Zhili Wu (2005) Towards A Community of Machine Learners Through Learning Online Communities of Practice

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Towards A Community of Machine Learners Through Learning Online Communities of Practice

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CONTRIBUTORS:

Author:

Zhili Wu

PROCEEDINGS TITLE:

Proceedings of the First HKBU-CSD Postgraduate Research Symposium (2005) Xiaolong Jin, ; Jianliang Xu, . Hong Kong: Hong Kong Baptist University.

YEAR:

2005

PUB TYPE:

Conference Paper in Proceedings

PAGES:

2 - 8

SUBJECT(S):

machine learners, interactive networks, online communities, Communities of Practice

DISCIPLINE:

No discipline assigned

HTTP:

http://www.comp.hkbu.edu.hk/~pgday/history/05-1/proceedings_2005_jan.pdf

LANGUAGE:

None

PUB ID:

103-412-119 (Last edited on 2005/01/26 05:17:10 US/Mountain)

SPONSOR(S):

ABSTRACT:
Tasks in the context of learning interaction networks, like the study of information dynamics of the WWW, Email communication and online communities, or the study of how to improve them, pose challenges to machine learning. To handle such tasks, we intend to propose a community of machine learners (CoL), which is an ensemble of machine learners interconnected through proper interactions. Our research is conducted with two reciprocal modes: 1) Proposing machine learning models to online communities, to get better insights from the collective practices of community participants; 2) Through the learning of community effects as in 1), to propose a community of machine learners, which by interconnecting machine learners through a much social way, can then be used to fulfill the tasks that originate from relational and interactive networks. And we conducted preparatory studies on data gathered from Chinese Bulletin Board Systems and an online algorithm competition platform, to show the feasibility of further exploring the topics of learning community data and constructing a community of machine learners.

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