The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Probabilistic Ranking Method of XML Fuzzy Query Results
Abstract
Fuzzy query processing for XML database systems is an important issue. Based on the fuzzy set theory, XML fuzzy query can be expressed exploiting fuzzy predicates. To deal with the ranking problem of XML fuzzy query results, this chapter proposes a novel ranking approach. Firstly, according to the workload of XML documents, this chapter speculates how much the users care about each attribute node and assign a corresponding weight to it. Then, a membership degree ranking method, which ranks the fuzzy query results according to corresponding membership degree, is presented. Furthermore, this chapter proposes the probabilistic ranking method, which improves the PIR method. The improved probabilistic ranking method considers the relevance between the nodes specified by fuzzy query and the nodes unspecified by fuzzy query. Finally, top-k ranking algorithm of XML fuzzy query results is presented. The efficiency and effectiveness of the approach are also demonstrated by experimental results.
Related Content
Hrithik Raj, Ritu Punhani, Ishika Punhani.
© 2023.
31 pages.
|
Divi Anand, Isha Kaushik, Jasmehar Singh Mann, Ritu Punhani, Ishika Punhani.
© 2023.
21 pages.
|
Jayanthi G., Purushothaman R..
© 2023.
10 pages.
|
Anshika Gupta, Shuchi Sirpal.
© 2023.
14 pages.
|
Reet Kaur Kohli, Seneha Santoshi, Sunishtha S. Yadav, Vandana Chauhan.
© 2023.
13 pages.
|
Poonam Tanwar.
© 2023.
14 pages.
|
Monika Mehta, Shivani Mishra, Santosh Kumar, Muskaan Bansal.
© 2023.
16 pages.
|
|
|