Personalized Information Access Using Semantic Knowledge


Handling the amount of information on the Web, known as the information overload problem, requires tremendous effort. One approach that relieves the user from this burden is offering personalized information access. Systems that adopt to users’ preferences are called adaptive systems. Based on a user profile containing details about the users’ preferences, the system adapts its content or the user interface to the user. In this chapter, we present a personalized news information system, providing users with entertainment news tailored to their needs. Using semantic technologies, the time to learn user preferences is reduced to a few interactions. We present the system in detail, and present an evaluation showing the benefits coming with the semantic approach.

author = {Till Plumbaum, Andreas Lommatzsch},
booktitle = {Smart Information Systems - Computational Intelligence for Real-Life Applications},
chapter = {Personalized Information Access Using Semantic Knowledge},
editor = {Frank Hopfgartner},
organization = {Springer},
publisher = {Springer}, 
series = {Advances in Computer Vision and Pattern Recognition},
volume = {...},
year = {2015},
ISBN = {978-3-319-14177-0},
ISSN = {...},
Till Plumbaum, Andreas Lommatzsch
Smart Information Systems - Computational Intelligence for Real-Life Applications, Springer; 2015