Lucene in Action (In Action series)
Lucene in Action (In Action series)
Why inverse document frequency?
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Mining search engine query logs for query recommendation
Proceedings of the 15th international conference on World Wide Web
Query suggestion based on user landing pages
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
From "Dango" to "Japanese Cakes": Query Reformulation Models and Patterns
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
CONQUER: a system for efficient context-aware query suggestions
Proceedings of the 20th international conference companion on World wide web
Field-weighted XML retrieval based on BM25
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
Social annotations in web search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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A person is generally motivated by the thoughts of a set of people in his social network and he has different degree of interest in each of those people considering the common interest, trust, philosophy and several other factors between them. In this work, we model the social context of the person as the status messages generated by those socially associated people and propose a method to use his social context to improve the web search query expansion process for him. Our method extracts and ranks keywords from the status messages, which are relevant with the initial search query that is to be expanded. The selected keyword is then appended with the initial query to form socially expanded query. We show that useful search queries can be formed in terms of specialization and parallel movement, if we use the socially expanded query for further expansion using traditional expansion processes. Our method ensures privacy by keeping the social network data segregated from search engine vendors. Moreover, we provide directions for implementing this method without the intervention of search engine vendors. Nevertheless, the background search process is considered to be provided by search engine vendors in the form of Application Program Interface (API).