Inquirus, the NECI meta search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
WWW '03 Proceedings of the 12th international conference on World Wide Web
Improving Category Specific Web Search by Learning Query Modifications
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Mining models of human activities from the web
Proceedings of the 13th international conference on World Wide Web
Object-Blog System for Environment-Generated Content
IEEE Pervasive Computing
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Twitter API: Up and Running Learn How to Build Applications with the Twitter API
Twitter API: Up and Running Learn How to Build Applications with the Twitter API
Probabilistic models of ranking novel documents for faceted topic retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Classification-enhanced ranking
Proceedings of the 19th international conference on World wide web
Exploiting query reformulations for web search result diversification
Proceedings of the 19th international conference on World wide web
Intent-aware search result diversification
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Pseudo test collections for learning web search ranking functions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Effects of Terms Recognition Mistakes on Requests Processing for Interactive Information Retrieval
International Journal of Information Retrieval Research
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The method proposed in this paper searches for web pages using an event-related query consisting of a noun, verb, and genre term. It re-ranks web pages retrieved using a standard search engine on the basis of scores calculated from an expression consisting of weighted factors such as the frequency of query words. For the genres that are characterized by their genre terms, the method optimizes the weights of the expression. Furthermore, the method attempts to improve the scores provided of relevant pages by using machine learning techniques. In addition, some evaluations are provided to show the effectiveness of the method.