Improving Recall in Web Information Retrieval via Genetic Programming
نویسندگان
چکیده
منابع مشابه
A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems
Relevance feedback techniques have demonstrated to be a powerful means to improve the results obtained when a user submits a query to an information retrieval system as the world wide web search engines. These kinds of techniques modify the user original query taking into account the relevance judgements provided by him on the retrieved documents, making it more similar to those he judged as re...
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For the current exponential growth of World Wide Web (WWW), there have been a lot of information gathering tools to help people cope with the volume of information on the WWW. However, these tools are insu cient to nd information attracting personal interest of a user with high precision and recall. In order to make information gathering re ect interests of a user, it is useful to equip a perso...
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Genetic programming is applied to an information retrieval system to improve Boolean query formulation via relevance feedback. Documents are viewed as vectors in term space. A Boolean query is a chromosome in the genetic programming sense. Through the mechanisms of genetic programming, the query is modified to improve precision and recall. Relevance feedback is incorporated via user-defined mea...
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تاریخ انتشار 1997