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» Maximum Margin Ranking Algorithms for Information Retrieval
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SIGIR
2009
ACM
16 years 8 days ago
Portfolio theory of information retrieval
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are depen...
Jun Wang, Jianhan Zhu
ECML
2007
Springer
15 years 12 months ago
An Unsupervised Learning Algorithm for Rank Aggregation
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
Alexandre Klementiev, Dan Roth, Kevin Small
SEMWEB
2005
Springer
15 years 11 months ago
The Fuzzy Description Logic f-SHIN
Abstract. In the Semantic Web information would be retrieved, processed, combined, shared and reused in the maximum automatic way possible. Obviously, such procedures involve a hig...
Giorgos Stoilos, Giorgos B. Stamou, Vassilis Tzouv...
SIGIR
1998
ACM
15 years 10 months ago
The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries
Abstract This paper presents a method for combining query-relevance with information-novelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR...
Jaime G. Carbonell, Jade Goldstein
CIKM
2009
Springer
16 years 10 days ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang