Mining Opinion Targets and Opinion Words from Reviews using Natural Language Processing (NLP) Techniques
Er. Samadhan U. Birajdar
, Prof. V. A. Losarwar
Feature Extraction, Stanford NLP, Opinion Review, Multi Word Aspects
This Since e-commerce is becoming popular every day, the number of customer feedback that products receive increases at a faster rate because the internet has become commonplace in every home. For popular products, reviews can reach thousands of people. For manufacturers, there are additional problems because many merchant websites may sell the same products and usually manufacturers will produce many products. We intend to summarize all reviews of products that customers receive. Summarizing objective, includes adding small but specific details, such as features, aspects and words that describe the product. Therefore, this work is different from traditional text summaries because we are only interested in the specific aspects of products that customers have commented. In addition, we also extract details such as positive or negative comments. This analysis will allow manufacturers to adjust products and launch new products with better buying opportunities. We do not summarize opinions by choosing or writing a subset of the original sentences from reviews to capture the main points as in the classic text summary. Our main focus is to analyze the opinions of the product features that the reviewer has commented on. There are many techniques to present such features. In this research, we aim to dig and summarize all customer reviews of the product. We proposed to develop a hybrid approach that will allow manufacturers to utilize the reviews and opinions of the customer and help in analyzing and improving the product. We will use different evaluative measures such as precision, recall, f-measure to identify the key index parameters and efficiency of our system
"Mining Opinion Targets and Opinion Words from Reviews using Natural Language Processing (NLP) Techniques", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 2, page no.50 - 55, February-2020, Available :https://ijsdr.org/papers/IJSDR2002010.pdf
Volume 5
Issue 2,
February-2020
Pages : 50 - 55
Paper Reg. ID: IJSDR_191297
Published Paper Id: IJSDR2002010
Downloads: 000347505
Research Area: Engineering
Country: Aurangabad, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
