Automatic Content Recommendation and Aggregation According to SCORM

Automatic Hashtag Recommendation in Social Networking and Microblogging Platforms Using a Knowledge-Intensive Content-based Approach

In social networking/microblogging environments, #tag is often used for categorizing messages and marking their key points. Also, since some social networks such as twitter apply restrictions on the number of characters in messages, #tags can serve as a useful tool for helping users express their messages. In this paper, a new knowledge-intensive content-based #tag recommendation system is intr...

Sharable Content Object Reference Model (SCORM)

Automatic Keywords Extraction – a Basis for Content Recommendation

This paper describes a use case for an application that recommends learning objects for reuse and is integrated in the authoring environment. The recommendations are based on the automatic detection of content being authored and the context in which this resource is authored or used. The focus of the paper is automatic keyword extraction, evaluated as a starting point for content analysis. The ...

An Automatic Multimedia Content Summarization System for Video Recommendation

In recent years, using video as a learning resource has received a lot of attention and has been successfully applied to many learning activities. In comparison with text-based learning, video learning integrates more multimedia resources, which usually motivate learners more than texts. However, one of the major limitations of video learning is that both instructors and learners must select su...

Multimedia content recommendation engine with automatic inference of user preferences

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...