Relevant bibliographies by topics / Attribute matching

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Attribute matching'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Attribute matching"

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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 the centre scope of attribute data to be matched. Secondly, the accurate match will be carried out through BP network of the standard heterogeneous data various attribute center. Finally, the matching result of the relevant actual database shows that this model can effectively reduce the matching space in the case of complex pattern. As for the large-scale data matching, the matching accuracy is relatively high. The average precision is 89.52%, and the average recall rate is 100%.
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Ando, Kazuaki, Shoji Mizobuchi, Masami Shishibori, and Jun-Ichi Aoe. "Efficient multi-attribute pattern matching." International Journal of Computer Mathematics 66, no. 1-2 (1998): 21–38. http://dx.doi.org/10.1080/00207169808804622.

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Zhang, Chun Ying, Jing Feng Guo, and Xiao Chen. "Research on Random Walk Rough Matching Algorithm of Attribute Sub-Graph." Key Engineering Materials 474-476 (April 2011): 297–302. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.297.

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In the analysis of social network, the attribute values of an entity change constantly as time goes by and the corresponding attribute graph changes accordingly. However, the essence of the entity is invariable. The problem is how to discover essence from the change of mining frequent rough matching attribute sub-graph in an attribute graph in this paper. The problem of the attribute sub-graph rough matching is defined and described, then the random walk rough matching algorithm of attribute sub-graph is designed so that the problem of incomplete coincide attribute sub-graph rough matching would be solved. Attribute sub-graph is the expansion of the traditional sub-graph; rough matching problem is the extension of traditional sub-graph matching problem. With the help of the random walk rough matching algorithm of attribute sub-graph, more potential frequent attribute sub-graphs can be discovered, and more valuable information mined.
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Long, Susan B., and Richard H. Evans. "Matching Attribute set and Attitude Model." Psychological Reports 60, no. 3_part_2 (1987): 1087–96. http://dx.doi.org/10.1177/0033294187060003-214.1.

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The attribute set/attitude model relationship recently proposed by Myers and Shocker was examined using correlational and (LISREL) causal analysis. Compared against more traditional single-attitude model approaches (Ahtola, Adequacy-Importance, and Fishbein), Myers and Shocker's mixed model appears promising. It matched the attitude model which best predicted behavioral intentions for two out of three product attribute sets, and along with the Fishbein model, produced a satisfactory fit with the hypothesized causal structure. However, when the alternative attitude models were compared using a multiple indicator approach, results suggest these models do not appear to be directly measuring the same underlying attribute sets.
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LONG, SUSAN B., and RICHARD H. EVANS. "MATCHING ATTRIBUTE SET AND ATTITUDE MODEL." Psychological Reports 60, no. 3c (1987): 1087–96. http://dx.doi.org/10.2466/pr0.1987.60.3c.1087.

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Cortés, Xavier, and Francesc Serratosa. "Learning Graph Matching Substitution Weights Based on the Ground Truth Node Correspondence." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 02 (2016): 1650005. http://dx.doi.org/10.1142/s0218001416500051.

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In pattern recognition, it is usual to compare structured objects through attributed graphs in which nodes represent local parts and edges relations between them. Thus, each characteristic in the local parts is represented by different attributes on the nodes or edges. In this framework, the comparison between structured objects is performed through a distance between attributed graphs. If we want to correctly tune the distance and node correspondence between graphs, we need to add some weights on the node and edge attributes to gauge the importance of each local characteristic while defining the distance measure between graphs. In this paper, we present a method to learn the weights of each node and edge attribute such that the distance between the ground truth correspondence between graphs and the automatically obtained correspondence is minimized.
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Zhao, Huimin. "Matching Attributes across Overlapping Heterogeneous Data Sources Using Mutual Information." Journal of Database Management 21, no. 4 (2010): 91–110. http://dx.doi.org/10.4018/jdm.2010100105.

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Identifying matching attributes across heterogeneous data sources is a critical and time-consuming step in integrating the data sources. In this paper, the author proposes a method for matching the most frequently encountered types of attributes across overlapping heterogeneous data sources. The author uses mutual information as a unified measure of dependence on various types of attributes. An example is used to demonstrate the utility of the proposed method, which is useful in developing practical attribute matching tools.
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Deng, Luo, Liu, and Wang. "Point of Interest Matching between Different Geospatial Datasets." ISPRS International Journal of Geo-Information 8, no. 10 (2019): 435. http://dx.doi.org/10.3390/ijgi8100435.

