Presentation at the 20th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 09), Dublin, 19th - 21st August 2009In this paper, we consider a classification-based approach to the recommendation of user-generated product reviews. In particular, we develop review ranking techniques that allow the most helpful reviews for a particular product to be recommended, thereby facilitating users to readily asses the quality of the product in question. We apply a supervised machine learning approach to this task and compare the performance achieved by several classification algorithms using a large-scale study based on TripAdvisor hotel reviews. Our findings indicate that our approach is successful in recommending helpful reviews c...
A huge amount of data is available on the internet and social media platforms. It is necessary to us...
Review helpfulness prediction has attracted growing attention of researchers that proposed various s...
Online reviews increase consumer visits, increase the time spent on the website, and create a sense ...
Paper presented at Twenty-ninth SGAI International Conference (AI-2009), Cambridge, UK, 15th-17th De...
Paper presented at the 21st Irish Conference on Artificial Intelligence and Cognitive Science (AICS ...
Many online stores encourage their users to submit product or service reviews in order to guide futu...
Paper presented at the 3rd ACM Conference on Recommender Systems (RecSys 2009), New York City, NY, U...
In this paper, we first classify the text reviews given by different users on different products. Th...
Abstract: The aim of the paper is to implement and analyze the machine learning models for product r...
For some of the most popular products, hundreds, if not thousands, of online product reviews are wri...
22nd International Conference on Case-Based Reasoning, Cork, Ireland, 29 September - 01 October 2014...
Project (M.S., Computer Science)--California State University, Sacramento, 2014.Online shopping webs...
In e-commerce systems, customer reviews are important information for understanding market feedbacks...
Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13), Beijing, China, ...
Abstract. The information in customer reviews is of great interest to both companies and consumers. ...
A huge amount of data is available on the internet and social media platforms. It is necessary to us...
Review helpfulness prediction has attracted growing attention of researchers that proposed various s...
Online reviews increase consumer visits, increase the time spent on the website, and create a sense ...
Paper presented at Twenty-ninth SGAI International Conference (AI-2009), Cambridge, UK, 15th-17th De...
Paper presented at the 21st Irish Conference on Artificial Intelligence and Cognitive Science (AICS ...
Many online stores encourage their users to submit product or service reviews in order to guide futu...
Paper presented at the 3rd ACM Conference on Recommender Systems (RecSys 2009), New York City, NY, U...
In this paper, we first classify the text reviews given by different users on different products. Th...
Abstract: The aim of the paper is to implement and analyze the machine learning models for product r...
For some of the most popular products, hundreds, if not thousands, of online product reviews are wri...
22nd International Conference on Case-Based Reasoning, Cork, Ireland, 29 September - 01 October 2014...
Project (M.S., Computer Science)--California State University, Sacramento, 2014.Online shopping webs...
In e-commerce systems, customer reviews are important information for understanding market feedbacks...
Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13), Beijing, China, ...
Abstract. The information in customer reviews is of great interest to both companies and consumers. ...
A huge amount of data is available on the internet and social media platforms. It is necessary to us...
Review helpfulness prediction has attracted growing attention of researchers that proposed various s...
Online reviews increase consumer visits, increase the time spent on the website, and create a sense ...