Call for Papers Elsevier Applied Soft Computing (SCI IF=2.81) Special Issue on Crow d Computing for Social Media Ecosystem http://www.journals.elsevier.com/applied-soft-computing/call-for-papers/special-issue-on-crowd-computing-for-social-media-ecosystem Aims and Scopes Recent decade has witnessed the birth of social media ecosystem that brings social organization s , media content and various stakeholders together , and now it appear s significant advantages of comprehensiveness, diversity and wi s do m that provide users with high er quality of experiences. With the explosive increase of social users , as well as the popularity of pervasive (mobile) social media tools and services, more and more u sers are much addicted to share personal feeling, sentiment , idea and experi ence to a wider range of friends , even friends of friends , by using video, images and photos , etc . Meanwhile, social media ecosystem suffers from security , privacy and trustworthiness threats. How to leverage the power of bottom-top crowd to improve the ecosystem ’ s efficacy and efficiency, as well as ensure its security and privacy become burning and challenging. This special issue seeks to publish high-quality original research articles , with a particular emphasis on advanced crowd computing and crowd intelligence methodologies applicable for real-world social media, and encourages more practical and validated techniques, not focused on pure concept ual model, framework and building blocks descriptions. Topics of interests include below , but are not limited to: Social media network architecture, model and new paradigm by using crowd computing Crowd computing and crowd intelligence methodologies for social media recommendation and sentimental analysis Social media content security, v ulnerability and forensics based on crowd intelligence and soft computing Crowd computing-enabling spatial-temporal access control, usage control and digital rights management for both online and offline social media Crowdsourcing-employed security and trustworthiness evaluation and measure of social media services, tools and systems The performance metrics and benchmarks studies on crowd computing for social media R isk management and assessment, as well as social-factor considerations in social media ecosystem by using soft computing Ubiquitous, p ersonal and mobile social media applications based on crowd intelligence Social media prototypes and empirical studies together with crowdsourcing Instructions for submission All submitted papers must be clearly written in excellent English and contain only original work and cutting-edges survey , which has not been published by or is currently under review for any other journal or conference. Leading guest editor would prescreen and make an initial determination on the suitability and scope of all submissions , only considering soft computing related and real-world application paper s in the topic domain. If suitable, the submission would be assigned to at least three international reviewers; if not, the guest editor would notify authors to resubmit elsewhere. Papers must be submitted through the Applied Soft Computing website at http://ees.elsevier.com/asoc , where guidelines for the manuscript preparation can also be found (see http://www.journals.elsevier.com/applied-soft-computing/ ). To ensure that all manuscripts are correctly identified for consideration by the Special Issue, the authors should select Special Issue: Crowd Social Media when they reach the “Article Type” step in the submission process. For further information, please contact the leading guest editor at zzy@iastate.edu. Important dates · Full paper submission deadline: July 31 , 201 6 · First author notification: October 31 , 201 6 · Revised paper due: December 31 , 201 6 · Final author notification: March 1 , 201 7 · Expected publication: the second quarter of 201 7 Guest e ditors Dr. Zhiyong Zhang Henan Province Distinguished Professor, Henan University of Science Technology, P. R. of China ; Visiting Prof essor, Department of Computer Science, Iowa State University, USA E-mail: zzy@iastate.edu , xidianzzy@126.com Homepage: www.sigdrm.org/~zzhang Dr. Kim-Kwang Raymond Choo Fulbright Scholar and Associate Professor, University of South Australia, Australia E-mail: raymond.choo@fulbrightmail.org Dr. Arun Kumar Sangaiah Professor, VIT University, India E-mail: arunkumarsangaiah@gmail.com Dr. Liang Chen University of West London , United Kingdom E-mail: liang.chen@uwl.ac.uk