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Point of interest (POI) matching finds POI pairs that refer to the same real-world entity, which is the core issue in geospatial data integration. To address the low accuracy of geospatial entity matching using a single feature attribute, this study proposes a method that combines the D–S (Dempster–Shafer) evidence theory and a multiattribute matching strategy. During POI data preprocessing, this method calculates the spatial similarity, name similarity, address similarity, and category similarity between pairs from different geospatial datasets, using the multiattribute matching strategy. The similarity calculation results of these four types of feature attributes were used as independent evidence to construct the basic probability distribution. A multiattribute model was separately constructed using the improved combination rule of the D–S evidence theory, and a series of decision thresholds were set to give the final entity matching results. We tested our method with a dataset containing Baidu POIs and Gaode POIs from Beijing. The results showed the following—(1) the multiattribute matching model based on improved DS evidence theory had good performance in terms of precision, recall, and F1 for entity-matching from different datasets; (2) among all models, the model combining the spatial, name, and category (SNC) attributes obtained the best performance in the POI entity matching process; and (3) the method could effectively address the low precision of entity matching using a single feature attribute.
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Yun, Jing, ZhiWei Xu, and GuangLai Gao. "Gated Object-Attribute Matching Network for Detailed Image Caption." Mathematical Problems in Engineering 2020 (January 13, 2020): 1–11. http://dx.doi.org/10.1155/2020/9562587.

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Image caption enables computers to generate a text description of images automatically. However, the generated description is not good enough recently. Computers can describe what objects are in the image but cannot give more details about these objects. In this study, we present a novel image caption approach to give more details when describing objects. In detail, a visual attention-based LSTM is used to find the objects, as well as a semantic attention-based LSTM is used for giving semantic attributes. At last, a gated object-attribute matching network is used to match the objects to their semantic attributes. The experiments on the public datasets of Flickr30k and MSCOCO demonstrate that the proposed approach improved the quality of the image caption, compared with the most advanced methods at present.
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Yang, Xin, Xuemeng Song, Fuli Feng, Haokun Wen, Ling-Yu Duan, and Liqiang Nie. "Attribute-wise Explainable Fashion Compatibility Modeling." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 1 (2021): 1–21. http://dx.doi.org/10.1145/3425636.

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With the boom of the fashion market and people’s daily needs for beauty, clothing matching has gained increased research attention. In a sense, tackling this problem lies in modeling the human notions of the compatibility between fashion items, i.e., Fashion Compatibility Modeling (FCM), which plays an important role in a wide bunch of commercial applications, including clothing recommendation and dressing assistant. Recent advances in multimedia processing have shown remarkable effectiveness in accurate compatibility evaluation. However, these studies work like a black box and cannot provide appropriate explanations, which are indeed of importance for gaining users’ trust and improving their experience. In fact, fashion experts usually explain the compatibility evaluation through the matching patterns between fashion attributes (e.g., a silk tank top cannot go with a knit dress). Inspired by this, we devise an attribute-wise explainable FCM solution, named ExFCM , which can simultaneously generate the item-level compatibility evaluation for input fashion items and the attribute-level explanations for the evaluation result. In particular, ExFCM consists of two key components: attribute-wise representation learning and attribute interaction modeling. The former works on learning the region-aware attribute representation for each item with the threshold global average pooling. Besides, the latter is responsible for compiling the attribute-level matching signals into the overall compatibility evaluation adaptively with the attentive interaction mechanism. Note that ExFCM is trained without any attribute-level compatibility annotations, which facilitates its practical applications. Extensive experiments on two real-world datasets validate that ExFCM can generate more accurate compatibility evaluations than the existing methods, together with reasonable explanations.
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Dissertations / Theses on the topic "Attribute matching"

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Riaz, Muhammad Atif, and Sameer Munir. "An Instance based Approach to Find the Types of Correspondence between the Attributes of Heterogeneous Datasets." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1938.

