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» Learning and Generalization with the Information Bottleneck
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SIGIR
2011
ACM
14 years 17 days ago
Active learning to maximize accuracy vs. effort in interactive information retrieval
We consider an interactive information retrieval task in which the user is interested in finding several to many relevant documents with minimal effort. Given an initial documen...
Aibo Tian, Matthew Lease
CIKM
2007
Springer
15 years 3 months ago
Generalizing from relevance feedback using named entity wildcards
Traditional adaptive filtering systems learn the user’s interests in a rather simple way – words from relevant documents are favored in the query model, while words from irre...
Abhimanyu Lad, Yiming Yang
WSDM
2012
ACM
214views Data Mining» more  WSDM 2012»
13 years 5 months ago
Selecting actions for resource-bounded information extraction using reinforcement learning
Given a database with missing or uncertain content, our goal is to correct and fill the database by extracting specific information from a large corpus such as the Web, and to d...
Pallika H. Kanani, Andrew K. McCallum
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
15 years 10 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
CICLING
2005
Springer
15 years 3 months ago
A Machine Learning Approach to Information Extraction
Information extraction is concerned with applying natural language processing to automatically extract the essential details from text documents. A great disadvantage of current ap...
Alberto Téllez-Valero, Manuel Montes-y-G&oa...