53 search results - page 5 / 11 » Learning to rank relevant and novel documents through user f... |
AAAI
2008
13 years 9 months ago
2008
Search engines present fix-length passages from documents ranked by relevance against the query. In this paper, we present and compare novel, language-model based methods for extr...
CORR
2006
Springer
13 years 6 months ago
2006
Springer
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
SIGIR
2012
ACM
11 years 9 months ago
2012
ACM
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
ICASSP
2007
IEEE
14 years 28 days ago
2007
IEEE
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
CIKM
2006
Springer
13 years 10 months ago
2006
Springer
This work addresses two common problems in search, frequently occurring with underspecified user queries: the top-ranked results for such queries may not contain documents relevan...