Enriching User Queries Using DBpedia Features and Relevance Feedback
نویسندگان
چکیده
منابع مشابه
RRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features
Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking algorithm using reinforcement learning. The proposed algorithm is called RRLUFF, in which the rank...
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It's now time to go back to the user We have detailed a lot of tools and techniques that allow for sophisticated matching criteria to be applied, however in doing so we have implicitly assumed that the user " knows " how to formulate her queries/preferences In some cases the user does not know at all what to look for. In this case, a " browsing " activity should be supported. We do not co...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2018
ISSN: 1877-0509
DOI: 10.1016/j.procs.2018.01.148