Abstract
We present a service-oriented scripting language for programming mobile agents in distributed systems. The main novelty of the language we call MOB, is the integration of the service-oriented and mobile agent paradigms. MOB is also encoded onto a process calculus with a well studied semantics. The encoding provides a specification for the front-end of the language compiler and allows us to use, for the back-end and for the run-time system, a compiler and a virtual machine previously developed for the process calculus.

Abstract
Clusterings based on many variables are difficult to visualize and interpret. We present a methodology based on Factor Analysis (FA) which can be used for that purpose. FA generates a small set of variables which encode most of the information in the original variables. We apply the methodology to segment the users of a web portal, using access log data. It not only makes it simpler to visualize and understand the clusters which are obtained on the original variables but it also helps the analyst in selecting some of the original variables for further analysis of those clusters.

Abstract

Abstract
In this paper we present MOB, a service-oriented scripting language for programming mobile agents in distributed systems. The main feature of the language is the integration of the service-oriented and the mobile agent paradigms. MOB is encoded onto a process calculus with a well studied semantics which provides us with a tool to prove the soundness of the language relative to the underlying calculus. Copyright 2006 ACM.

Abstract
We present a methodology for the personalization of e-newsletters based on the analysis of user access logs. To approach the problem we have used clustering on the set of users, described by their web access patterns. Our work is evaluated using a case study with real data from e-newsletters sent by mail to users of a web portal, and can be adapted to similar situations. Positive results were obtained, indicating that the methodology is able to automatically select contents for a personalized e-newsletter.

Abstract