0000000000953505
AUTHOR
Ires Dias
Algebraic Properties to Optimize kNN Queries
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
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…