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SIGIR
2008
ACM
15 years 6 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
16 years 28 days ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei
COLING
2000
15 years 8 months ago
Word Order Acquisition from Corpora
In this paper we describe a method of acquiring word order fl'om corpora. Word order is defined as the order of modifiers, or the order of phrasal milts called 'bunsetsu...
Kiyotaka Uchimoto, Masaki Murata, Qing Ma, Satoshi...
ICMCS
2005
IEEE
169views Multimedia» more  ICMCS 2005»
16 years 6 days ago
Dynamic language model adaptation using latent topical information and automatic transcripts
This paper considers dynamic language model adaptation for Mandarin broadcast news recognition. Both contemporary newswire texts and in-domain automatic transcripts were exploited...
Berlin Chen
CORR
1998
Springer
99views Education» more  CORR 1998»
15 years 6 months ago
Models of Co-occurrence
A model of co-occurrence in bitext is a boolean predicate that indicates whether a given pair of word tokens co-occur in corresponding regions of the bitext space. Co-occurrence i...
I. Dan Melamed