Thursday, 5 April 2018

13th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP 2018)


The 13th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP 2018) will take place in Zaragoza (Spain), on 6th and 7th September 2018. SMAP 2018 will be organized with the support of the Aragón Engineering Research Institute (Instituto de Investigación en Ingeniería de Aragón, I3A) - University of Zaragoza.

The Semantic and Social Media Adaptation and Personalization (SMAP) workshop is the evolution of the Semantic Media Adaptation and Personalization initiative, which was founded during the summer of 2006 in an effort to discuss the state of the art, recent advances and future perspectives for semantic media adaptation and personalization. However, as Social Media applications have substantially transformed the way organizations, communities, and individuals interact, we have the scopes of SMAP extended towards this new trend, seeking to bring together researchers from the social web as well as from the semantic web communities.

After twelve successful workshops starting from Athens (2006), and then London (2007), Prague (2008), San Sebastian (2009), Limassol (2010), Vigo (2011), Luxembourg (2012), Bayonne (2013), Corfu (2014), Trento (2015), Thessaloniki (2016), and Bratislava (2017), the SMAP workshop series has been consolidated as a reference event in order to discuss about the newest advances in the field.

Aim and topics

SMAP 2018 aims to address several issues of semantic and social multimedia technologies and their use in content creation, media adaptation and user profiling. Topics of interest include but are not limited to:

  • Content creation, annotation and modeling for semantic and social web
  • Computational intelligence for media adaptation and personalization
  • Semantics-driven indexing and retrieval of multimedia contents
  • User modeling and dynamic profiling
  • Ontologies and reasoning
  • Multimedia standards
  • Semantics-based recommender systems: theory and applications
  • Recommender systems for mobile users
  • Web adaptation methods and techniques
  • Hybrid social and semantic approaches to profiling, recommendation engines or adaptation systems
  • Social multimedia applications (livecasting, audio-video sharing)
  • Social multimedia tagging and multimedia content communities
  • User-generated content mechanisms
  • Privacy/Security issues in Social and Personalized Media Applications
  • Privacy preserving data mining and social networks
  • Content customization and adaptation
  • Semantic context modeling and extraction
  • Context-aware multimedia applications
  • Adaptive and personalized multimedia summaries
  • Multilingual content navigation
  • Intelligent personalized interfaces
  • Social and semantic media collaboration platforms (e.g. semantic wikis)
  • Social web economics and business
  • Social network aggregation
  • Social data analytics
  • Social data mining
  • Adaptive/Personalized conversational media


In addition, SMAP 2018 seeks special sessions proposals addressing emerging issues in all the above aspects, that will complement the regular program. If you are interested in organizing a special session, please submit a proposal including a title, abstract/motivation, and if possible a list of potential authors that could be interested in the special session. Authors will have the opportunity to present their work in short papers that will appear in the official SMAP 2018 workshop proceedings.

Important dates

  • Special session proposals: January 30, 2018
  • Special session approval: February 7, 2018
  • Paper submission deadline: April 23, 2018
  • Notification of acceptance: June 26, 2018
  • Camera-ready submission deadline: July 4, 2018
  • Registration for authors: July 10, 2018
  • Early registration: July 12, 2018
  • Late registration: September 1, 2018
  • Workshop: 6-7th September, 2018


Please, avoid registration procedures during the summer. The University of Zaragoza is expected to be closed from August 1 to August 14, 2018, and with more limited support for administrative services since mid-July until the end of August.

Submission guidelines

Each submitted paper will be refereed by at least three members of the SMAP 2018 Program Committee, based on its relevance, originality, significance, technical soundness and clarity of expression.

Submissions must be in English, and can present mature research or experimental results as well as promising work in progress. Papers must be formatted according to the IEEE 2-column conference article style, with a limit of 6 pages, including all figures, tables and references. A minimum paper length of 4 pages is also imposed.

As with all previous editions of SMAP, all accepted papers are planned to be published by IEEE in IEEE Xplore. SMAP 2018 is supported by IEEE Computational Intelligence Society (technical co-sponsorship).

For your convenience, you may use the LaTeX or MSWord templates. Papers can be submitted via EasyChair in PDF format.

