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Full-Text Articles in Physical Sciences and Mathematics
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Research Collection School Of Computing and Information Systems
Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of …
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Research Collection School Of Computing and Information Systems
Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Evaluation And Improvement Of Procurement Process With Data Analytics, Melvin H. C. Tan, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Analytics can be applied in procurement to benefit organizations beyond just prevention and detection of fraud. This study aims to demonstrate how advanced data mining techniques such as text mining and cluster analysis can be used to improve visibility of procurement patterns and provide decision-makers with insight to develop more efficient sourcing strategies, in terms of cost and effort. A case study of an organization’s effort to improve its procurement process is presented in this paper. The findings from this study suggest that opportunities exist for organizations to aggregate common goods and services among the purchases made under and across …
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Research Collection School Of Computing and Information Systems
From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example, sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users' travel preferences. The topic model (TM) method is an effective way to solve the "sparsity problem," but is still far …
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Research Collection School Of Computing and Information Systems
As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we …