James Salter

CinemaScreen recommender agent: combining collaborative and content-based filtering

A film recommender agent expands and fine-tunes collaborative-filtering results according to filtered content elements - namely, actors, directors, and genres. This approach supports recommendations for newly released, previously unrated titles. Directing users to relevant content is increasingly important in todays society with its ever-growing information mass. To this end, recommender systems have become a significant component of e-commerce systems and an interesting application domain for intelligent agent technology.

An optimized two-tier P2P architecture for contextualized keyword searches

We describe a two-tiered P2P network for efficient lookup of contextualized data, utilizing an alternative strategy for building the network overlay designed to reduce the hops required to route lookups and improve fault tolerance by allowing the selection of nodes to build subrings. We show how the method is used to support context-keyword queries. Our calculations indicate that the technique yields improvements in the average query hop count while reducing the amount of state stored on each node. The use of Preference Lists can further reduce the average hop count through bypassing previously traversed segments of the structures

Efficient resource discovery in grids and P2P networks

Presents a new model for resource discovery in grids and peer‐to‐peer networks designed to utilise efficiently small numbers of messages for query processing and building of the network. Outlines and evaluates the model through a theoretical comparison with other resource discovery systems and a mathematical analysis of the number of messages utilised in contrast with Chord, a distributed hash table. Shows that through careful setting of parameter values the model is able to provide responses to queries and node addition in fewer messages than Chord. The model is shown to have significant benefits over other peer‐to‐peer networks reviewed. Uses a case study to show the applicability of the model as a methodology for building resource discovery systems in peer‐to‐peer networks using different underlying structures. Shows a promising new method of creating a resource discovery system by building a timeline structure on demand, which will be of interest to both researchers and system implementers in the fields of grid computing, peer‐to‐peer networks and distributed resource discovery in general.