Genius is a popular commercial music recommender system that is based on collaborative filtering of huge amounts of user data. To understand the aspects of music similarity that collaborative filtering can capture, we compare Genius to two canonical music recommender systems: one based purely on artist similarity, the other purely on similarity of acoustic content. We evaluate this comparison w...

We propose novel algorithms for automatically determining a user’s profile from his/her content usage history (profiling agent), and automatically filtering content according to the user’s profile (filtering agent). A fuzzy inference system is used to construct and periodically update the preferences of a user based on the user’s interactions with various types of content over an observation pe...

Recommender Systems apply machine learning and data mining techniques for filtering unseen information and can predict whether a user would like a given resource. To date a number of recommendation algorithms have been proposed, where collaborative filtering and content-based filtering are the two most famous and adopted recommendation techniques. Collaborative filtering recommender systems rec...

This paper proposes a method for creating a high quality collection of researchers’ homepages. The proposed method consists of three phases: rough filtering of the possible web pages, accurate evaluation of the web pages and precise selection of the correct homepages. For the rough filtering, the authors first define content-based keyword-lists, then generate filtering rules and relax the rules...

recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. user similarity measurement plays an important role in collaborative filtering based recommender systems. in order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

One fundamental issue in today On-line Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is a...

Web applications increasingly utilize search techniques that heavily rely on content-based text and image analyses. For example, for parental site filtering, it is necessary to identify adult sites. These applications must rely on a semantic analysis of images in the process of identification where text analysis alone is insufficient. In this article, we describe our site filtering system "WebG...

Semantic filtering of multimedia content is a challenging problem. The gap that exists between low-level media features and high-level semantics of multimedia is difficult to bridge. We propose a flexible probabilistic graphical framework to bridge this gap to some extent and perform automatic detection of semantic concepts. Using probabilistic multimedia objects (multijects) and a network of s...

Email spam is the most effective form of online advertising. Unlike telephone marketing, email spamming does not require huge human or financial resources investment. Most existing spam filtering techniques concentrate on the emails’ content. However, most spammers obfuscate their emails’ content to circumvent content-based spam filters. An integrated solution for restricting spam emails is nee...