distributed database systems no index model is found in the literature. Therefore efficient access is a major problem in distributed databases. Our proposed index model avoids the query-f

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Ren, Xiang Min, Jing Yang, Jian Pei Zhang, and Zong Fu Jia. "Uncertain Data Privacy Protection Based on K-Anonymity via Anatomy." Advanced Engineering Forum 6-7 (September 2012): 64–69. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.64.

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In traditional database domain, k-anonymity is a hotspot in data publishing for privacy protection. In this paper, we study how to use k-anonymity in uncertain data set, use influence matrix of background knowledge to describe the influence degree of sensitive attribute produced by QI attributes and sensitive attribute itself, use BK(L,K)-clustering to present equivalent class with diversity, and a novel UDAK-anonymity model via anatomy is proposed for relational uncertain data. We will extend our ideas for handling how to solve privacy information leakage problem by using UDAK-anonymity algor

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Wang, Mao Lin, and Ai Jun Xu. "Design and Implementation of Point Symbol Database Based on ArcGIS Engine." Applied Mechanics and Materials 263-266 (December 2012): 1853–57. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1853.

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In this article, geometric primitive approach is used to realize the design and development of point symbol database for mapping based on C# .NET and ArcGIS Engine. This paper presents the design framework and the design process of point symbol database, and studies design method and attribute management of point symbol, especially the design of point symbol attribute of word type of TrueType, which makes conveniently the point symbol for special map users needed.

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et al., Samra. "Design of a clinical database to support research purposes: Challenges and solutions." International Journal of ADVANCED AND APPLIED SCIENCES 8, no. 3 (2021): 21–29. http://dx.doi.org/10.21833/ijaas.2021.03.003.

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The aim of this paper is to propose solutions to challenges faced by database systems for clinical research purposes. Current clinical databases are primarily based on data acquisition for healthcare intentions. However, these healthcare databases lack the data analysis capability for clinical researchers. In order for clinical researchers to use the healthcare databases in an effective manner, such as in their clinical trial studies, challenges of data integration, data storage, and data retrieval in the current healthcare database settings need to be overcome. Our proposed solutions include

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