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INTERSPEECH
2010
13 years 13 days ago
Extractive summarization using a latent variable model
Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative ap...
Asli Çelikyilmaz, Dilek Hakkani-Tür
CIKM
2008
Springer
13 years 7 months ago
A latent variable model for query expansion using the hidden markov model
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...
Qiang Huang, Dawei Song
LREC
2008
153views Education» more  LREC 2008»
13 years 7 months ago
Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis
We present results from using Random Indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. We compare Latent Semantic Analysis, Random ...
Linus Sellberg, Arne Jönsson
CORR
2010
Springer
139views Education» more  CORR 2010»
13 years 5 months ago
The semantic mapping of words and co-words in contexts
Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of document...
Loet Leydesdorff, Kasper Welbers
AUSAI
2009
Springer
13 years 9 months ago
Adapting Spectral Co-clustering to Documents and Terms Using Latent Semantic Analysis
Abstract. Spectral co-clustering is a generic method of computing coclusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of ...
Laurence A. F. Park, Christopher Leckie, Kotagiri ...