Despite of success in both research and industry, traditional collaborative filtering (CF) based recommender systems suffer from a fundamental problem, which lies in its dependence on users’ numeric ratings as its sole source of user preference information. User ratings are often unable to fully represent user preferences. As a result, it is difficult and error prone to identify genuinely simil...

Background: There is limited understanding about the development of the online one-stop shops for evidence in a limited-resource setting, such as Uganda. This study aimed to provide a comprehensive account of the development process of the online resource for local policy and systems-relevant information in this setting. Methods: We utilized a case study design to address our objective where ...

A closer look at how users perform search is needed in order to best design a more efficient next generation sentiment search engine and understand fundamental behaviours involved in online review/opinion search processes. The paper proposes utilizing personalized search, eye tracking and sentiment analysis for better understanding of end-user behavioural characteristics while making a judgemen...

Purpose – Modelling users’ interactions online is envisaged to allow developers to increase the usability of online systems and will aid system developers in building better systems to meet users’ needs, hereby creating better system design processes. Design/methodology/approach – The normative task model that was developed in this paper was created through an expert review of 14 online grocery...

The emergence of online product review forums has enabled firms to monitor consumer opinions about their products in real-time by mining publicly available information from the Internet. This paper studies the value of online product ratings in revenue forecasting of new experience goods. Our objective is to understand what metrics of online ratings are the most informative indicators of a prod...