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Novel Text Summarization Techniques for Contextual Advertising

Novel Text Summarization Techniques for Contextual Advertising

Giuliano Armano, Alessandro Giuliani
Copyright: © 2014 |Pages: 20
ISBN13: 9781466650190|ISBN10: 1466650192|EISBN13: 9781466650206
DOI: 10.4018/978-1-4666-5019-0.ch008
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MLA

Armano, Giuliano, and Alessandro Giuliani. "Novel Text Summarization Techniques for Contextual Advertising." Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding, edited by Alessandro Fiori, IGI Global, 2014, pp. 185-204. https://doi.org/10.4018/978-1-4666-5019-0.ch008

APA

Armano, G. & Giuliani, A. (2014). Novel Text Summarization Techniques for Contextual Advertising. In A. Fiori (Ed.), Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding (pp. 185-204). IGI Global. https://doi.org/10.4018/978-1-4666-5019-0.ch008

Chicago

Armano, Giuliano, and Alessandro Giuliani. "Novel Text Summarization Techniques for Contextual Advertising." In Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding, edited by Alessandro Fiori, 185-204. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-5019-0.ch008

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Abstract

Recently, there has been a renewed interest on automatic text summarization techniques. The Internet has caused a continuous growth of information overload, focusing the attention on retrieval and filtering needs. Since digitally stored information is more and more available, users need suitable tools able to select, filter, and extract only relevant information. This chapter concentrates on studying and developing techniques for summarizing Webpages. In particular, the focus is the field of contextual advertising, the task of automatically suggesting ads within the content of a generic Webpage. Several novel text summarization techniques are proposed, comparing them with state of the art techniques and assessing whether the proposed techniques can be successfully applied to contextual advertising. Comparative experimental results are also reported and discussed. Results highlight the improvements of the proposals with respect to well-known text summarization techniques.

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