Towards an integrated framework for querying collection of heterogeneous data
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
A coherent measurement of web-search relevance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Extending information unit across media streams for improving retrieval effectiveness
Data & Knowledge Engineering
State-of-the-art review on relevance of genetic algorithm to internet web search
Applied Computational Intelligence and Soft Computing
Domain specific multistage query language for medical document repositories
Proceedings of the VLDB Endowment
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Given a user keyword query, current Web search engines return a list of individual web pages ranked by their "goodness" with respect to the query. Thus the basic unit for search and retrieval is an individual page, even though information on a topic is often spread across multiple pages. This degrades the quality of search results especially for long or uncorrelated (multi-topic) queries (in which individual keywords rarely occur together in the same document) where a single page is unlikely to satisfy the user's information need. We propose a technique that given a keyword query, on-the-fly generates new pages, called composed pages, which contain all query keywords. The composed pages are generated by extracting and stitching together relevant pieces from hyperlinked Web pages, and retaining links to the original Web pages. To rank the composed pages we consider both the hyperlink structure of the original pages, as well as the associations between the keywords within each page. Furthermore, we present and experimentally evaluate heuristic algorithms to efficiently generate the top composed pages. The quality of our method is compared to current approaches using user surveys. Finally, we also show how our techniques can be used to perform query-specific summarization of web pages.