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Survey Paper | Computer Science & Engineering | India | Volume 5 Issue 2, February 2016
A Survey Paper on Extraction of Web Services for Effective User Review Sentiment Analysis
Jyotsna A Pawar | Prof. N. R. Wankhade
Abstract: This paper presents a survey on features Extraction of Web Services for effective User Review Sentiment Analysis. Recognition of opinion features from online user reviews is a task to find on which feature user is going to put his opinion. For opinion feature identification there are number of existing techniques but, features are extracted from single corpus. Quality of Service has become a standard way of evaluating web services and selecting the one that suites user interests the best. Traditional methods adopt a fixed set of QoS parameters and typical ones include response time, fee, and availability. There currently lacks an effective way of identifying quality features that users are actually interested in when choosing a service. Meanwhile, the traditional way of collecting QoS values relies on either public information released by service providers or test results from repeatedly invoking a service. The last section of paper will discuss the disadvantages of current systems and will state the future scope.
Keywords: Opinion mining, Opinion feature, QoS, web services, sentiment analysis
Edition: Volume 5 Issue 2, February 2016,
Pages: 2175 - 2179
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Student Project, Computer Science & Engineering, India, Volume 10 Issue 12, December 2021
Pages: 1357 - 1360An Opinion Mining for Indian Premier League Using Machine Learning Techniques
Rakshith N [2] | Suraj B S | Chethana C
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Survey Paper, Computer Science & Engineering, India, Volume 3 Issue 12, December 2014
Pages: 2188 - 2191Sentiment Analysis by Visual Inspection of User Data from Social Sites - A Review on Opinion Mining
Vijayshri R. Ingale | Rajesh Nandkumar Phursule