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KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 11 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
IR
2010
13 years 7 months ago
LETOR: A benchmark collection for research on learning to rank for information retrieval
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
Tao Qin, Tie-Yan Liu, Jun Xu, Hang Li
CLEF
2007
Springer
14 years 3 months ago
Overview of QAST 2007
This paper describes QAST, a pilot track of CLEF 2007 aimed at evaluating the task of Question Answering in Speech Transcripts. The paper summarizes the evaluation framework, the ...
Jordi Turmo, Pere Comas, Christelle Ayache, Djamel...
KDD
2002
ACM
148views Data Mining» more  KDD 2002»
14 years 9 months ago
Discovering informative content blocks from Web documents
In this paper, we propose a new approach to discover informative contents from a set of tabular documents (or Web pages) of a Web site. Our system, InfoDiscoverer, first partition...
Shian-Hua Lin, Jan-Ming Ho
IADIS
2004
13 years 10 months ago
Relevance feedback using semantic association between indexing terms in large free text corpuses
Relevance feedback has been considered as a means of incorporating learning into information retrieval systems for quite sometime now. This paper discusses the research results of...
Shahzad Khan, Kenan Azam