Automated web data mining using semantic analysis

Wenxiang Dou; Jinglu Hu

doi:10.1007/978-3-642-35527-1_45

Automated web data mining using semantic analysis

Wenxiang Dou^*, Jinglu Hu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper presents an automated approach to extracting product data from commercial web pages. Our web mining method involves the following two phrases: First, it analyzes the data information located at the leaf node of DOM tree structure of the web page, generates the semantic information vector for other nodes of the DOM tree and find maximum repeat semantic vector pattern. Second, it identifies the product data region and data records, builds a product object template by using semantic tree matching technique and uses it to extract all product data from the web page. The main contribution of this study is in developing a fully automated approach to extract product data from the commercial sites without any user's assistance. Experiment results show that the proposed technique is highly effective.

Original language	English
Title of host publication	Advanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings
Pages	539-551
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-35527-1_45
Publication status	Published - 2012
Externally published	Yes
Event	8th International Conference on Advanced Data Mining and Applications, ADMA 2012 - Nanjing, China Duration: 2012 Dec 15 → 2012 Dec 18

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7713 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Advanced Data Mining and Applications, ADMA 2012
Country/Territory	China
City	Nanjing
Period	12/12/15 → 12/12/18

Keywords

Product data mining
Web data extraction
Web mining

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-35527-1_45

Cite this

Dou, W., & Hu, J. (2012). Automated web data mining using semantic analysis. In Advanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings (pp. 539-551). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7713 LNAI). https://doi.org/10.1007/978-3-642-35527-1_45

Automated web data mining using semantic analysis. / Dou, Wenxiang; Hu, Jinglu.

Advanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings. 2012. p. 539-551 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7713 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dou, W & Hu, J 2012, Automated web data mining using semantic analysis. in Advanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7713 LNAI, pp. 539-551, 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, Nanjing, China, 12/12/15. https://doi.org/10.1007/978-3-642-35527-1_45

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AB - This paper presents an automated approach to extracting product data from commercial web pages. Our web mining method involves the following two phrases: First, it analyzes the data information located at the leaf node of DOM tree structure of the web page, generates the semantic information vector for other nodes of the DOM tree and find maximum repeat semantic vector pattern. Second, it identifies the product data region and data records, builds a product object template by using semantic tree matching technique and uses it to extract all product data from the web page. The main contribution of this study is in developing a fully automated approach to extract product data from the commercial sites without any user's assistance. Experiment results show that the proposed technique is highly effective.

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Automated web data mining using semantic analysis

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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