Advances in Web Intelligence and Data Mining

2006 ◽  
Keyword(s):  
Data Mining ◽  
Web Intelligence

Web Intelligence and Data Mining in Urban Areas

2019 ◽  
pp. 27-47 ◽  
Author(s):  
Anandakumar Haldorai ◽  
Arulmurugan Ramu ◽  
Suriya Murugan
Keyword(s):  
Data Mining ◽  
Urban Areas ◽  
Web Intelligence

Scientific Web Intelligence

2011 ◽  
pp. 995-999
Author(s):  
Mike Thelwall
Keyword(s):  
Data Mining ◽  
End Users ◽  
Research Field ◽  
Data Sources ◽  
Web Pages ◽  
Web Intelligence ◽  
Research Fields ◽  
Patterns Of Communication ◽  
The Impact ◽  
Citation Databases

Scientific Web Intelligence (SWI) is a research field that combines techniques from data mining, Web intelligence, and scientometrics to extract useful information from the links and text of academic-related Web pages using various clustering, visualization, and counting techniques. Its origins lie in previous scientometric research into mining off-line academic data sources such as journal citation databases. Typical scientometric objectives are either evaluative (assessing the impact of research) or relational (identifying patterns of communication within and among research fields). From scientometrics, SWI also inherits a need to validate its methods and results so that the methods can be justified to end users, and the causes of the results can be found and explained.

Data mining for Web intelligence

Computer ◽  
2002 ◽  
Vol 35 (11) ◽  
pp. 64-70 ◽  
Author(s):  
Jiawei Han ◽  
K.C.-C. Chang
Keyword(s):  
Data Mining ◽  
Web Intelligence

IMPENDING BRAIN INFORMATICS RESEARCH FROM WEB INTELLIGENCE PERSPECTIVE

2006 ◽  
Vol 05 (04) ◽  
pp. 713-727 ◽  
Author(s):  
NING ZHONG
Keyword(s):  
Data Mining ◽  
Research And Development ◽  
High Impact ◽  
Human Intelligence ◽  
Research Issues ◽  
Web Intelligence ◽  
Brain Sciences ◽  
Intelligence Models ◽  
Multi Agent

Web Intelligence (WI)-based portal techniques (e.g. the wisdom Web, data mining, multi-agent, and data/knowledge grids) will provide a new powerful platform for Brain Sciences. New understanding and discovery of the human intelligence models in Brain Sciences (e.g. cognitive science, neuroscience, brain informatics) will yield new WI research and development. In this paper, we briefly investigate three high-impact research issues as well as present a case study, to demonstrate the potentials of Brain Informatics (BI) research from WI perspective.

Scientific Web Intelligence

2011 ◽  
pp. 1714-1719
Author(s):  
Mike Thelwall
Keyword(s):  
Data Mining ◽  
Research Field ◽  
Data Sources ◽  
Web Pages ◽  
Web Intelligence ◽  
Research Fields ◽  
Web Science ◽  
Patterns Of Communication ◽  
The Impact ◽  
Citation Databases

Scientific Web Intelligence (SWI) is a research field that combines techniques from data mining, web intelligence and scientometrics to extract useful information from the links and text of academic-related web pages, using various clustering, visualization and counting techniques. Its origins lie in previous scientometric research into mining offline academic data sources such as journal citation databases, in contrast to Web Science, which focuses on engineering an effective Web (Berners-Lee et al., 2006). Typical scientometric objectives are either evaluative: assessing the impact of research; or relational: identifying patterns of communication within and between research fields. From scientometrics, SWI also inherits a need to validate its methods and results so that the methods can be justified to end-users and the causes of the results can be found and explained.

Opening Address

2017 ◽  
Vol 21 (1) ◽  
pp. 8-8
Author(s):  
Editor: Prof. Yasufumi Takama ◽  
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Computational Intelligence ◽  
Smart Grids ◽  
Fuzzy Inference ◽  
Peer Review Process ◽  
Web Intelligence ◽  
The Past ◽  
Research Areas ◽  
Institute Of Technology

The JACIII was first published in 1997, and 2017 marks its 20th anniversary. During the last two decades, the research fields in computational intelligence have rapidly evolved owing to the spread of the Internet, performance improvement of computers, and accumulation of scientific knowledge. To celebrate this 20th anniversary, we have selected 6 important research areas from the JACIII scope, and invited outstanding researchers from each of these areas to contribute papers about the progress and major topics in those areas during the past 20 years. Submitted paper went through a peer-review process by distinguished professors to further improve the quality. The research areas selected were computational intelligence, fuzzy intelligence, intelligent robots, artificial intelligence and web intelligence, data mining, and smart grids. Each of those paper covers broad topics appeared in the research areas, from which readers could grasp what happened during the past 20 years. We also hope readers could find some hints about future directions of their own researches towards the next 20 years. <strong>Invited Paper 1: Computational Intelligence: Retrospection and Future</strong> Author: Witold Pedrycz (University of Alberta, Canada) <strong>Invited Paper 2: Fuzzy Inference: Its Past and Prospects</strong> Authors: Kiyohiko Uehara (Ibaraki University, Japan) and Kaoru Hirota (Beijing Institute of Technology, China) <strong>Invited Paper 3: Relationship Between Human and Robot in Nonverbal Communication</strong> Authors: Yukiko Nakagawa and Noriaki Nakagawa (RT Corporation, Japan) <strong>Invited Paper 4: Web Intelligence and Artificial Intelligence</strong> Author: Yasufumi Takama (Tokyo Metropolitan University, Japan) <strong>Invited Paper 5: A Review of Data Mining Techniques and Applications</strong> Authors: Ratchakoon Pruengkarn, Kok Wai Wong, and Chun Che Fung (Murdoch University, Australia) <strong>Invited Paper 6: Development and Current State of Smart Grids: A Review</strong> Author: Ken Nagasaka (Tokyo University of Agriculture and Technology, Japan)

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