Information Technology Reference
In-Depth Information
Discovering Proximal Social Intelligence
for Quality Decision Support
Yuan-Chu Hwang
*
Abstract.
The concepts of proximity have been utilized for exploring both psy-
chological and geographical incentives for users within social networks to collabo-
rate with others for mutual goals. The massive information does not facilitate
quality decision support. In this chapter, we focus on discovering the proximal so-
cial intelligence for quality decision support. The utilization of investigating both
the context and the content of the application domain from social network rela-
tionships would highly improve the information quality for better decisions.
Discovering proximal social intelligence from user's personal context they en-
countered enable the improvement of decision-making quality. We illustrate a
case of leisure recommendatory e-service for bicycle exercise entertainment in
Taiwan. We introduce the proximity e-service as well as its theoretical support.
The most recent personalized experience according to its context provides remark-
able perceptual data from unique information sources. Moreover, the social net-
work relationships extend the power of the unique perceptual information to
converge as the collective social network intelligence.
1 Introduction
The debate of “Content is King” least for a long time. But the content in leisure
entertainment industry is still weak. The leisure entertainment content is usually
monopolized by business owners, available information are bundled with market-
ing strategy that lay particular stress on specific commercial firm. Sometimes the
quality of obtainable leisure entertainment information is insufficient for user to
make equitable decisions. In order to improve the decision quality, appropriate
reference materials should be provided for user to make fair judgments.
In order to improve the quality of content, possible solution including broaden
the reference information from various feasible sources; retrieve from both homo-
geneous and heterogeneous information sources; gather information from user's
social network relationships instead of the traditional sources. By focus on user's