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Context: Determining attribute correspondence is the most important, time consuming and knowledge intensive part during databases integration. It is also used in other data manipulation applications such as data warehousing, data design, semantic web and e-commerce. Objectives: In this thesis the aim is to investigate how to find the types of correspondence between the attributes of heterogeneous datasets when schema design information of the data sets is unknown. Methods: A literature review was conducted to extract the knowledge related to the approaches that are used to find the correspondence between the attributes of heterogeneous datasets. Extracted knowledge from the literature review is used in developing an instance based approach for finding types of correspondence between the attributes of heterogeneous datasets when schema design information is unknown. To validate the proposed approach an experiment was conducted in the real environment using the data provided by the Telecom Industry (Ericsson) Karlskrona. Evaluation of the results was carried using the well known and mostly used measures from information retrieval field precision, recall and F-measure. Results: To find the types of correspondence between the attributes of heterogeneous datasets, good results depend on the ability of the algorithm to avoid the unmatched pairs of rows during the Row Similarity Phase. An evaluation of proposed approach is performed via experiments. We found 96.7% (average of three experiments) F-measure. Conclusions: The analysis showed that the proposed approach was feasible to be used and it provided users a mean to find the corresponding attributes and the types of correspondence between corresponding attributes, based on the information extracted from the similar pairs of rows from the heterogeneous data sets where their similarity based on the same common primary keys values.
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SOLBIATI, MONICA. "SYNCOPE RISK STRATIFICATION IN THE EMERGENCY DEPARTMENT: COMPARISON OF DIFFERENT PREDICTION MODELS AND THE POSSIBLE ROLE OF ATTRIBUTE MATCHING." Doctoral thesis, Università degli Studi di Milano, 2018. http://hdl.handle.net/2434/555557.

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Gli strumenti fino ad ora disponibili hanno fallito nel tentativo di predire gli eventi avversi dei pazienti con sincope in pronto soccorso. Per valutare i possibili punti di forza e di debolezza e confrontare i diversi metodi statistici usati per la derivazione di score e scale di rischio, abbiamo deciso di derivare dei modelli basati su regressione logistica multivariata e reti neurali artificiali (ANN) a partire da un database retrospettivo e di validarli in un nuovo dataset di 354 pazienti. L’area sotto la curva ROC di regressione multivariata e ANN è risultata rispettivamente di 0.726 e 0.694 nella coorte di validazione. Vista la bassa accuratezza predittiva dei modelli analizzati, abbiamo provato a identificare metodi alternativi per predire il rischio di eventi avversi dei pazienti con sincope. Abbiamo ipotizzato che si potesse stimare una probabilità pre-test accurata appaiando ogni singolo paziente ad un gruppo di pazienti con le stesse caratteristiche cliniche, e valutando la proporzione che aveva sviluppato l’outcome di interesse (attribute matching). In teoria, il funzionamento ideale di tale sistema consentirebbe di confrontare un profilo clinico tanto più dettagliato e di avere stime di rischio molto precise quanto più il database di riferimento è ampio. Pertanto, questo strumento non è ancora utilizzabile nella pratica clinica, ma sembra un metodo promettente. Studi futuri dovrebbero costruire database prospettici che arruolino un gran numero di pazienti per valutare se l’attibute matching possa aggiungere informazioni agli strumenti predittivi tradizionali e alla stima del rischio da parte di medici esperti. Inoltre, la possibilità di introdurre variabili nuove e sempre più complesse e di poter predire nel dettaglio diversi tipi di outcome, potrebbe creare un profilo clinico più specifico e potenzialmente sempre più accurato.<br>Clinical prediction tools have failed in the correct risk stratification of syncope patients in the emergency department. To assess the possible strengths and weaknesses and to compare the different statistical methodologies to derive prediction tools, we decided to derive both a multivariate logistic regression model and an artificial neural network (ANN) on a large retrospective database and to prospectively validate them in a new dataset of 354 patients. The area under the ROC curve of multivariate regression and ANN in the validation cohort were 0.726 and 0.694, respectively. Since the poor predictive accuracy of the analyzed models, we tried to identify alternative methods. We hypothesized that accurate pretest probability assessments can be obtained by matching an individual patient to a group of previously studied patients who shared the same clinical characteristic and determining the percentage of these previously studied patients who had the outcome of interest. In theory, the ideal attribute matching system would allow a very detailed clinical profile to be matched against a very large reference database to provide accurate risk estimates. Therefore, we do not offer a clinically useful prediction tool at this stage, but this method seems promising. Future studies should focus on building large prospective datasets to assess if attribute matching adds any value to both the traditional clinical decision tools and the implicit estimate of probability from clinicians. Moreover, the introduction of new and more complex input attributes and the possibility to provide as output a detailed risk assessment will create a more specific and potentially more accurate clinical profile.
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Eschmann, Marcel. "Study of bitwise operations on non-scarce attribute based data structures in PostgreSQL." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232075.

