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Statistical Models for Text Segmentation

by Doug Beeferman, Adam Berger, John Lafferty - Machine Learning , 1999
"... . This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text. The mode ..."
Abstract - Cited by 268 (3 self) - Add to MetaCart
. This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text

Text Segmentation by Topic

by Jay Ponte And, Jay M. Ponte, W. Bruce Croft - In Proceedings of the First European Conference on Research and Advanced Technology for Digital Libraries , 1997
"... We investigate the problem of text segmentation by topic. ..."
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We investigate the problem of text segmentation by topic.

Text Segmentation by Topic

by Jay M. Ponte, W. Bruce Croft - In Proceedings of the First European Conference on Research and Advanced Technology for Digital Libraries , 1997
"... . We investigate the problem of text segmentation by topic. Applications for this task include topic tracking of broadcast speech data and topic identification in full-text databases. Researchers have tackled similar problems before but with different goals. This study focuses on data with relativel ..."
Abstract - Cited by 105 (2 self) - Add to MetaCart
. We investigate the problem of text segmentation by topic. Applications for this task include topic tracking of broadcast speech data and topic identification in full-text databases. Researchers have tackled similar problems before but with different goals. This study focuses on data

Latent Semantic Analysis for Text Segmentation

by Freddy Y. Y. Choi, Peter Wiemer-Hastings, Johanna Moore - In Proceedings of EMNLP , 2001
"... This paper describes a method for linear text segmentation that is more accurate or at least as accurate as state-of-the-art methods (Utiyama and Isahara, 2001 ..."
Abstract - Cited by 92 (1 self) - Add to MetaCart
This paper describes a method for linear text segmentation that is more accurate or at least as accurate as state-of-the-art methods (Utiyama and Isahara, 2001

Text Segmentation with Topic Models

by Martin Riedl, Chris Biemann
"... This article presents a general method to use information retrieved from the Latent Dirichlet Allocation (LDA) topic model for Text Segmentation: Using topic assignments instead of words in two well-known Text Segmentation algorithms, namely TextTiling and C99, leads to significant improvements. Fur ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
This article presents a general method to use information retrieved from the Latent Dirichlet Allocation (LDA) topic model for Text Segmentation: Using topic assignments instead of words in two well-known Text Segmentation algorithms, namely TextTiling and C99, leads to significant improvements

An iterative approach to text segmentation

by Fei Song, William M. Darling, Adnan Duric, Fred W. Kroon - In Proceedings of the 33rd European Conference on Advances in Information Retrieval, ECIR’11 , 2011
"... Abstract. We present divSeg, a novel method for text segmentation that iteratively splits a portion of text at its weakest point in terms of the connectivity strength between two adjacent parts. To search for the weakest point, we apply two different measures: one is based on language modeling of te ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
Abstract. We present divSeg, a novel method for text segmentation that iteratively splits a portion of text at its weakest point in terms of the connectivity strength between two adjacent parts. To search for the weakest point, we apply two different measures: one is based on language modeling

Text Segmentation from Images

by Punam Patel, Shamik Tiwari
"... Texts detection from image or complex colored document is a very challenging problem. Text in images and videos contain useful information. There is a significant need to extract and analyze the text in images on Web documents, for effective indexing, semantic analysis and searching. The extraction ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
of text information is very important because texts contain highlevel semantic information. In this paper, we proposed a hybrid approach of text segmentation using edge and texture feature information.This result can also be used for other image interpretation and analysis. 1.

Text Segmentation Based On Similarity Between Words

by Hideki Kozima , 1993
"... This paper proposes a new indicator of text structure, called the lexical cohesion profile (LCP), which locates segment boundaries in a text. A text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. LCP records mutual similarity of words in a seq ..."
Abstract - Cited by 128 (4 self) - Add to MetaCart
This paper proposes a new indicator of text structure, called the lexical cohesion profile (LCP), which locates segment boundaries in a text. A text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. LCP records mutual similarity of words in a

Advances in Domain Independent Linear Text Segmentation

by Freddy Y. Y. Choi , 2000
"... This paper describes a method for linear text seg- mc. ntation which is twice as accurate and over seven times as fast as the state-of-the-art (Reynar, 1998). Inter-sentence similarity is replaced by rank in the local context. Boundary locations are discovered by divisive clustering. ..."
Abstract - Cited by 182 (1 self) - Add to MetaCart
This paper describes a method for linear text seg- mc. ntation which is twice as accurate and over seven times as fast as the state-of-the-art (Reynar, 1998). Inter-sentence similarity is replaced by rank in the local context. Boundary locations are discovered by divisive clustering.

Statistical Models for Text Segmentation

by Doug Beeferman Adam, Adam Berger, John Lafferty - Machine Learning , 1999
"... . This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text. The mod ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
. This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text
Results 1 - 10 of 386,313