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» Enhancing Relevance Models with Adaptive Passage Retrieval
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SIGIR
2009
ACM
14 years 5 months ago
Risky business: modeling and exploiting uncertainty in information retrieval
Most retrieval models estimate the relevance of each document to a query and rank the documents accordingly. However, such an approach ignores the uncertainty associated with the ...
Jianhan Zhu, Jun Wang, Ingemar J. Cox, Michael J. ...
ML
2000
ACM
150views Machine Learning» more  ML 2000»
13 years 10 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
KDD
1998
ACM
101views Data Mining» more  KDD 1998»
14 years 2 months ago
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Ernest P. Chan, Santiago Garcia, Salim Roukos
CIKM
2009
Springer
14 years 5 months ago
On domain similarity and effectiveness of adapting-to-rank
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng
ECIR
2004
Springer
13 years 11 months ago
A Simulated Study of Implicit Feedback Models
In this paper we report on a study of implicit feedback models for unobtrusively tracking the information needs of searchers. Such models use relevance information gathered from se...
Ryen W. White, Joemon M. Jose, C. J. van Rijsberge...