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This report investigates the viability of bitwise operations on non-scarce attribute based data structures in PostgreSQL. For applications where computation can’t be avoided, it most probably can be optimized. In an attempt of bringing the computation closer to hardware and the underlying data, operations directly on the database system are explored, taking inspiration from the research field of comparative genomics. With the case-study of an online job platform in mind, where possible matchings between candidate and job descriptions are calculated by a matching engine, a binary encoding is proposed and the computational components identified. The ultimate goal was to evaluate the scalability of the bitwise strategy with respect to the current matching engine. Through an iterative approach, this report conducts quantitative experiments on the presented components. Most notably, an implementation of the population count in the form of a C extension was introduced. It was found, that even for large sequence lengths, the operation is highly efficient. Among the chosen algorithms Lookup Table, Hamming Weight, Intrinsic functions and Unrolled Inline Assembly, the 64 bit intrinsic function displayed the best performance. Benchmarks determined, that the proposed bitwise approach is an excellent strategy for the outlined use-case. Despite the tradeoff of additional complexity in the encoding and decoding of data, the speedup is so significant, that the targeted user base of 100000 can easily be managed and allows for the deprecation of caching mechanisms.<br>Denna rapport undersöker gångbarheten för bitwise-operationer på icke-knappa attributbaserade datastrukturer i PostgreSQL. För applikationer där komputationen inte kan undvikas, kan den högst troligen optimeras. I ett försök att föra beräkningen närmare hårdvaran och den underliggande datan, undersöks operationer direkt på databasen med inspiration från forskningsområdet inom komparativ genomik. Med fallstudien av en online rekryteringsplattform i åtanke, där möjliga matchningar mellan kandidatoch arbetsbeskrivningar beräknas av en matchningsmotor, föreslås en binär kodning och komputationskomponenterna identifieras. Det slutgiltiga målet var att utvärdera skalbarheten hos bitwise-strategin med avseende till den aktuella matchningsmotorn. Genom ett iterativ tillvägagångssätt utför denna rapport kvantitativa experiment på de presenterade komponenterna. Framför allt infördes en implementering av population count i form av ett C-tillägg i databasen. Det visade sig att även för större sekvenslängder är operationen mycket effektiv. Bland de utvalda algoritmerna Lookup Table, Hamming Weight, Intrinsic-funktioner och Unrolled Inline Assembly, visade 64-bitars Intrisicfunktionen den bästa prestandan. Experimenten fastställde att det föreslagna bitwisetillvägagångssättet är en utmärkt strategi för den valda fallstudien. Trots avvägningen med ytterligare komplexitet vid kodning och avkodning av data är hastigheten så signifikant att ett användarantal på 100000 enkelt kan hanteras och möjliggör uteslutning av cache-mekanismer.
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Watanabe, Toyohide, Yuusuke Uehara, Yuuji Yoshida, and Teruo Fukumura. "A semantic data model for intellectual database access." IEEE, 1990. http://hdl.handle.net/2237/6923.

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Workneh, Tewabe Chekole <1986&gt. "A Continuous - Time Quantum Walk for Attributed Graphs Matching." Master's Degree Thesis, Università Ca' Foscari Venezia, 2013. http://hdl.handle.net/10579/3468.

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ABSTRACT Various Aspects Of the Theory of Quantum Walks on Graphs are Surveyed. In particular, Quantum network routing ,Kempe[2002],Quantum Walk Search Algorithm, Shenvi,Kempe and Whaley[2002] , Element distinctness ,Ambainis, [2004]. Connections with the eigenvalues of Graphs and the use of these connections in the study of Quantum walks is described. Dierent researchers had contribution and put their benchmark idea Pertaining with this concept. I also try to investigate recent Application of Quantum walks, In particular the problem pertained with Graph matching i.e Matching nodes(vertices) of the Graphs. In this paper,I consider how Continuous-time quantum walk (CTQW) can be applied to Graph-matching problems. The matching problem is abstracted using weighted(attribiuted) Graphs that connects vertices of one Graph to other and Try to compute the distance b/n two Graphs Node's Beside that nding the Cost related to Matching. Finally classing Those Nodes upon the values they had
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MANZO, MARIO. "ATTRIBUTED RELATIONAL SIFT-BASED REGIONS GRAPH (ARSRG):DESCRIPTION, MATCHING AND APPLICATIONS." Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233320.

