Intelligent Filtering of Computer-Mediated Human Communication

1. GOAL

Develop methods to aid users of asynchrounous group communication systems (e.g. email, mailing lists, conference systems, Usenet News) to select important messages.

2. MOTIVATION

Group communication systems are spreading increasingly fast as they become part of the infrastructure in educational, commercial and governmental organizations. The systems provide effective means for fast coordination, dissemination and retrieval of information. As with all new media they have specific advantages, but with increased popularity a number of disadvantages, such as information overload and a low ratio of quality to quantity also appears.

3. METHOD

The KOM group conference 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. In the process of reading a stream of messages, the user classifies some of them as highly interesting and some as rubbish. The classification is individual to each user and develops over time. Each message has a number of absolute or inferred properties such as subject, length, sender, keywords, conference etc. By solicitating the user's explicit classification of typical messages, it is hypothesized that machine learning techniques can be employed to perform automatic classification of messages, using the absolute and inferred properties of the messages.

4. EXPECTED RESULTS

Particular classes of messages are more easily identifiable than others. The presence of important keywords, for instance, is a significant factor in the determination of a message's class. The automatic classification accuracy is highly dependent on the machine learning technique employed, the set of training examples given by the user and the concept or class these training examples represent to the user.

5. APPLICATIONS

An automatized message classification module, coupled to the KOM conference system. The module provide user's with a priority estimate of their unseen messages, according to their preferencs as stated through examples given to the system.