BACKGROUND Previous studies have demonstrated how the media has an influence on policy decisions and healthcare coverage. Studies of Canadian media have shown that news coverage often emphasizes and hypes certain aspects of high profile health debates. We hypothesized that in Canadian media coverage of access to healthcare issues about therapies and technologies including for rare diseases, the...

Conservation science needs to engage the general public to ensure successful conservation interventions. Although online technologies such as Twitter and Facebook offer new opportunities to accelerate communication between conservation scientists and the online public, factors influencing the spread of conservation news in online media are not well understood. We explored transmission of conser...

Although commonly only item clustering is suggested by Web mining techniques for news articles recommendation systems, one of the various tasks of personalized recommendation is categorization of Web users. With the rapid explosion of online news articles, predicting user-browsing behavior using collaborative filtering (CF) techniques has gained much attention in the web personalization area. H...

English. This paper presents a methodology for the annotation of the semantic and functional components of news articles (Content Zones, henceforth CZs). We distinguish between narrative and descriptive zones and, within them, among finergrained units contributing to the overall communicative purpose of the text. Furthermore, we show that the segmentation in CZs could provide valuable cues for ...

Named entity disambiguation has become an important research area providing the basis for improving search engine precision and for enabling semantic search. Current approaches for the named entity disambiguation are usually based on exploiting structured semantic and lingual resources (e.g. WordNet, DBpedia). Unfortunately, each of these resources cover independently from each other insufficie...

A novel approach to news aggregation is proposed. Rather than ranking or summarisation of cluster topics, we propose that articles are grouped by topic similarity and then clustered within topic groups in order to identify archetypal articles that represent the various perspectives upon a topic. An example application is examined and a preliminary user study is discussed. Future applications an...

In this paper we present an approach for diversifying user comments on news articles. In our proposed framework, we analyse user comments w.r.t. four different criteria in order to extract the respective diversification dimensions in the form of feature vectors. These criteria involve content similarity, sentiment expressed within comments, article’s named entities also found within comments an...

We present a new context based event indexing and event ranking model for News Articles. The context event clusters formed from the UNL Graphs uses the modified scoring scheme for segmenting events which is followed by clustering of events. From the context clusters obtained three models are developed-Identification of Main and Sub events; Event Indexing and Event Ranking. Based on the properti...