Unlike traditional recommender systems, which make recommendations only by using the
relation between users and items, a context-aware recommender system makes …

Text clustering is a text mining task which is often used to aid the organization, knowledge
extraction, and exploratory search of text collections. Nowadays, the automatic text …

The area of sentiment analysis has experienced significant developments in the last few
years. More specifically, there has been growing interest in aspect-based sentiment analysis …

Globalization places people in a multilingual environment. There is a growing number of
users to access and share information in several languages for public or private purpose. In …

Automatically deciding if two or more news articles cover the same event—thereby building
a story chain—is an important problem in news analytics, and knowledge about such story …

In news aggregation systems focused on broad news domains, certain stories may appear
in multiple articles. Depending on the relative importance of the story, the number of …

Data is mostly stored in digital format rather than hard copy because the former is safer,
more secure, smaller in size, and faster to retrieve than the latter. With the increasing …

This work in progress paper presents initial results on the development and testing of a
novel assessment tool utilizing an ethics transfer case methodology targeted at measuring …

In this article, we present a new algorithm for clustering a bilingual collection of comparable
news items in groups of specific topics. Our hypothesis is that named entities (NE s) are …

In this paper, we investigate challenges related to the adaptation of similarity measures used
in the field of Information Retrieval to work with semantic features, ie Named Entities. The …