Local Organizers
  • Sergio Ilarri (President)
  • Fernando Bobillo
  • Raquel Trillo


General Chairs
  • Martín López-Nores
  • Sergio Ilarri
  • Fernando Bobillo
  • Raquel Trillo


Program Committee

Adel Alti, University of Setif, Algeria
Angelos Michalas, Technological Educational Institute of Western Macedonia, Greece
Athanasios Loukopoulos, University of Thessaly, Greece
Chrisa Tsinaraki, European Union - Joint Research Center (EU - JRC)
Christos Kalloniatis, University of the Aegean, Greece
Dimitris Dranidis, CITY College, The University of Sheffield International Faculty,
Greece
Evaggelos Spyrou, National Technical University of Athens, Greece
Fernando Bobillo, University of Zaragoza, Spain
Florence Sèdes, Université Paul Sabatier Toulouse III, France
Francesco Guerra, University of Modena and Reggio Emilia, Italy
Ioanna Lykourentzou, Luxembourg Institute of Science and Technology, Luxembourg
Ioannis Karydis, Department of Informatics, Ionian University, Greece
Jan Paralic, Technical University in Kosice, Slovakia
Jaroslav Zendulka, Technical University in Brno, Czech Republic
José Pazos-Arias, University of Vigo, Spain
Kristína Machová, Technical University in Kosice, Slovakia
Laura Po, University of Modena and Reggio Emilia, Italy
Manolis Wallace, University of Peloponnese, Greece
Maria Bielikova, Slovak University of Technology in Bratislava, Slovakia
Marián Šimko, Slovak University of Technology in Bratislava, Slovakia
Martín López-Nores, University of Vigo, Spain
Michal Kompan, Slovak University of Technology in Bratislava, Slovakia
Michalis Stefanidakis, Ionian University, Greece
Nicolas Tsapatsoulis, Cyprus University of Technology, Cyprus
Panagiotis Vlamos, Ionian University, Greece
Panos Alexopoulos, Textkernel B. V., Amsterdam, The Netherlands
Petr Saloun, VSB-TU Ostrava, Czech Republic
Petros Kefalas, CITY College, The University of Sheffield International Faculty,
Greece
Philippe Roose, LIUPPA, Université de Pau et des Pays de l'Adour, France
Phivos Mylonas, Ionian University, Greece
Przemysław Kazienko, Wroclaw University of Technology, Poland
Raquel Trillo-Lado, University of Zaragoza, Spain
Sébastien Laborie, LIUPPA, Université de Pau et des Pays de l'Adour, France
Sergio Ilarri, University of Zaragoza, Spain
Stefanos Vrochidis, Information Technologies Institute, Greece
Tadeusz Morzy, Poznan University of Technology, Poland
Theodoros Kotsilieris, TEI Peloponesse, Greece
Thrasyvoulos Tsiatsos, Aristotle University of Thessaloniki, Greece
Tomas Horvath, Eötvös Loránd University
Yannick Naudet, Luxembourg Institute of Science and Technology, Luxembourg

Wednesday, 4 April 2018

Australasian Joint Conference on Artificial Intelligence (AI 2018) (Jul 1)

