Review Mining: A New Approach using Modified NLP
Umang Sardesai1, Aakash Makwana2, Sagar Haria3
1Umang Sardesai, U.G. Student, Department of Computer, DJSCOE, Vile-Parle (W), Mumbai (Maharashtra), India.
2Aakash Makwana, U.G. Student, Department of Computer, DJSCOE, Vile-Parle (W), Mumbai (Maharashtra), India.
3Sagar Haria, U.G. Student, Department of Computer, DJSCOE, Vile-Parle (W), Mumbai (Maharashtra), India.
Manuscript received on 20 May 2014 | Revised Manuscript received on 25 May 2014 | Manuscript published on 30 May 2014 | PP: 87-90 | Volume-3 Issue-2, May 2014 | Retrieval Number: B1108053214/2014©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. Nowadays we get all the technical specifications of a product on the Web, but what matters is what the customer feels about or what his opinions about the product are. This paper focuses on analyzing and summarizing online customer reviews of products. While analyzing we devise a new approach for NLP, by assigning a latent weight to each aspect/feature of a product. After extracting the sentiment in each sentence of the review, we summarize the opinions and express it graphically. This will not only help customers but also help the product manufacturers to get an indirect customer feedback.
Keywords: NLP, Sentiment Analysis, Opinion mining, Latent weight, Visualization
Scope of the Article: Predictive Analysis