More and more people read the news online, eg, by visiting the websites of their favorite newspapers or by navigating the sites of news aggregators. However, the abundance of …
Content-based recommender systems (CBRSs) rely on item and user descriptions (content) to build item representations and user profiles that can be effectively exploited to suggest …
News consumption has shifted over time from traditional media to online platforms, which use recommendation algorithms to help users navigate through the large incoming streams …
User-generated content has dominated the web's recent growth and today the so-called real- time web provides us with unprecedented access to the real-time opinions, views, and …
F Goossen, W IJntema, F Frasincar… - Proceedings of the …, 2011 - dl.acm.org
When recommending news items, most of the traditional algorithms are based on TF-IDF, ie, a term-based weighting method which is mostly used in information retrieval and text mining …
Recommender systems are built to provide the most proper item or information within the huge amount of data on the internet without the manual effort of the users. As a specific …
A Hawalah, M Fasli - Expert Systems with Applications, 2014 - Elsevier
As users may have different needs in different situations and contexts, it is increasingly important to consider user context data when filtering information. In the field of web …
O Baysal, MW Godfrey, R Cohen - 2009 IEEE 17th …, 2009 - ieeexplore.ieee.org
Assigning bug reports to individual developers is typically a manual, time-consuming, and tedious task. In this paper, we present a framework for automated assignment of bug-fixing …
N Jonnalagedda, S Gauch - 2013 IEEE/WIC/ACM International …, 2013 - ieeexplore.ieee.org
Online news reading has become a popular way to read news articles from a huge collection of news sources around the globe. News recommender systems help users …