نتایج جستجو برای: relevance feedback
تعداد نتایج: 272550 فیلتر نتایج به سال:
We investigate the possibility of using Semantic Web data to improve hypertext Web search. In particular, we use relevance feedback to create a ‘virtuous cycle’ between data gathered from the Semantic Web of Linked Data and web-pages gathered from the hypertext Web. Previous approaches have generally considered the searching over the Semantic Web and hypertext Web to be entirely disparate, inde...
Within the structure of the TREC 2005 HARD track guidelines, we investigated the following hypotheses: H1: Query expansion using a “clarity”-based approach will increase effectiveness over baseline queries and baseline queries plus pseudo-relevance feedback; H2: Query expansion based on the Web will increase effectiveness over baseline queries and baseline queries plus pseudo-relevance feedback...
We investigate the possibility of using structured data to improve unstructured search. In particular, we use relevance feedback to create a ‘virtuous cycle’ between structured data gathered from the Semantic Web of Linked Data and unstructured gathered from the hypertext Web. Previous approaches have generally considered the searching over the Semantic Web and hypertext Web to be entirely disp...
Relevance feedback can effectively improve the performance of content-based multimedia retrieval systems. To be effective, a relevance feedback approach must be able to efficiently capture the user’s query concept from a very limited number of training samples. To address this issue, we propose a novel adaptive classification method using random forests, which is a machine learning algorithm wi...
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