The Australasian Joint Conference on Artificial Intelligence is an annual conference that has dedicated to fostering research communication and collaboration among Australasian AI community since inception. The 31th Australasian Joint Conference on Artificial Intelligence will be hosted by Victoria University of Wellington, New Zealand in December 2018. The Program Committee invite prospective authors to submit original and previously unpublished research and application papers in all spectrums of Artificial Intelligence. The conference topics cover but are not limited to the following areas:
Prospective authors are invited to submit their original unpublished work to AI 2018. The topics of interest to this conference include but are not limited to the following:
  • Agent-based and multiagent systems
  • AI applications and innovations
  • Cognitive modelling and computer human interaction
  • Big data capture, representation and analytics
  • Commonsense reasoning
  • Computer vision and image processing
  • Constraint satisfaction, search and optimization
  • Data mining and knowledge discovery
  • Evolutionary computation and learning
  • Fuzzy systems and neural networks
  • Game playing and interactive entertainment
  • Intelligent education and tutoring systems
  • Knowledge acquisition and ontologies
  • Knowledge representation and reasoning
  • Machine learning and applications
  • Multidisciplinary AI
  • Natural language processing
  • Planning and scheduling, combinatorial optimisation
  • Uncertainty in AI
  • Visualisation in AI
  • Robotics
  • Game theory
  • Text mining and Web mining
  • Web/Social media mining
We encourage cross-boundary works contributing to theory and practice of AI. Novel application domains including cyber security, healthcare, IoT, social media and big data real-world applications are highly welcome. Submitted papers should not exceed 12 pages and should not be under review or submitted for publication elsewhere during the review period. All papers will be peer reviewed by at least three independent referees.
All papers accepted and presented at AI 2018 will be included in the conference proceedings published by the Springer Lecture Notes in Computer Science/Artificial Intelligence (LNCS/LNAI, pending to approval), which are typically indexed by Engineering Index (Compendex), ISI Proceedings/ISTP, and DBLP.

Tuesday, 3 April 2018

IEEE TNNLS April 2018 - Table of Contents

******************************************
Call for IEEE TNNLS Outstanding Paper Award Nomination: We are accepting the nominations for the IEEE TNNLS Outstanding Paper Award. For the current round of competition, any paper published in 2016 (Volume 27) of TNNLS is eligible for consideration. The complete nomination packet must be submitted in a single PDF file by email to the Chair of the Committee for soliciting nominations, Prof. Cesare Alippi <cesare.alippi@polimi.it> and a copy to cis-info@ieee.org. The nomination deadline is April 30, 2018 (strict deadline).
******************************************

The following articles appeared in the latest issue of IEEE Transactions on Neural Networks and Learning Systems: Volume 29, Issue 4, April 2018.

This issue published papers on adaptive control, unsupervised learning, reinforcement learning, recurrent neural network, associative memory, feature selection, among others. We welcome your submissions to IEEE TNNLS.

These articles can be retrieved on IEEE Xplore:
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5962385
or directly by clicking the individual paper URL below.

IEEE Transactions on Neural Networks and Learning Systems;
Volume 29, Issue 4, April 2018.


1. Multicolumn RBF Network
Author(s): Ammar O. Hoori; Yuichi Motai
Page(s): 766 - 778
http://ieeexplore.ieee.org/document/7828142/

2. A Regularized SNPOM for Stable Parameter Estimation of RBF-AR(X) Model
Author(s): Xiaoyong Zeng; Hui Peng; Feng Zhou
Page(s): 779 - 791
http://ieeexplore.ieee.org/document/7828032/

3. A Fast Algorithm of Convex Hull Vertices Selection for Online Classification
Author(s): Shuguang Ding; Xiangli Nie; Hong Qiao; Bo Zhang
Page(s): 792 - 806
http://ieeexplore.ieee.org/document/7828045/

4. Adaptive Antisynchronization of Multilayer Reaction–Diffusion Neural Networks
Author(s): Yanzhi Wu; Lu Liu; Jiangping Hu; Gang Feng
Page(s): 807 - 818
http://ieeexplore.ieee.org/document/7831353/

5. Synchronization for the Realization-Dependent Probabilistic Boolean Networks
Author(s): Hongwei Chen; Jinling Liang; Jianquan Lu; Jianlong Qiu
Page(s): 819 - 831
http://ieeexplore.ieee.org/document/7831482/

6. Adaptive Tracking Control for Robots With an Interneural Computing Scheme
Author(s): Feng-Sheng Tsai; Sheng-Yi Hsu; Mau-Hsiang Shih
Page(s): 832 - 844
http://ieeexplore.ieee.org/document/7831462/

7. Robust Estimation for Neural Networks With Randomly Occurring Distributed Delays and Markovian Jump Coupling
Author(s): Yong Xu; Renquan Lu; Peng Shi; Jie Tao; Shengli Xie
Page(s): 845 - 855
http://ieeexplore.ieee.org/document/7831385/

8. Finite-Time Stabilization of Delayed Memristive Neural Networks: Discontinuous State-Feedback and Adaptive Control Approach
Author(s): Zuowei Cai; Lihong Huang
Page(s): 856 - 868
http://ieeexplore.ieee.org/document/7833122/

