TY - GEN
T1 - Visualizing potential communities
T2 - 1998 International Conference on Multi Agent Systems, ICMAS 1998
AU - Yoshida, Sen
AU - Kamei, Koji
AU - Yokoo, Makoto
AU - Ohguro, Takeshi
AU - Funakoshi, Kaname
AU - Hattori, Fumio
N1 - Publisher Copyright:
© 1998 IEEE.
PY - 1998
Y1 - 1998
N2 - The generic term communityware (M. Chalmers and P. Chitson, 1992) has been proposed to represent systems that typically support the formation, activities, and organization of informal groups on open networks such as the Internet or mobile computing systems. Communityware is intended to provide support for a diverse and amorphous group of people who do not yet have a clearly defined goal. We explain the development of an example communityware system that graphically presents a potential community, i.e., people sharing common interests. The proposed system determines the degree of common interests for each pair of people, and it then locates the users in a plane where the distance between the users reflects the relevance between them. A major challenge for implementing this system is distinguishing an appropriate set of keywords to visualize potential communities. The system extracts keywords from the users' profiles and calculates the degree of relevance among the users using those keywords. We use a weight system for keywords as well as a learning mechanism that determines the desired weight from user feedback. It is shown that agents can speed up this learning process by cooperation.
AB - The generic term communityware (M. Chalmers and P. Chitson, 1992) has been proposed to represent systems that typically support the formation, activities, and organization of informal groups on open networks such as the Internet or mobile computing systems. Communityware is intended to provide support for a diverse and amorphous group of people who do not yet have a clearly defined goal. We explain the development of an example communityware system that graphically presents a potential community, i.e., people sharing common interests. The proposed system determines the degree of common interests for each pair of people, and it then locates the users in a plane where the distance between the users reflects the relevance between them. A major challenge for implementing this system is distinguishing an appropriate set of keywords to visualize potential communities. The system extracts keywords from the users' profiles and calculates the degree of relevance among the users using those keywords. We use a weight system for keywords as well as a learning mechanism that determines the desired weight from user feedback. It is shown that agents can speed up this learning process by cooperation.
UR - http://www.scopus.com/inward/record.url?scp=84956980660&partnerID=8YFLogxK
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U2 - 10.1109/ICMAS.1998.699294
DO - 10.1109/ICMAS.1998.699294
M3 - Conference contribution
AN - SCOPUS:84956980660
SN - 081868500X
SN - 9780818685002
T3 - Proceedings - International Conference on Multi Agent Systems, ICMAS 1998
SP - 477
EP - 478
BT - Proceedings - International Conference on Multi Agent Systems, ICMAS 1998
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 July 1998 through 7 July 1998
ER -