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WWW
2008
ACM
16 years 5 months ago
Learning to classify short and sparse text & web with hidden topics from large-scale data collections
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi
WSDM
2009
ACM
136views Data Mining» more  WSDM 2009»
15 years 11 months ago
Mining common topics from multiple asynchronous text streams
Text streams are becoming more and more ubiquitous, in the forms of news feeds, weblog archives and so on, which result in a large volume of data. An effective way to explore the...
Xiang Wang 0002, Kai Zhang, Xiaoming Jin, Dou Shen
FLAIRS
2007
15 years 6 months ago
Indexing Documents by Discourse and Semantic Contents from Automatic Annotations of Texts
The basic aim of the model proposed here is to automatically build semantic metatext structure for texts that would allow us to search and extract discourse and semantic informati...
Brahim Djioua, Jean-Pierre Desclés
COLING
1992
15 years 5 months ago
Learning Translation Templates From Bilingual Text
This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This ...
Hiroyuki Kaji, Yuuko Kida, Yasutsugu Morimoto
NAACL
1994
15 years 5 months ago
Principles of Template Design
The functionality of systems that extract information from texts can be specified quite simply: the input is a stream of texts and the output is some representation of the informa...
Jerry R. Hobbs, David J. Israel