Browsing by Subject "Query view"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Open Access Exploiting query views for static index pruning in web search engines(ACM, 2009-11) Altıngövde, İsmail Şengör; Özcan, Rıfat; Ulusoy, ÖzgürWe propose incorporating query views in a number of static pruning strategies, namely term-centric, document-centric and access-based approaches. These query-view based strategies considerably outperform their counterparts for both disjunctive and conjunctive query processing in Web search engines. Copyright 2009 ACM.Item Open Access Static index pruning in web search engines: combining term and document popularities with query views(Association for Computing Machinery, 2012) Altingovde, I. S.; Ozcan, R.; Ulusoy, O.Static index pruning techniques permanently remove a presumably redundant part of an inverted file, to reduce the file size and query processing time. These techniques differ in deciding which parts of an index can be removed safely; that is, without changing the top-ranked query results. As defined in the literature, the query view of a document is the set of query terms that access to this particular document, that is, retrieves this document among its top results. In this paper, we first propose using query views to improve the quality of the top results compared against the original results. We incorporate query views in a number of static pruning strategies, namely term-centric, document-centric, term popularity based and document access popularity based approaches, and show that the new strategies considerably outperform their counterparts especially for the higher levels of pruning and for both disjunctive and conjunctive query processing. Additionally,we combine the notions of term and document access popularity to form new pruning strategies, and further extend these strategies with the query views. The new strategies improve the result quality especially for the conjunctive query processing, which is the default and most common search mode of a search engine. © 2012 ACM.