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Finding correspondences between images is a crucial activity in many overlapping fields of research, such as Image Retrieval and Pattern Recognition. Many existing techniques address this problem using local invariant image features, instead of color, shape and texture, that to some degree loose the large scale structure of the image. In this thesis, in order to account for spatial relations among the local invariant features and to improve the image representation, first a graph data structure is introduced, where local features are represented by nodes and spatial relations by edges; second an algorithm able to find matches between local invariant features, organized in graph structures, is built; third a mapping procedure from graph to vector space is proposed, in order to speed up the classification process. Effectiveness of the proposed framework is demonstrated through applications in image-based localization and art painting. The literature shows many approximate algorithms to solve these problems, so a comparison with the state of the art is performed in each step of the process. By using both local and spatial information, the proposed framework outperforms its competitors for the image correspondence problems.
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Kanchinadam, Krishna M. "DataMapX a tool for cross-mapping entities and attributes between bioinformatics databases /." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3135.

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Thesis (M.S.)--George Mason University, 2008.<br>Vita: p. 29. Thesis director: Jennifer Weller. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Bioinformatics. Title from PDF t.p. (viewed July 7, 2008). Includes bibliographical references (p. 28). Also issued in print.
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Sands, Obed Scott. "Transitive, anti-symmetric relational attributes in structural description matching with applications to radar target identification /." The Ohio State University, 1990. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487683401443243.

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Dungan, Kerry Edward. "Feature-based Vehicle Classification in Wide-angle Synthetic Aperture Radar." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1274402314.

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Haugeard, Jean-Emmanuel. "Extraction et reconnaissance de primitives dans les façades de Paris à l'aide d'appariement de graphes." Thesis, Cergy-Pontoise, 2010. http://www.theses.fr/2010CERG0497.

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Cette dernière décennie, la modélisation des villes 3D est devenue l'un des enjeux de la recherche multimédia et un axe important en reconnaissance d'objets. Dans cette thèse nous nous sommes intéressés à localiser différentes primitives, plus particulièrement les fenêtres, dans les façades de Paris. Dans un premier temps, nous présentons une analyse des façades et des différentes propriétés des fenêtres. Nous en déduisons et proposons ensuite un algorithme capable d'extraire automatiquement des hypothèses de fenêtres. Dans une deuxième partie, nous abordons l'extraction et la reconnaissance des primitives à l'aide d'appariement de graphes de contours. En effet une image de contours est lisible par l'oeil humain qui effectue un groupement perceptuel et distingue les entités présentes dans la scène. C'est ce mécanisme que nous avons cherché à reproduire. L'image est représentée sous la forme d'un graphe d'adjacence de segments de contours, valué par des informations d'orientation et de proximité des segments de contours. Pour la mise en correspondance inexacte des graphes, nous proposons plusieurs variantes d'une nouvelle similarité basée sur des ensembles de chemins tracés sur les graphes, capables d'effectuer les groupements des contours et robustes aux changements d'échelle. La similarité entre chemins prend en compte la similarité des ensembles de segments de contours et la similarité des régions définies par ces chemins. La sélection des images d'une base contenant un objet particulier s'effectue à l'aide d'un classifieur SVM ou kppv. La localisation des objets dans l'image utilise un système de vote à partir des chemins sélectionnés par l'algorithme d'appariement<br>This last decade, modeling of 3D city became one of the challenges of multimedia search and an important focus in object recognition. In this thesis we are interested to locate various primitive, especially the windows, in the facades of Paris. At first, we present an analysis of the facades and windows properties. Then we propose an algorithm able to extract automatically window candidates. In a second part, we discuss about extraction and recognition primitives using graph matching of contours. Indeed an image of contours is readable by the human eye, which uses perceptual grouping and makes distinction between entities present in the scene. It is this mechanism that we have tried to replicate. The image is represented as a graph of adjacency of segments of contours, valued by information orientation and proximity to edge segments. For the inexact matching of graphs, we propose several variants of a new similarity based on sets of paths, able to group several contours and robust to scale changes. The similarity between paths takes into account the similarity of sets of segments of contours and the similarity of the regions defined by these paths. The selection of images from a database containing a particular object is done using a KNN or SVM classifier
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Books on the topic "Attribute matching"

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Shugart, Matthew S., Matthew E. Bergman, Cory L. Struthers, Ellis S. Krauss, and Robert J. Pekkanen. Party Personnel Strategies. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192897053.001.0001.

