Glossary Collaborative filtering: a recommendation method which is based on rating information of the user community Content-based filtering: a recommendation method which is based on characteristics of the recommended items as well as individual user feedback Hybrid recommender system: a recommender system that combines different recommendation approaches or data sources Rating matrix: a grid ...

The problem of Recommender systems is to apply knowledge discovery techniques and to provide personalized recommendations. A recommender system tracks past actions of a group of users to make recommendations to individual members of the group. In today’s e-commerce world these systems are achieving widespread success. Content based and collaborative filtering based approaches are the two major ...

Applying traditional collaborative filtering to digital publishing is challenging because user data is very sparse due to the high volume of documents relative to the number of users. Content based approaches, on the other hand, is attractive because textual content is often very informative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To ...

In the Internet era, information processing for personalization and relevance has been one of the key topics of research and development. It ranges from design of applications like search engines, web crawlers, learning engines to reverse image searches, audio processed search, auto complete, etc. Information retrieval plays a vital role in most of the above mentioned applications. A part of in...

Why it's needed, how it works, and solutions from SonicWALL ® CONTENTS Importance of content filtering – For businesses – For schools and libraries 2 How content filtering works – Site blocking versus content monitoring – Solution architectures 4 SonicWALL content filtering solutions – SonicWALL Content Filtering Service – SonicWALL Content Security Manager 2100 Content Filter – Features and be...

Real-time content analysis can be a bottleneck in Web filtering. This work presents a simple, but effective early decision algorithm to accelerate the filtering process by examining only part of the Web content. The algorithm can make the filtering decision, either to block or to pass the Web content, as soon as it is confident with a high probability that the content should belong to a banned ...

While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the re...

Building recommender systems, that filters and suggests relevant and personalized information to its user, has become a practical challenge for researchers in AI. On the other hand, the relevance of such information is a userdependent notion, defmed within the scope or context of a particular domain or topic. Previous work, mainly in IR, focuses on the analysis of the content by means of keywor...