TITLE:
Generating Recommendation Status of Electronic Products from Online Reviews
AUTHORS:
Bolanle Adefowoke Ojokoh, Olufunke Catherine Olayemi, Olumide Sunday Adewale
KEYWORDS:
Opinion Aggregation; Electronic Commerce; Infrequent Feature; Electronic Product; Recommendation
JOURNAL NAME:
Intelligent Control and Automation,
Vol.4 No.1,
February
5,
2013
ABSTRACT: The need for effective and efficient mining of online reviews cannot be overemphasized. This position is as a result of the overwhelmingly large number of reviews available online which makes it cumbersome for customers to read through all of them. Hence, the need for online web review mining system which will help customers as well as manufacturers read through a large number of reviews and provide a quick description and summary of the performance of the product. This will assist the customer make better and quick decision, and also help manufacturers improve their products and services. This paper describes a research work that focuses on mining the opinions expressed on some electronic products, providing ranks or ratings for the features, with the aim of summarizing them and making recommendations to potential customers for better online shopping. A technique is also proposed for scoring segments with infrequent features. The evaluation results using laptops demonstrate the effectiveness of these techniques.