This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …

With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

A large amount of information exists in reviews written by users. This source of information
has been ignored by most of the current recommender systems while it can potentially …

Recently, some E-commerce sites launch a new interaction box called Tips on their mobile
apps. Users can express their experience and feelings or provide suggestions using short …

The Web has accumulated a rich source of information, such as text, image, rating, etc,
which represent different aspects of user preferences. However, the heterogeneous nature …

An important factor affecting the performance of collaborative filtering for recommendation
systems is the sparsity of the rating matrix caused by insufficient rating data. Improving the …

Automated recommendations have become a pervasive feature of our online user
experience, and due to their practical importance, recommender systems also represent an …

In this paper, we propose a recommendation technique that not only can recommend items
of interest to the user as traditional recommendation systems do but also specific aspects of …

This paper presents a novel genetic-based recommender system (BLI GA) that depends on
the semantic information and historical rating data. The main contribution of this research …