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COLING
2010
12 years 11 months ago
Text Summarization of Turkish Texts using Latent Semantic Analysis
Text summarization solves the problem of extracting important information from huge amount of text data. There are various methods in the literature that aim to find out well-form...
Makbule Ozsoy, Ilyas Cicekli, Ferda Nur Alpaslan
NLDB
2010
Springer
13 years 8 months ago
Semantic Content Access Using Domain-Independent NLP Ontologies
We present a lightweight, user-centred approach for document navigation and analysis that is based on an ontology of text mining results. This allows us to bring the result of exis...
René Witte, Ralf Krestel
HICSS
2010
IEEE
258views Biometrics» more  HICSS 2010»
13 years 5 months ago
An Empirical Comparison of Four Text Mining Methods
The amount of textual data that is available for researchers and businesses to analyze is increasing at a dramatic rate. This reality has led IS researchers to investigate various...
Sangno Lee, Jeff Baker, Jaeki Song, James C. Wethe...
CIVR
2005
Springer
118views Image Analysis» more  CIVR 2005»
13 years 10 months ago
On Image Retrieval Using Salient Regions with Vector-Spaces and Latent Semantics
Abstract. The vector-space retrieval model and Latent Semantic Indexing approaches to retrieval have been used heavily in the field of text information retrieval over the past yea...
Jonathon S. Hare, Paul H. Lewis
EMNLP
2010
13 years 2 months ago
Incorporating Content Structure into Text Analysis Applications
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
Christina Sauper, Aria Haghighi, Regina Barzilay