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  • Subject area(s): Marketing
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  • Published on: 14th September 2019
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...Abstract - Online shopping is becoming increasingly important as more and more manufacturers sell products on the Internet, and many users are using the Internet to express and share their opinions. However, it is impossible for consumers to read all product reviews. Therefore, it is necessary to design effective systems to summarize the pros and cons of product characteristics, so that consumers can quickly find their favorable products. In this paper, we present a product ranking system using opinion mining techniques. Users can specify product features to get back the ranking results of all matched products. In this system, we consider three issues while calculating product scores: 1) product reviews, 2) product popularity, and 3) product release month. Finally, the experimental results show that the system is practical and the ranking results are interesting using Hadoop.

Key Words:  Opinion mining, sentiment analysis, information retrieval, XML document, POS (Part of Speech).

1. INTRODUCTION

In this paper, a product ranking system using opinion mining techniques to find favorable products for users is presented. Opinion mining was a hot research topic in recent years. Some papers have explored opinion mining methods to identify the polarity [2-4] or to improve accuracy [5, 6]. Opinion mining is very suitable for the applications 'many users to discuss a single topic' when a large number of sentences and reviews are on the criticism of a single topic or when exactly identifying the correct rate of a bias direction is required to improve accuracy. Here, our product ranking system considers three issues while calculating product scores 1) product reviews, 2) product popularity, and 3) product release month. Eventually, our system would provide users to specify product features in a query, and send back the ranking results of all matched products.

1.1 PROJECT IDEA

The rapid growth of the Web and the convenience of the Internet, more and more people have been changing their shopping habits from traditional to online shopping. For online shopping, since thousands of products are posted on shopping websites, it is impossible for consumers to read all product reviews.

1.2 PROBLEM STATEMENT

This project aims to find the product with best quality and the quality is predicting from the users reviews about that product in online shopping. To find the best effective product, proposed work implements an approach called product ranking system, which rank the product efficiently by mining the genuine reviews of the product.

2. SCIENTIFIC FUNDAMENTALS

2.1 XML Documents

An XML document can be represented as a tree structure. A document tree could contain element nodes, attribute nodes, and text nodes which are all mapped from elements, attributes, and texts specified in an XML document.

2.2 XML Path Language

The XML Path Language (i.e., XPath) was defined by the W3C (World Wide Web Consortium), and it is a major element in

XSLT (Extensible Style sheet Language Transformations). XPath uses path expressions to select nodes or node-sets in

An XML document. A path expression is the path from an XML node (or the current context node) to another node, or a group of nodes written as a sequence of steps. The character "/" in a path expression is used to separate each step, and three constituent elements can be employed to reach a target node; i.e., 1) directly approaching the target node, 2) specifying the element node for screening, and 3) filtering the node with the attribute having a specified value.

Given an example as follows, we can use the path expression '// name[@kind='Laptop']' to find the node "name" with the attribute "kind" and the value "Laptop", and then call function text() to get the text 'MacBook Air'.

2.3 Part of Speech Tagging

The Part-of-speech tagging (i.e., POS tagging or POST), also called grammatical tagging or word-category disambiguation, is the process for assigning the correct part of speeches (e.g. noun, adjective, verb, adverb, etc.) to each word in a text based on both its definition and context.

2.4 Semantic Orientation

There are several methods commonly used to identify opinion words. The most well-known one is the unsupervised semantic orientation method proposed by Turn by. They used the Point-wise Mutual Information (PMI) to compute the association of two terms, and then calculated the phrase polarity.

2.5 Mathematical Model Mapping Diagram

A, B, C =Products

D   =Extraction of products

F1, F2, F3 =Building of XML file

B, A, C =Products ranking

Set Theory:

S = {s, e, X, Y}

S = Set of Product

s = Start of the program

X = Input of the program

X= {A, B, C}

   Where,

A, B, C =Products

Y = {B, A, C}

    Where,

    B, A, C =Ranking of products

e = End of the program

3. CONCLUSIONS

 Online shopping will become increasingly important as more and more manufacturers sell products on internet by expressing their opinions in form of reviews. Here we are interested in finding favorable product amongst matched product using Hadoop. We use opinion mining to identify the sentence polarity and then calculate the scores by using different formulas. The experimental result will show the system is practical and ranking results are interesting. The result may vary that new products are not always more favorable than old products.

ACKNOWLEDGEMENT

I would like to thank my guide prof. Shubhangi Patil, of computer department, SIT, Lonavala, provide a helpful guidance for writing this paper.

References

[1] Barath Sriram " Ranking Of Products Using Opinion Mining On Authentic Reviews",International Journal of Emerging Technology in Computer Science Electronics (IJETCSE) ISSN: 0976-1353 Volume 13 Issue 4-MARCH 2015.

[2] LiZhen Liu, WenTao Wang, HangShi Wang "Summarizing Customer Reviews Based On Product

Features",978-1-4673-0964-6/12/31:00012 IEEE.

[3] P.Ajitha "An approach of Opinion Mining for online marketing Using Sentiment Thesaurus and Concept Search Engine",978-1-4673-9825-1/15/3l:00 c 2015 IEEE.

[4] Kavita Bathe " Product Ranking using Opinion Mining',  International Journal of Research in Advent Technology, Vol.3, No.3, March 2015 E-ISSN: 2321-963747.

[5] Pravesh Kumar Singh " METHODOLOGICAL STUDY OF OPINION MINING AND SENTIMENT ANALYSIS TECHNIQUES', International Journal on Soft Computing (IJSC) Vol. 5, No. 1, February 2014.

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