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» Classifying Document Titles Based on Information Inference
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SIGIR
2006
ACM
14 years 3 months ago
Bias and the limits of pooling
Modern retrieval test collections are built through a process called pooling in which only a sample of the entire document set is judged for each topic. The idea behind pooling is...
Chris Buckley, Darrin Dimmick, Ian Soboroff, Ellen...
AIRWEB
2009
Springer
14 years 4 months ago
Looking into the past to better classify web spam
Web spamming techniques aim to achieve undeserved rankings in search results. Research has been widely conducted on identifying such spam and neutralizing its influence. However,...
Na Dai, Brian D. Davison, Xiaoguang Qi
JCDL
2004
ACM
89views Education» more  JCDL 2004»
14 years 3 months ago
Machine learning for information architecture in a large governmental website
This paper describes ongoing research into the application of machine learning techniques for improving access to governmental information in complex digital libraries. Under the ...
Miles Efron, Jonathan L. Elsas, Gary Marchionini, ...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 10 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
SIGIR
2004
ACM
14 years 3 months ago
An effective approach to document retrieval via utilizing WordNet and recognizing phrases
Noun phrases in queries are identified and classified into four types: proper names, dictionary phrases, simple phrases and complex phrases. A document has a phrase if all content...
Shuang Liu, Fang Liu, Clement T. Yu, Weiyi Meng