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------====== Call for Papers ======----- ACM Transactions on Intelligent
Systems and Technology Special Issue on Crowd in Intelligent Systems = AIMS
AND SCOPE = Crowdsourcing, i.e., outsourcing tasks to an indefinite crowd,
has now become a common strategy to resolve problems that are difficult to
computers. It has proven the intelligence, wisdom, or judgments from the
crowd, when appropriately combined, can be effective in addressing
challenges in various areas, from knowledge organization (such as
Wikipedia), business investment, policy making, government transparency to
scientific development. In particular, the contributions from the crowd are
stretching out the horizon of intelligent systems by filling the gap
between artificial intelligence and human intelligence with the wisdom of
crowd. Successful applications can readily been seen in the fields of
computer-human interaction, computer vision, information retrieval, social
computing, biomedical research (such as Foldit), and information and
multimedia systems. The uses in crowdsourcing have opened up many new forms
of intelligent systems and technologies most of which have barely been
explored to date. However, challenging research questions still lie in the
way to unleash the potentials of the crowd as a part of intelligent
systems. This special issue aims to address these challenges in the hope of
overcoming the obstacles blocking the road toward intelligent systems where
artificial- and human-intelligence perfectly harmonize. The dimensions
listed below indicate the range of work that is relevant to the special
issue. Each article is expected to make a significant scientific
contribution along one or more of these dimensions. In case of doubt about
the relevance of your topic, please contact the special issue guest
editors. = TOPIC DIMENSIONS = - General: Theoretical, experimental, and/or
methodological developments advancing state-of-the-art knowledge of
crowdsourcing for intelligent systems - Novel applications: Novel uses of
contributions from the crowd for intelligent systems (e.g., complicated
tasks rather than simple judgment or labeling tasks) - Evaluation:
Evaluation of the design and quality of intelligent systems by the crowd -
Machine learning: Effective learning and information aggregation from noisy
crowd inputs; quality assurance and cheat detection for the crowd
contributions - Human factors: Effective interfaces and workflow for the
task workers, especially for complicated, compound tasks - Infrastructure:
Programming languages, tools and platforms providing enhanced support for
crowdsourcing; security, privacy, trust, and reputation management in
crowdsourcing for intelligent systems - Economics and incentives: Enable
effective and efficient crowd contributions that traditionally would only
be possible by expensive domain experts - Ethics: Theory, design, or
mechanisms that address ethical issues in adopting crowd’s efforts in
intelligent systems. Possible ethical issues include education, labor
exploitation, crowd awareness (of the tasks they perform), and alienation.
- Inherent biases, limitations and trade-offs of combining crowd
intelligence and artificial intelligence = SCHEDULE = Submission due: 10
February 2015 (firm) First review completed: 17 April 2015 Final manuscript
due: 19 June 2015 Publication: September 2015 = HOW TO SUBMIT = Please see
the special issue CfP website http://www.iis.sinica.edu.tw/~swc/tist_crowd/
The papers will be evaluated for their originality, contribution
significance, soundness, clarity, and overall quality. The interest of
contributions will be assessed in terms of technical and scientific
findings, contribution to the knowledge and understanding of the problem,
methodological advancements, and/or applicative values. = GUEST EDITORS =
Irwin King, The Chinese University of Hong Kong, Hong Kong Kuan-Ta Chen,
Academia Sinica, Taiwan Omar Alonso, Microsoft, United States Martha
Larson, Delft University of Technology, Netherlands = CONTACT US = For
questions or more information, please contact the guest editors Irwin King (
[email protected]), Kuan-Ta Chen ([email protected]), Omar Alonso (
[email protected]), and Martha Larson ([email protected]).

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