In this paper, we present a systematic framework for a fast and easy implementation and deployment of a recommendation system for one or several Websites, based on any available combination of open source tools that include crawling, indexing, and searching capabilities. The supported recommendation strategies include several popular flavors such as content based filtering (straight forward), c...

The article presents a survey of personalization and customization technologies. It starts with an analysis of user profiling and explains how user profiles can be used for generating personalized products and services. The article explains some standard personalization techniques such as rule-based filtering, collaborative filtering, and content-based filtering. Web usage mining is also explai...

Collaborative filtering methods (CF) exploit the wisdom of crowds to capture deeply structured similarities in musical objects, such as songs, artists or albums. When CF is available, it frequently outperforms content-based methods in recommendation tasks. However, songs in the so-called “long tail” cannot reap the benefits of collaborative filtering, and practitioners must rely on content-base...

Users of Social Networking Sites (SNS) consume SNS content by means of online social streams such as the newsfeed system on Facebook. In this regard, a Facebook newsfeed content may comprise different kinds of user generated content, but also editorial content provided by fan pages, business pages or advertisers. Before being displayed on the Facebook newsfeed, contents are automatically pre-se...

Many businesses are using recommender systems for marketing outreach. Recommendation algorithms can be either based on content or driven by collaborative filtering. We study different ways to incorporate content information directly into the matrix factorization approach of collaborative filtering. These content-boosted matrix factorization algorithms not only improve recommendation accuracy, b...

This paper discusses an overview of data mining techniques for personalization. It discusses some of the standard techniques which are used in order to adapt and increase the ability of the system to tailor itself to specific user behavior. We discuss several such techniques such as collaborative filtering, content based methods, and content based collaborative filtering methods. We examine the...