Many websites over the Internet are producing a variety of textual data; such as news,
research articles, ebooks, personal blogs, and user reviews. In these websites, the textual …

Skip-gram with negative sampling, a popular variant of Word2vec originally designed and
tuned to create word embeddings for Natural Language Processing, has been used to …

Linked Open Data has been recognized as a valuable source for background information in
many data mining and information retrieval tasks. However, most of the existing tools require …

Social network platforms can use the data produced by their users to serve them better. One
of the services these platforms provide is recommendation service. Recommendation …

Collaborative filtering recommendation systems, which analyze sets of user ratings, have
been applied to various domains and have resulted in considerable improvements in the …

User engagement is crucial to the long-term success of a mobile app. Several metrics, such
as dwell time, have been used for measuring user engagement. However, how to effectively …

Due to the widespread usage of electronic devices and the growing popularity of social
media, a lot of text data is being generated at the rate never seen before. It is not possible for …

In this paper we present a deep content-based recommender system (DeepCBRS) that
exploits Bidirectional Recurrent Neural Networks (BRNNs) to learn an effective …

Recently, the recommender system has been raised as one of the essential research topics
in smart tourism. The massive card transaction data generated in the tourism industry has …

Distance metric learning based on triplet loss has been applied with success in a wide
range of applications such as face recognition, image retrieval, speaker change detection …