Neural Network World ( ScienceCitation Index Expanded Journal) http://www.nnw.cz/ Callfor Papers –Special Issue on Applied Soft Computing for Online Social Networks Social media are computer-mediated tools that allow people to create,share or exchange information, ideas, pictures, audios or videos in virtualcommunities by using open Internet. Over the past five years, online socialnetwork (OSN) websites or services have been widely developed and deployed,including general-purpose OSNs like Twitter, Facebook and Wechat, orspecial-purpose ones for multimedia sharing YouTube, professional communicationLinkedIn, and so on. Whatever the type of an OSN is, there exist veryinteresting and challengeable research works on how to improve an efficientsocial media computing and how to make an effective social network analysis andmining from the perspectives of both academia and industry. In order to bettercope with the burning issues, advances on soft computing technologies, such asneural network and system, evolutionary computing and genetic algorithms, fuzzyset and rough set theories, probabilistic computing, as well as chaos theoryand chaotic systems, are paving a road to more valuable and feasible solutionsto the emerging social media and big data, finally bringing a brilliant futureof wisdom and intelligent social media network. This special issue aimsto solicit the cutting edge research contributions of applied soft computing onsocial media and online networks. We specially invite authors to submit high quality,original papers that must not be under consideration for publication in anyother journal or conference, and meanwhilesome all-around and readable survey papers about the state-of-the art of softcomputing in social network applications are also welcomed. Research Thepossible main topics are listed as follows, but not limited to. ² Artificial/natural neural network and neural systemapplied to social media and online social network establishment ² Fuzzy set and rough set theories in social mediapropagation and redistribution ² Chaos theory and chaotic systems for social media content security ² Deep learning and machine learning for multimedia recommendationsystems and algorithms ² Soft computing technologies for both quantitative and qualitativetrust assessment and risk management in online social networks ² Soft computing enabling (mobile) multimedia socialnetwork prototypes, empirical cases studies and other applications Submissions Guideline All potential authors would sendtheir papers both Word and PDF files to the leading and corresponding guesteditor Prof. Zhiyong Zhang by xidianzzy@126.com .And, please make sure you clearly write the thematic issue title “ SpecialIssue on Applied Soft Computing for Online Social Networks ” in the coverletter for our conveniences on checking submitted manuscripts. Besides, if you still have any question, please do nothesitate to contact Prof. ZhiyongZhang by xidianzzy@126.com Prof. Arun Kumar Sangaiah by arunkumarsangaiah@gmail.com Important Dates Papersubmission: April 15, 2016 1st round of reviewnotification: July 15, 2016 Revision submissiondue: September 15, 2016 Finalacceptance: November 15, 2016 Publication(Tentative): The first issue of 2017 Guest Editors Zhiyong Zhang (Leading andCorresponding GE) Visiting Professor, Iowa State University,Ames, USA;Henan ProvinceDistinguished Professor, Henan University of Science Technology, Luoyang, China E-mail: xidianzzy@126.com Homepage: www.sigdrm.org/~zzhang ArunKumar Sangaiah Professor,VIT University,Vellore, India E-mail: arunkumarsangaiah@gmail.com Homepage: https://in.linkedin.com/pub/dr-arun-kumar-sangaiah/a9/452/81
硬计算与软计算这两个术语首先由美国加州大学的 Zadeh 教授于 20 世纪 90 年代提出。 硬计算的主要特征：（ 1 ）易于建立问题的规范数学模型；（ 2 ）建立的数学模型易于求解，且能达到较高的精确度；（ 3 ）解具有较好的稳定性。 软计算的主要特征：（ 1 ）难于建立问题的规范数学模型；（ 2 ）难于得到问题的较高精度的解；（ 3 ）算法具有较好的适应性，能够适应动态环境。软计算中的核心方法主要包括模糊逻辑（ Fuzzy Logic ， FL ）、神经网络（ Neural Networks ， NN ）和遗传算法（ Genetic Algorithms ， GA ）以及这几种方法之间的不同组合形式。 混合计算是传统的硬计算与新兴的软计算的组合，混合计算可以获取各自所长，克服各自局限性。 一个合适的面向问题求解的计算策略的选择取决于问题的属性。 Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. （ http://www.soft-computing.de/def.html ） 参考文献： 1. Zadeh, Lotfi A., Fuzzy Logic, Neural Networks, and Soft Computing, Communications of the ACM, March 1994, 37 （ 3 ）： 77-84 2. D. K. Pratihar. Soft Computing, Narosa Publishing House, 2008( 王攀 等译. 软计算，科学出版社 , 2009) 3. Ovaska S. J., VanLandingham H. F., Kamiya A.. Fusion of soft computing and hard computing in industrial applications: an overview. IEEE Transactions on Systems, Man and Cybernetics. Part C, Applications and reviews, 2002,32(2):72-79
标签: 软计算
