0000000001151335
AUTHOR
Agma Traina
showing 3 related works from this author
International Journal of Business Intelligence and Data Mining - Special Issue on Beyond multimedia and XML streams querying and mining
2010
International audience; Over the last decade, information has become available and reachable anywhere and everywhere. As a result, we have seen an explosion of multimedia and XML streams captured from multitudes of sources monitoring just about every aspect of life. This has lead to the emergence of a new generation of ambient and context-aware applications. Mining and querying the resulting large datasets is possibly the only way to discover information and extract new knowledge in them. One of the challenges is bridging several disciplines, such as database systems, XML and information retrieval, artificial intelligence, and multimedia processing. Thus, it has become important to understa…
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…
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…