An Automatic Text Summarization Approach using Content-Based and Graph-Based Characteristics

Sornil, Ohm; Gree-ut, K.

doi:10.1109/iccis.2006.252361

Cited by 20 publications

(14 citation statements)

References 19 publications

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“…The information about who is doing what to whom clarifies the contribution of each term in a sentence to the meaning of the main topic of that sentence [9].This concept-based mining model captures the semantic structure of each term within a sentence rather than the frequency of the term alone. This similarity measure outperforms other similarity measures that are based on term analysis models [10].…”

Section: Concept Based Segmentation Processmentioning

confidence: 88%

Query Sensitive Comparative Summarization of Search Results Using Concept Based Segmentation

Chitra¹

2011

CSEIJ

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Section: Concept Based Segmentation Processmentioning

confidence: 88%

Query Sensitive Comparative Summarization of Search Results Using Concept Based Segmentation

Chitra¹

2011

CSEIJ

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“…A similar idea has been demonstrated as a tool on the Ainibot Website 4 . DTV provides a representative overview structure of a Web page in the form of a tree structure as shown in Figure 3.…”

Section: Document Type View (Dtv)mentioning

confidence: 97%

“…The original can be a single document or multiple documents, whereas the result can be in the form of a short passage or a list of main sentences from the original document. In addition, the result can be established by extraction or abstraction from the original text [4]. A summary by extraction is to find a part of text that can be considered as an indicative passage of the content by choosing the best ranked sentences [3].…”

Section: ) Text Summarizationmentioning

confidence: 99%

Discover Information and Knowledge from Websites Using an Integrated Summarization and Visualization Framework

Fung

Thanadechteemapat

2010

2010 Third International Conference on Knowledge Discovery and Data Mining

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Abstract-The number of Web sites has noticeably increased to roughly 225 million in the last ten years. This means there is a rapid growth of knowledge and information on the Internet. Although search engines can help users to filter their desired information based on key words, the searched result is normally presented in the form of a list, and users have to visit each Web page in order to determine the appropriateness of the result. A considerable amount of time therefore has to be spent on finding the required information. To address this issue, this paper proposes a knowledge discovery approach on the Web by providing an overview of the information on a Website using an integration of summarization and visualization techniques. This includes text summarization, tag cloud, Document Type View, and interactive features such as drill down and thumbnails. This approach is capable to reduce the time required to identify and search for information or knowledge from the Web.

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“…The summary can be produced by extraction or abstraction from the original text [12]. A summary by extraction is to find a part of text that can be considered as indicative of the content using choosing the best rank of sentences [11].…”

Section: Text Summarizationmentioning

confidence: 99%

Summarizing information from Web sites on distributed power generation and alternative energy development

Fung

Thanadechteemapat

Wong

2009

8th International Conference on Advances in Power System Control, Operation and Management (APSCOM 2009)

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The World Wide Web (WWW) has become a huge repository of information and knowledge, and an essential channel for information exchange. Many sites and thousands of pages of information on distributed power generation and alternate energy development are being added or modified constantly and the task of finding the most appropriate information is getting difficult. While search engines are capable to return a collection of links according to key terms and some forms of ranking mechanism, it is still necessary to access the Web page and navigate through the site in order to find the information. This paper proposes an interactive summarization framework called iWISE to facilitate the process by providing a summary of the information on the Web site. The proposed approach makes use of graphical visualization, tag clouds and text summarization. A number of cases are presented and compared in this paper with a discussion on future work.

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An Automatic Text Summarization Approach using Content-Based and Graph-Based Characteristics

Cited by 20 publications

References 19 publications

Query Sensitive Comparative Summarization of Search Results Using Concept Based Segmentation

Query Sensitive Comparative Summarization of Search Results Using Concept Based Segmentation

Discover Information and Knowledge from Websites Using an Integrated Summarization and Visualization Framework

Summarizing information from Web sites on distributed power generation and alternative energy development

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