Enhancing web page classification through image-block importance analysis

We present a term weighting approach for improving web page classification, based on the assumption that the images of a web page are those elements which mainly attract the attention of the user. This assumption implies that the text contained in the visual block in which an image is located, calle...

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Vydané v:	Information processing & management Ročník 44; číslo 4; s. 1431 - 1447
Hlavní autori:	Fersini, E., Messina, E., Archetti, F.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier Ltd 01.07.2008 Elsevier Elsevier Science Ltd
Predmet:	Algorithms Classification Content analysis Document classification Exact sciences and technology Indexing. Classification. Abstracting Indexing. Classification. Abstracting. Syntheses Information and communication sciences Information and document structure and analysis Information processing and retrieval Information retrieval Information retrieval. Man machine relationship Information science. Documentation Internet Layout Research process. Evaluation Sciences and techniques of general use Studies Term weighting Vector space model Visual layout analysis Web pages Websites Weighting Vector space model Visual layout analysis Document classification Term weighting Image analysis Automatic classification Vector space Bayes method Web mining Information extraction Information retrieval system
ISSN:	0306-4573, 1873-5371
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Abstract	We present a term weighting approach for improving web page classification, based on the assumption that the images of a web page are those elements which mainly attract the attention of the user. This assumption implies that the text contained in the visual block in which an image is located, called image-block, should contain significant information about the page contents. In this paper we propose a new metric, called the Inverse Term Importance Metric, aimed at assigning higher weights to important terms contained into important image-blocks identified by performing a visual layout analysis. We propose different methods to estimate the visual image-blocks importance, to smooth the term weight according to the importance of the blocks in which the term is located. The traditional TFxIDF model is modified accordingly and used in the classification task. The effectiveness of this new metric and the proposed block evaluation methods have been validated using different classification algorithms.
AbstractList	We present a term weighting approach for improving web page classification, based on the assumption that the images of a web page are those elements which mainly attract the attention of the user. This assumption implies that the text contained in the visual block in which an image is located, called image-block, should contain significant information about the page contents. In this paper we propose a new metric, called the Inverse Term Importance Metric, aimed at assigning higher weights to important terms contained into important image-blocks identified by performing a visual layout analysis. We propose different methods to estimate the visual image-blocks importance, to smooth the term weight according to the importance of the blocks in which the term is located. The traditional TFxIDF model is modified accordingly and used in the classification task. The effectiveness of this new metric and the proposed block evaluation methods have been validated using different classification algorithms. [PUBLICATION ABSTRACT] We present a term weighting approach for improving web page classification, based on the assumption that the images of a web page are those elements which mainly attract the attention of the user. This assumption implies that the text contained in the visual block in which an image is located, called image-block, should contain significant information about the page contents. In this paper we propose a new metric, called the Inverse Term Importance Metric, aimed at assigning higher weights to important terms contained into important image-blocks identified by performing a visual layout analysis. We propose different methods to estimate the visual image-blocks importance, to smooth the term weight according to the importance of the blocks in which the term is located. The traditional TFxIDF model is modified accordingly and used in the classification task. The effectiveness of this new metric and the proposed block evaluation methods have been validated using different classification algorithms. Adapted from the source document. We present a term weighting approach for improving web page classification, based on the assumption that the images of a web page are those elements which mainly attract the attention of the user. This assumption implies that the text contained in the visual block in which an image is located, called image-block, should contain significant information about the page contents. In this paper we propose a new metric, called the Inverse Term Importance Metric, aimed at assigning higher weights to important terms contained into important image-blocks identified by performing a visual layout analysis. We propose different methods to estimate the visual image-blocks importance, to smooth the term weight according to the importance of the blocks in which the term is located. The traditional TFxIDF model is modified accordingly and used in the classification task. The effectiveness of this new metric and the proposed block evaluation methods have been validated using different classification algorithms.
Author	Archetti, F. Messina, E. Fersini, E.
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SubjectTerms	Algorithms Classification Content analysis Document classification Exact sciences and technology Indexing. Classification. Abstracting Indexing. Classification. Abstracting. Syntheses Information and communication sciences Information and document structure and analysis Information processing and retrieval Information retrieval Information retrieval. Man machine relationship Information science. Documentation Internet Layout Research process. Evaluation Sciences and techniques of general use Studies Term weighting Vector space model Visual layout analysis Web pages Websites Weighting
Title	Enhancing web page classification through image-block importance analysis
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