Search results for "Similarity queries"
showing 4 items of 4 documents
Adding Knowledge Extracted by Association Rules into Similarity Queries
2010
International audience; In this paper, we propose new techniques to improve the quality of similarity queries over image databases performing association rule mining over textual descriptions and automatically extracted features of the image content. Based on the knowledge mined, each query posed is rewritten in order to better meet the user expectations. We propose an extension of SQL aimed at exploring mining processes over complex data, generating association rules that extract semantic information from the textual description superimposed to the extracted features, thereafter using them to rewrite the queries. As a result, the system obtains results closer to the user expectation than i…
Optimisation des requêtes de similarité dans les espaces métriques répondant aux besoins des usagers
2012
The complexity of data stored in large databases has increased at very fast paces. Hence, operations more elaborated than traditional queries are essential in order to extract all required information from the database. Therefore, the interest of the database community in similarity search has increased significantly. Two of the well-known types of similarity search are the Range (Rq) and the k-Nearest Neighbor (kNNq) queries, which, as any of the traditional ones, can be sped up by indexing structures of the Database Management System (DBMS). Another way of speeding up queries is to perform query optimization. In this process, metrics about data are collected and employed to adjust the par…
Algebraic Properties to Optimize kNN Queries
2011
International audience; New applications that are being required to employ Database Management Systems (DBMSs), such as storing and retrieving complex data (images, sound, temporal series, genetic data, etc.) and analytical data processing (data mining, social networks analysis, etc.), increasingly impose the need for new ways of expressing predicates. Among the new most studied predicates are the similarity-based ones, where the two commonest are the similarity range and the k-nearest neighbor predicates. The k-nearest neighbor predicate is surely the most interesting for several applications, including Content-Based Image Retrieval (CBIR) and Data Mining (DM) tasks, yet it is also the mos…
Identifying Algebraic Properties to Support Optimization of Unary Similarity Queries
2009
International audience; Abstract. Conventional operators for data retrieval are either based on exact matching or on total order relationship among elements. Neither ofthem is appropriate to manage complex data, such as multimedia data, time series and genetic sequences. In fact, the most meaningful way tocompare complex data is by similarity. However, the Relational Algebra, employed in the Relational Database Management Systems (RDBMS),cannot express similarity criteria. In order to address this issue, we provide here an extension of the Relational Algebra, aimed at representingsimilarity queries in algebraic expressions. This paper identies fundamental properties to allow the integration…