We are working on behavioral marketing in the Internet. On one hand we observe the behavior of visitors, and on the other hand we trigger (in real-time) stimulations intended to al...
Abstract. In many activities, such as watching movies or having dinner, people prefer to find partners before participation. Therefore, when recommending activity items (e.g., mov...
Wenting Tu, David Wai-Lok Cheung, Nikos Mamoulis, ...
Searching for patterns in graphs is an active field of data mining. In this context, most work has gone into discovering subgraph patterns, where the task is to find strictly de...
Tayena Hendrickx, Boris Cule, Pieter Meysman, Stef...
With social media sites, such as Twitter, providing a visual record of the daily interests and concerns of users in the form of tweets and tweeting behaviors, there is growing dema...
Recommender systems research has experienced different stages such as from user preference understanding to content analysis. Typical recommendation algorithms were built on the fo...
Associative Classification (AC) is a well known tool in knowledge discovery and it has been proved to extract competitive classifiers. However, imbalanced data has posed a challeng...
With the popularization of positioning devices such as GPS navigators and smart phones, large volumes of spatiotemporal trajectory data have been produced at unprecedented speed. F...
The recent advancements in online social networks and mobile devices have provided valuable data sources to track users’ smartphone adoption, i.e., the usage of smartphones over ...
Le Wu, Yin Zhu, Nicholas Jing Yuan, Enhong Chen, X...
Abstract. Predicting next items of sequences of symbols has many applications in a wide range of domains. Several sequence prediction models have been proposed such as DG, All-k-or...
Ted Gueniche, Philippe Fournier-Viger, Rajeev Rama...