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» Maximum Margin Ranking Algorithms for Information Retrieval
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ICML
2007
IEEE
16 years 6 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
CIVR
2003
Springer
200views Image Analysis» more  CIVR 2003»
15 years 11 months ago
Multimedia Search with Pseudo-relevance Feedback
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in both text and image modalities. While the normalization and combination of evi...
Rong Yan, Alexander G. Hauptmann, Rong Jin
SIGIR
2006
ACM
15 years 12 months ago
Minimal test collections for retrieval evaluation
Accurate estimation of information retrieval evaluation metrics such as average precision require large sets of relevance judgments. Building sets large enough for evaluation of r...
Ben Carterette, James Allan, Ramesh K. Sitaraman
ECWEB
2010
Springer
219views ECommerce» more  ECWEB 2010»
15 years 7 months ago
Semantic Tag Cloud Generation via DBpedia
Abstract. Many current recommender systems exploit textual annotations (tags) provided by users to retrieve and suggest online contents. The text-based recommendation provided by t...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
CIKM
2010
Springer
15 years 3 months ago
Manifold ranking with sink points for update summarization
Update summarization aims to create a summary over a topic-related multi-document dataset based on the assumption that the user has already read a set of earlier documents of the ...
Pan Du, Jiafeng Guo, Jin Zhang, Xueqi Cheng