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Agent software is a rapidly developing area of research. However, the overuse of the word ‘agent ’ has tended to mask the fact that, in reality, there is a truly heterogeneous body of research being carried out under this banner. This overview paper presents a typology of agents. Next, it places agents in context, defines them and then goes on, inter alia, to overview critically the rationales, hypotheses, goals, challenges and state-of-the-art demonstrators of the various agent types in our typology. Hence, it attempts to make explicit much of what is usually implicit in the agents literature. It also proceeds to overview some other general issues which pertain to all the types of agents in the typology. This paper largely reviews software agents, and it also contains some strong opinions that are not necessarily widely accepted by the agent community. 1 1

design of data mining in telecom SM is established. In response to the difficulty of possible time for prediction of high sales, this study applies data mining techniques to build a model for prediction.

patterns of interest. In this paper, we propose the use of Regular Expressions (REs) as a flexible constraint specification tool that enables user-controlled focus to be incorporated into the pattern mining process. We develop a family of novel algorithms (termed SPIRIT – Sequential Pattern mIning

The Group was set up in January 2007 as an ad hoc committee to: • review current global plans for space exploration; • assess what opportunities and benefits exist for UK participation; and • provide advice to BNSC and partners as to which areas the UK should focus on if it wishes to engage

Recommender systems are being used by an ever-increasing number of E-commerce sites to help consumers find products to purchase. What started as a novelty has turned into a serious business tool. Recommender systems use product knowledge -- either hand-coded knowledge provided by experts or "mined

over a period of four months. Our analysis explores the propensity of a subscriber to churn out of a service provider’s network depending on the number of ties (friends) that have already churned. Based on our findings, we propose a spreading activation-based technique that predicts potential churners

evaluation, this study compares various data mining techniques that can assign a “propensity-to-churn ” score periodically to each and every subscribers of a mobile operator. The results indicate that both decision tree and neural network techniques can deliver accurate churn prediction models by using

from extensive study of realworld human connectivity traces. We exploit distributed community detection from the trace and propose a Socio-Aware Overlay over detected communities for publish/subscribe communication. Centrality nodes have the best visibility to the other nodes in the network. We create

Questions pertaining to home terminals in the cable environment are examined. The functions of subscriber wined television receivers in this new setting are examined and the details of set-top converters are closely scrutinized. Also explored are augmented one-way and two-way services which