Message Classification and Filtering

This document is a proposal of how to implement classification and filtering of messages in the computer conference system kom. The kom system consists of two basic components, a client and a server. The client is the user interface through which the user exchanges messages with the server and updates personal information. The server acts as a central repository and database for both messages and information about users. In addition to its communication with the clients, the server also exchanges information with other servers. These other servers may be other kom servers or servers for Usenet News or electronic mail. From the user's point of view, the kom system collects messages from several sources (kom, Usenet News, mailing lists and email) and presents them in a coherent form. The kom client enables the user to process messages from or to these sources through a single interface. 2 Messages Sequenced by Multiple Source

Message Classification and Filtering

This document is a proposal of how to implement classification and filtering of messages in the computer conference system kom. The kom system consists of two basic components, a client and a server. The client is the user interface through which the user exchanges messages with the server and updates personal information. The server acts as a central repository and database for both messages and information about users. In addition to its communication with the clients, the server also exchanges information with other servers. These other servers may be other kom servers or servers for Usenet News or electronic mail. From the user's point of view, the kom system collects messages from several sources (kom, Usenet News, mailing lists and email) and presents them in a coherent form. The kom client enables the user to process messages from or to these sources through a single interface. 2 Messages Sequenced by Multiple Source

Comparisons of the Cosine Measure and Sub-String Indexing on Usenet News Articles

Two document similarity measures are compared on a sample of Usenet News messages. 1 Introduction In order to estimate the similarity between a query and a collection of documents in a database, a number of measures has been applied and tried in the area of information retrieval. For the purpose of a filtering application, these devices appear to be good starting points in the selection of one of more measures that are to provide a numerical distance between unread messages and a set of long-term queries established by the user. This paper describes a set of evaluations applied to two such similarity measures, the cosine measure and sub-string indexing. 2 The Cosine Measure The cosine measure [SM83] has received its name from a trigonometrical analogy: the angle between two vectors in N-dimensional space is always measurable across a 2-D plane. When the vectors point in the same direction the angle between them is OE = 0. When they are perpendicular to each other the angle between t..

A Brief Comparison of News Filtering Software

length and report interval. Two further parameters are available to the user; the interval in days between reports and the number of lines to be abstracted from each article. 3.3 Operation and Implementation sift operates at a remote site, out of the user's control and sends abstracts of the retrieved articles to they user by email. It is implemented in C and has been compiled on several Unix platforms (DEC Ultrix 4.2, HPUX 8.07 and SunOS 4.1). 3.4 Results Results available so far appears to deal primarily with the economy and efficiency of the filtering engine itself. 4 NewsWeeder NewsWeeder [Lan94, Lan95b] is a system in experimental use at Carnegie Mellon University. A special www-browser serves as user interface. The user visits each newsgroup of interest in turn. For each group, the user rates interesting articles using a number in the range 1--5. The system collects the rating information and presents the overall rating averaged across all other NewsWeeder users. As such ..

Intelligent Filtering; Based on Keywords Only?

Empirical studies on users of Usenet News indicate that features other than keywords also plays an important role in the user's decision to read or reject a message. The IntFilter project aims to develop a message classification mechanism which use such extra features while minimizing the burden for the user who has to provide and maintain long-term queries. KEYWORDS: Text classification, information filtering, computer-mediated communication, machine learning. INTRODUCTION Keywords and phrases are in common use in information filtering ([4, 5, 10]), but other criteria could be usable, especially in combination with machine learning techniques. By studying how users of Usenet News select and rate information, we have searched for additional filtering criteria. The term filtering here include the concept of selection, as well as rejection. USER STUDIES In a first pilot study [2] the aim was to investigate how experienced users of Usenet News selected their information and how they..

Security Issues in an Active Documents Application based on Java and Jini

The Jima infrastructure for active documents is built as a system of mobile agents based on Java and Jini. Using a meeting scenario application as catalyst, a set of selected security issues are identified. The Extended Java Security Platform is briefly displayed and design solutions for three security issues (mobility servers, Jini service objects and enforcing distributed routing decisions) are discussed in detail. 1 Introduction Instant access to resources and generous connectivity across any form of natural barrier appears to be crucial properties in the concept of ubiquitous computing. However, such unlimited freedom was never practical even in the days when there were only human users in the computer networks. Today, access and connectivity is still needed by users, but the humans are now in the company of electronic counterparts. Popularly known as agents, these software robots perform serious tasks and make sensitive decisions. No more than we want to see the mechanized..

Intelligent Information Filtering

this document contains a number of screenshots from the pefn

PEFNA - The Private Filtering News Agent

This document describes the pefna system. 1.1 Overvie