Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Understanding user behavior in online feedback reporting
Proceedings of the 8th ACM conference on Electronic commerce
Red Opal: product-feature scoring from reviews
Proceedings of the 8th ACM conference on Electronic commerce
Analyzing and Detecting Review Spam
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
An easy-to-implement fuzzy expert package with applications using existing Java classes
Expert Systems with Applications: An International Journal
Developing the index for product design communication and evaluation from emotional perspectives
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
e-Commerce is becoming an increasingly popular trend nowadays, where a consumer can buy a product through the internet. After buying a product, consumers can post their reviews and comments about the product in web sites and blogs. These comments can be a powerful source of finding out the consumer preferences and making recommendations of products to a new consumer who desires to buy a product. Even though there are existing systems which try to utilize these reviews and try to find the inherent quality of a product, a complete and comprehensive system is absent which provides a mechanism to rate products without any bias. Hence, an attempt is made to propose a complete system which starts from reviews collection to the analysis of reviews and the final score calculation of a product. The novel methods used in this system are the calculation of spam level of each review and the calculation of scores for each feature of a product. Fuzzy logic is used to calculate the spam level scores and the product ratings.