Knowledge organization systems such as thesauri or taxonomies are increasingly being expressed using the Simple Knowledge Organization System (SKOS) and published as structured data on the Web. Search engines can exploit these vocabularies and improve ...

In this paper, a hybrid recommender system for job seeking and recruiting websites is presented. The various interaction features designed on the website help the users organize the resources they need as well as express their interest. The hybrid ...

This work presents a novel method for the generation of a knowledge base oriented to Sentiment Analysis from the continuous stream of published micro-blogs in social media services like Twitter. The method is simple in its approach and has shown to be ...

Commonsense knowledge representation and reasoning support a wide variety of potential applications in fields such as document auto-categorization, Web search enhancement, topic gisting, social process modeling, and concept-level opinion and sentiment ...

Opinion holder and opinion target extraction are among the most popular and challenging problems tackled by opinion mining researchers, recognizing the significant business value of such components and their importance for applications such as media ...

With the steady increase of videos published on media sharing platforms such as Dailymotion and YouTube, more and more efforts are spent to automatically annotate and organize these videos. In this paper, we propose a framework for classifying video ...

Helping users to understand the news is an acute problem nowadays as the users are struggling to keep up with tremendous amount of information published every day in the Internet. In this research, we focus on modelling the content of news events by ...

Aiming to improve user experience for a job search engine, in this paper we propose an idea to switch from query-biased snippets used by most web search engines to rich structured snippets associated with the main sections of a job posting page, which ...

Interest in domain-specific search is steadfastly increasing, yielding a growing need for domain-specific synonym discovery. Existing synonym discovery methods perform poorly when faced with the realistic task of identifying a target term's synonyms ...

This paper presents a framework for automatically constructing timeline summaries from collections of web news articles. We also evaluate our solution against manually created timelines and in comparison with related work.

Traditional works in sentiment analysis do not incorporate author preferences during sentiment classification of reviews. In this work, we show that the inclusion of author preferences in sentiment rating prediction of reviews improves the correlation ...