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The book develops the notion of “party personnel strategies”, which are the ways in which political parties assign their elected members—their “personnel”—to serve collective organizational goals. Key party goals are to advance a policy brand and maximize seats in the legislature. We offer a theory of how assignments of members to specialized legislative committees contribute to these goals. Individual members vary in their personal attributes, such as prior occupation, gender, and local experience. Parties seek to harness the attributes of their members by assigning them to committees where members’ expertise is relevant; doing so may enhance the party’s policy brand. Under some electoral systems, parties may need to trade off the harnessing of expertise against the pursuit of seats, instead matching legislators according to electoral situation (e.g., marginality of seat) or characteristics of their constituency (e.g., population density). The book offers analysis of the extent to which parties trade of these goals by matching the attributes of their personnel and their electoral needs to the functions of the available committee seats. The analysis is based on a dataset of around 6,000 legislators across thirty-eight elections in six established parliamentary democracies with diverse electoral systems.
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Huda, Ahmed Samei. The Medical Model in Mental Health. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198807254.001.0001.

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The medical model is a biopsychosocial model assessing a patient’s problems and matching them to the diagnostic construct using pattern recognition of clinical features. Diagnostic constructs allow for researching, communicating, teaching, and learning useful clinical information to influence clinical decision-making. They also have social and administrative functions such as access to benefits. They may also help explain why problems occur. Diagnostic constructs are used to describe diseases/syndromes and also other types of conditions such as spectrums of conditions. Treatments in medicine and psychiatry have several treatment objectives including cure or reducing distress and a variety of mechanisms of action apart from reversing disease/cure. Causation of conditions in medicine and psychiatry are often complex. The medical model allows doctors to assess and offer effective treatments to large numbers of patients and provide emergency cover. Diagnostic constructs in psychiatry and general medicine overlap for attributes such as clinical utility (e.g. predicting likely outcomes) and validity (e.g. lack of boundaries between different diagnostic constructs) and importance of social factors. There is an overlap in effectiveness between psychiatric and general medicine treatments and many general medicine medications do not reverse disease processes. Different mental health classifications have particular strengths and weaknesses for clinical, research, and social functions. Mental health research into understanding causes and mechanisms may need other classifications than diagnosis. As doctors in all specialties encounter mental health problems, there will always be psychiatric diagnostic constructs compatible with their training. Mental health research and service provision will always need to address psychosocial issues.
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Wright, A. G. The Photomultiplier Handbook. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199565092.001.0001.

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This handbook is aimed at helping users of PMTs who are faced with the challenge of designing sensitive light detectors for scientific and industrial purposes. The raison d’être for photomultipliers (PMTs) stems from four intrinsic attributes: large detection area, high, and noiseless gain, and wide bandwidth. Detection involves a conversion process from photons to photoelectrons at the photocathode. Photoelectrons are subsequently collected and increased in number by the action of an incorporated electron multiplier. Photon detection, charge multiplication, and many PMT applications are statistical in nature. For this reason appropriate statistical treatments are provided and derived from first principles. PMTs are characterized by a range of photocathodes offering detection over UV to infra-red wavelengths, the sensitivities of which can be calibrated by National Laboratories. The optical interface between light sources and PMTs, particularly for diffuse or uncollimated light, is sparsely covered in the scientific literature. The theory of light guides, Winston cones, and other light concentrators points to means for optimizing light collection subject to the constraints of Liouville’s theorem (étandue). Certain PMTs can detect single photons but are restricted by the limitations of unwanted background ranging in magnitude from a fraction of a photoelectron equivalent to hundreds of photoelectrons. These sources, together with their correlated nature, are examined in detail. Photomultiplier biasing requires a voltage divider comprising a series of resistors or active components, such as FETs. Correct biasing provides the key to linear operation and so considerable attention is given to the treatment of this topic. Electronic circuits and modules that perform the functions of charge to voltage conversion, pulse shaping, and impedance matching are analysed in detail.
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Book chapters on the topic "Attribute matching"

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Gal, Avigdor. "Enhancing the Capabilities of Attribute Correspondences." In Schema Matching and Mapping. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16518-4_3.

