Harumi Maeda

CoMeMo-Community: A System for Supporting Community Knowledge Evolution

CoMeMo-Community is a system that is designed to support knowledge evolution in a community. It is based on two ideas. One is associative representation for facilitating externalization of both personal and community knowledge. The other is visualization of knowledge interaction based on the talking-alter-egos metaphor. In this paper, we present how these ideas are incorporated into the CoMeMo-Community system and report preliminary experimentation with it. We also discuss how CoMeMo-Community helps us to understand community.

CoMeMo: constructing and sharing everyday memory

This paper describes the CoMeMo project which aims to develop systems which articulate, organize and utilize everyday memory in a group or in a community. The basic hypothesis is that connecting information without defining the semantics using the weak information structures is effective to deal with a large amount of diverse information. The CoMeMo architecture consists of: CoMeMo Workbench, CoMeMo Incorporator, CoMeMo Mobile Terminal, CoMeMo Server, CoMeMo Protocol and CoMeMo Agent. We have implemented the CoMeMo Workbench, the CoMeMo Incorporator and a prototype of the CoMeMo Mobile Terminal. We have developed applications based on the CoMeMo architecture: information gathering and reorganization from WWW pages; ontology development; education support; and conference support.

Constructing Information Bases Using Associative Structures

We present an approach based on knowledge medium using associative structures as a framework of information representation to gather raw information from heterogeneous information sources and to integrate it into information bases cost-effectively.We then present a knowledge media information base system called CM-2 which provides users with a means of accumulating, sharing, exploring and refining conceptually diverse information gathered from vast information sources. We describe the systems four major facilities; (a) an information capture facility, (b) an information integration facility, (c) an information retrieval facility and (d) an information refinement facility. We discuss the strength and weakness of our approach by analyzing results of experiments.

The knowledgeable community-facilitating the knowledge process by humans and computers

The long-term goal of the Knowledgeable Community project is to develop a computational framework for facilitating the knowledge process by humans and computers. We model the knowledgeable community as an open system of natural and artificial agents interacting in knowledgeable environments where real or virtual entities are associated with conceptualization. First, we study associative representation based on information representation with variable degrees of formality which permits raw information materials to be incrementally formalized into a well-defined system of knowledge and even incomplete knowledge pieces to be accessed and utilized by humans and computers. Second, we present the aspect theory for describing the world from multiple perspectives and its application to ontology-based intelligent document base system for human knowledge sharing. Third, we describe a computational framework using agent development, ontology-grounding, and ontology-based mediation. We have implemented several complete prototypes which can demonstrate the significance of our idea. Experimental evaluation is in progress.