Improving product rating system with text mining on product review/comments
Cataloged from PDF version of thesis report.
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BRAC University
2014
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| Accés en línia: | http://hdl.handle.net/10361/3221 |
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10361-3221 |
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10361-32212022-01-26T10:20:08Z Improving product rating system with text mining on product review/comments Karim, Md. Ahsanul Islam, Raduanul Ahmed, Sk. Wasif Rahman, Md. Zahidur Department of Computer Science and Engineering, BRAC University Computer science and engineering Cataloged from PDF version of thesis report. Includes bibliographical references (page 23). This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. It is often considered a better exercise to have a complete idea of a particular service or a product before availing it. Now a days almost every online shopping sites or even the manufacturer of the product has a star based rating system and review/comment zone in their website. It is often not feasible to go through all the review before purchasing or availing that particular product. So people often tends to have an idea based on the number of stars on that product.Currently available systems use a star based rating where people rate the service or product on the scale of 5 or 10. The problem with that is when they give those rating stars they often tends to give it without giving much thought to it. User experience level and his mind set while rating varies very much. For example a person who loves particular brand of Soda, if he drink soda of another brand he might rate it lower than what it should be because he is used to a particular brand. But when he writes a review the chances are higher that he will write the major positive and negative aspects of that product . Thus the chances of getting a better feedback comes when it is review rather than stars. But as it has been mentioned earlier, going through all the reviews are not feasible. So we tried to improve the rating system by extracting information from the review text by using text mining technique upon that. Raduanul Islam Sk. Wasif Ahmed Md. Ahsanul Karim B. Computer Science and Engineering 2014-05-12T08:15:58Z 2014-05-12T08:15:58Z 2014 4/30/2014 Thesis ID 10101023 ID 14141015 ID 10101027 http://hdl.handle.net/10361/3221 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 23 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Computer science and engineering |
| spellingShingle |
Computer science and engineering Karim, Md. Ahsanul Islam, Raduanul Ahmed, Sk. Wasif Improving product rating system with text mining on product review/comments |
| description |
Cataloged from PDF version of thesis report. |
| author2 |
Rahman, Md. Zahidur |
| author_facet |
Rahman, Md. Zahidur Karim, Md. Ahsanul Islam, Raduanul Ahmed, Sk. Wasif |
| format |
Thesis |
| author |
Karim, Md. Ahsanul Islam, Raduanul Ahmed, Sk. Wasif |
| author_sort |
Karim, Md. Ahsanul |
| title |
Improving product rating system with text mining on product review/comments |
| title_short |
Improving product rating system with text mining on product review/comments |
| title_full |
Improving product rating system with text mining on product review/comments |
| title_fullStr |
Improving product rating system with text mining on product review/comments |
| title_full_unstemmed |
Improving product rating system with text mining on product review/comments |
| title_sort |
improving product rating system with text mining on product review/comments |
| publisher |
BRAC University |
| publishDate |
2014 |
| url |
http://hdl.handle.net/10361/3221 |
| work_keys_str_mv |
AT karimmdahsanul improvingproductratingsystemwithtextminingonproductreviewcomments AT islamraduanul improvingproductratingsystemwithtextminingonproductreviewcomments AT ahmedskwasif improvingproductratingsystemwithtextminingonproductreviewcomments |
| _version_ |
1814309245435248640 |