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Fan, Fengfeng, Zhanhuai Li, and Qun Chen. "Attribute Value Matching with Limited Budget." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02698-1_13.

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Fan, Fengfeng, and Zhanhuai Li. "Attribute Value Matching by Maximizing Benefit." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01391-2_5.

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Han, Yue, Weihong Han, Shudong Li, and Zhen Wang. "Attribute Value Extraction Based on Rule Matching." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8101-4_10.

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Harada, Lilian. "Pattern Matching over Multi-attribute Data Streams." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45735-6_17.

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Zhang, Jiachen, Giovanni Lo Bianco, and J. Christopher Beck. "Model-Based Approaches to Multi-attribute Diverse Matching." In Integration of Constraint Programming, Artificial Intelligence, and Operations Research. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08011-1_28.

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Yang, Ran, Meng Jian, Ge Shi, Lifang Wu, and Ye Xiang. "Attribute-Level Interest Matching Network for Personalized Recommendation." In Pattern Recognition and Computer Vision. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88007-1_40.

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Batina, Lejla, Jens Hermans, Jaap-Henk Hoepman, and Anna Krasnova. "High-Speed Dating Privacy-Preserving Attribute Matching for RFID." In Radio Frequency Identification: Security and Privacy Issues. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13066-8_2.

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Ou, Yangming, and Christos Davatzikos. "DRAMMS: Deformable Registration via Attribute Matching and Mutual-Saliency Weighting." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02498-6_5.

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Liu, Haishan, and Dejing Dou. "Breaking the Deadlock: Simultaneously Discovering Attribute Matching and Cluster Matching with Multi-Objective Simulated Annealing." In On the Move to Meaningful Internet Systems: OTM 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25106-1_21.

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Conference papers on the topic "Attribute matching"

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Kim, Seungryong, Dongbo Min, Somi Jeong, Sunok Kim, Sangryul Jeon, and Kwanghoon Sohn. "Semantic Attribute Matching Networks." In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.01262.

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Fu, Cheng, Xianpei Han, Jiaming He, and Le Sun. "Hierarchical Matching Network for Heterogeneous Entity Resolution." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/507.

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Entity resolution (ER) aims to identify data records referring to the same real-world entity. Most existing ER approaches rely on the assumption that the entity records to be resolved are homogeneous, i.e., their attributes are aligned. Unfortunately, entities in real-world datasets are often heterogeneous, usually coming from different sources and being represented using different attributes. Furthermore, the entities’ attribute values may be redundant, noisy, missing, misplaced, or misspelled—we refer to it as the dirty data problem. To resolve the above problems, this paper proposes an end-to-end hierarchical matching network (HierMatcher) for entity resolution, which can jointly match entities in three levels—token, attribute, and entity. At the token level, a cross-attribute token alignment and comparison layer is designed to adaptively compare heterogeneous entities. At the attribute level, an attribute-aware attention mechanism is proposed to denoise dirty attribute values. Finally, the entity level matching layer effectively aggregates all matching evidence for the final ER decisions. Experimental results show that our method significantly outperforms previous ER methods on homogeneous, heterogeneous and dirty datasets.
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Fan, Fengfeng, Zhanhuai Li, and Yanyan Wang. "Cohesion based attribute value matching." In 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2017. http://dx.doi.org/10.1109/cisp-bmei.2017.8302312.

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Ahmadi, Saba, Faez Ahmed, John P. Dickerson, Mark Fuge, and Samir Khuller. "An Algorithm for Multi-Attribute Diverse Matching." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/1.

