Collaborative filtering is a new method for retrieving information. Instead of basing the search on the content in the information units, a collaborative filter or recommender system uses databases of user ratings as a basis for predictions. From our user studies we see that collaborative filtering can be of great help to users when they search for information. In order to be truly useful colla...

This research was triggered by the criticism on the emergence of homogeneity in recommendation within the collaborative filtering based recommender systems that put similarity as the main principle in the algorithm. To overcome the problem of homogeneity, this study proposes a novelty, i.e. the diversity of recommendations applied to the multicriteria collaborative filtering-based document reco...

Mobil listrik mulai menjadi pilihan beberapa tahun terakhir ini, karakternya yang lebih ramah lingkungan serta biaya pemeliharaan rendah daripada mobil konvensional alasan utama konsumen memilihnya. Seiring meningkatnya minat konsumen, perusahaan besar banyak memproduksi dengan berbagai spesifikasi seperti kapasitas baterainya juga jarak tempuhnya. Hal tersebut membuat diberikan dalam memilih s...

Collaborative filtering (CF) systems have been proven to be very effective for personalized and accurate recommendations. These systems are based on the Recommendations of previous ratings by various users and products. Since the present database is very sparse, the missing values are considered first and based on that, a complete prediction dataset are made. In this paper, some standard comput...

Nowadays, most of e-learning systems embody online discussion forums as a medium for collaborative learning that supports knowledge sharing and information exchanging between learners. The exponential growth of the available shared information in e-learning online discussion forums has caused a difficulty for learners in discovering interesting information. This paper introduces a novel recomme...

A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering). Recommender systems have been a useful tool to recomm...

This paper provides an overview of SANDS (Specialized Active Networking for Distributed Simulation), a DARPA-ITO sponsored research project that is using active networking to develop a new approach to real-time, content-based information dissemination. Our approach is based on the use of active interest filtering, a publish/subscribe mechanism that uses active networks technology to install and...

Future network environments will be pervasive and distributed over a multitude of devices that are dynamically networked. The data collected by pervasive devices (e.g. traffic data, CO2 values) provide important information for applications that use such contexts actively. Future applications of this type will form a grid over the Internet to offer various services and such a grid requires more...