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A Novel Approach for Crawling the Opinions from World Wide Web

A Novel Approach for Crawling the Opinions from World Wide Web

Surbhi Bhatia, Manisha Sharma, Komal Kumar Bhatia
Copyright: © 2016 |Volume: 6 |Issue: 2 |Pages: 23
ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781466692497|DOI: 10.4018/IJIRR.2016040101
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MLA

Bhatia, Surbhi, et al. "A Novel Approach for Crawling the Opinions from World Wide Web." IJIRR vol.6, no.2 2016: pp.1-23. http://doi.org/10.4018/IJIRR.2016040101

APA

Bhatia, S., Sharma, M., & Bhatia, K. K. (2016). A Novel Approach for Crawling the Opinions from World Wide Web. International Journal of Information Retrieval Research (IJIRR), 6(2), 1-23. http://doi.org/10.4018/IJIRR.2016040101

Chicago

Bhatia, Surbhi, Manisha Sharma, and Komal Kumar Bhatia. "A Novel Approach for Crawling the Opinions from World Wide Web," International Journal of Information Retrieval Research (IJIRR) 6, no.2: 1-23. http://doi.org/10.4018/IJIRR.2016040101

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Abstract

Due to the sudden and explosive increase in web technologies, huge quantity of user generated content is available online. The experiences of people and their opinions play an important role in the decision making process. Although facts provide the ease of searching information on a topic but retrieving opinions is still a crucial task. Many studies on opinion mining have to be undertaken efficiently in order to extract constructive opinionated information from these reviews. The present work focuses on the design and implementation of an Opinion Crawler which downloads the opinions from various sites thereby, ignoring rest of the web. Besides, it also detects web pages which frequently undergo updation by calculating the timestamp for its revisit in order to extract relevant opinions. The performance of the Opinion Crawler is justified by taking real data sets that prove to be much more accurate in terms of precision and recall quality attributes.

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