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Bipartite b-matching, where agents on one side of a market are matched to one or more agents or items on the other, is a classical model that is used in myriad application areas such as healthcare, advertising, education, and general resource allocation. Traditionally, the primary goal of such models is to maximize a linear function of the constituent matches (e.g., linear social welfare maximization) subject to some constraints. Recent work has studied a new goal of balancing whole-match diversity and economic efficiency, where the objective is instead a monotone submodular function over the matching. Basic versions of this problem are solvable in polynomial time. In this work, we prove that the problem of simultaneously maximizing diversity along several features (e.g., country of citizenship, gender, skills) is NP-hard. To address this problem, we develop the first combinatorial algorithm that constructs provably-optimal diverse b-matchings in pseudo-polynomial time. We also provide a Mixed-Integer Quadratic formulation for the same problem and show that our method guarantees optimal solutions and takes less computation time for a reviewer assignment application. The source code is made available at https://github.com/faezahmed/diverse_matching.
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Yin, Zhou, Wei-Shi Zheng, Ancong Wu, et al. "Adversarial Attribute-Image Person Re-identification." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/153.

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While attributes have been widely used for person re-identification (Re-ID) which aims at matching the same person images across disjoint camera views, they are used either as extra features or for performing multi-task learning to assist the image-image matching task. However, how to find a set of person images according to a given attribute description, which is very practical in many surveillance applications, remains a rarely investigated cross-modality matching problem in person Re-ID. In this work, we present this challenge and leverage adversarial learning to formulate the attribute-image cross-modality person Re-ID model. By imposing a semantic consistency constraint across modalities as a regularization, the adversarial learning enables to generate image-analogous concepts of query attributes for matching the corresponding images at both global level and semantic ID level. We conducted extensive experiments on three attribute datasets and demonstrated that the regularized adversarial modelling is so far the most effective method for the attribute-image cross-modality person Re-ID problem.
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Gardezi, Jaffer, Leopoldo Bertossi, and Iluju Kiringa. "Matching dependencies with arbitrary attribute values." In the 4th International Workshop. ACM Press, 2011. http://dx.doi.org/10.1145/1966357.1966362.

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Peng, Yu, Raymond Chi-Wing Wong, Liangliang Ye, and Philip S. Yu. "Attribute-Based Subsequence Matching and Mining." In 2012 IEEE International Conference on Data Engineering (ICDE 2012). IEEE, 2012. http://dx.doi.org/10.1109/icde.2012.81.

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Wang, Ning, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, and Qinghua Zheng. "Graph Few-shot Learning with Attribute Matching." In CIKM '20: The 29th ACM International Conference on Information and Knowledge Management. ACM, 2020. http://dx.doi.org/10.1145/3340531.3411923.

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Huang, Xuri, Laurence R. Bentley, and Claude Laflamme. "Seismic history matching guided by attribute zonation." In SEG Technical Program Expanded Abstracts 2001. Society of Exploration Geophysicists, 2001. http://dx.doi.org/10.1190/1.1816410.

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Papathomas, Thomas V., and Andrei Gorea. "Class of stimuli for studying correspondence in apparent motion." In OSA Annual Meeting. Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.fd4.

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Correspondence matching is the process by which the visual system matches the attributes of objects (luminance, color, shape, contrast, etc.) at different places and at different times to determine the path of the objects in apparent (stroboscopic) motion. We present a class of stimulus which allows the existence of simultaneous motion paths carried by a multiplicity of attributes. Each attribute can be matched independently of the others to elicit unambiguous (unidirectional) or ambiguous (multidirectional) motion perception. When two or more attributes are matched, we can either match them along the same direction (concurrent matching) or along different ones (competitive matching). This flexibility in manipulating the stimuli makes it possible to (a) isolate specific motion mechanisms in the absence of stimulation of any other mechanisms, (b) assess the summation index for motion strength when two or more attributes are matched concurrently, and (c) directly assess the relative strength of pairs of attributes by using competitive matchings to determine which of them prevails in determining the perceived direction of motion. These stimuli have been employed in psychophysical experiments to assess the relative strength of several attributes (color, orientation, luminance, spatial frequency, binocular disparity, and polarity) in eliciting motion.
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Reports on the topic "Attribute matching"

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Elacqua, Gregory, and Leonardo Rosa. Teacher transfers and the disruption of Teacher Staffing in the City of Sao Paulo. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004737.

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This paper analyzes preferences for certain school attributes among in-service teachers. We explore a centralized matching process in the city of Sao Paulo that teachers must use when transferring schools. Because teachers have to list and rank their preferences for schools, we can estimate the desirability of school attributes using a rank-ordered logit model. We show that the schools distance from the teachers home, school average test scores, and teacher composition play a central role in teacher preferences. Furthermore, we show that preferences vary according to teacher characteristics, such as gender, race, age, and academic subject.
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