9. Identifying a Probabilistic Boolean Threshold Network From Samples
Author(s): Avraham A. Melkman; Xiaoqing Cheng; Wai-Ki Ching; Tatsuya Akutsu
Page(s): 869 - 881
http://ieeexplore.ieee.org/document/7833108/

10. Online Nonlinear AUC Maximization for Imbalanced Data Sets
Author(s): Junjie Hu; Haiqin Yang; Michael R. Lyu; Irwin King; Anthony Man-Cho So
Page(s): 882 - 895
http://ieeexplore.ieee.org/document/7835710/

11. Feature Combination via Clustering
Author(s): Jian Hou; Huijun Gao; Xuelong Li
Page(s): 896 - 907
http://ieeexplore.ieee.org/document/7835669/

12. Impulsive Effects on Quasi-Synchronization of Neural Networks With Parameter Mismatches and Time-Varying Delay
Author(s): Ze Tang; Ju H. Park; Jianwen Feng
Page(s): 908 - 919
http://ieeexplore.ieee.org/document/7835694/

13. Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model
Author(s): Wenjie Pei; Hamdi Dibeklioğlu; David M. J. Tax; Laurens van der Maaten
Page(s): 920 - 931
http://ieeexplore.ieee.org/document/7835652/

14. Manifold Regularized Reinforcement Learning
Author(s): Hongliang Li; Derong Liu; Ding Wang
Page(s): 932 - 943
http://ieeexplore.ieee.org/document/7835715/

15. Adaptive Unsupervised Feature Selection With Structure Regularization
Author(s): Minnan Luo; Feiping Nie; Xiaojun Chang; Yi Yang; Alexander G. Hauptmann; Qinghua Zheng
Page(s): 944 - 956
http://ieeexplore.ieee.org/document/7835729/

16. Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games
Author(s): Qinglai Wei; Derong Liu; Qiao Lin; Ruizhuo Song
Page(s): 957 - 969
http://ieeexplore.ieee.org/document/7835683/

17. Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints
Author(s): Quan-Yong Fan; Guang-Hong Yang; Dan Ye
Page(s): 970 - 980
http://ieeexplore.ieee.org/document/7839175/

18. A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization
Author(s): Shaofu Yang; Qingshan Liu; Jun Wang
Page(s): 981 - 992
http://ieeexplore.ieee.org/document/7839186/

19. On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear H_infty Control
Author(s): Ding Wang; Chaoxu Mu; Derong Liu; Hongwen Ma
Page(s): 993 - 1005
http://ieeexplore.ieee.org/document/7839293/

20. Regularized Label Relaxation Linear Regression
Author(s): Xiaozhao Fang; Yong Xu; Xuelong Li; Zhihui Lai; Wai Keung Wong; Bingwu Fang
Page(s): 1006 - 1018
http://ieeexplore.ieee.org/document/7839224/

21. Collaborative Random Faces-Guided Encoders for Pose-Invariant Face Representation Learning
Author(s): Ming Shao; Yizhe Zhang; Yun Fu
Page(s): 1019 - 1032
http://ieeexplore.ieee.org/document/7839179/

22. Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems
Author(s): Yuan-Xin Li; Guang-Hong Yang
Page(s): 1033 - 1045
http://ieeexplore.ieee.org/document/7839951/

23. Finite-Time State Estimation for Recurrent Delayed Neural Networks With Component-Based Event-Triggering Protocol
Author(s): Licheng Wang; Zidong Wang; Guoliang Wei; Fuad E. Alsaadi
Page(s): 1046 - 1057
http://ieeexplore.ieee.org/document/7843646/

24. Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning
Author(s): Naoki Masuyama; Chu Kiong Loo; Manjeevan Seera; Naoyuki Kubota
Page(s): 1058 - 1068
http://ieeexplore.ieee.org/document/7842602/

25. Safe Exploration Algorithms for Reinforcement Learning Controllers
Author(s): Tommaso Mannucci; Erik-Jan van Kampen; Cornelis de Visser; Qiping Chu
Page(s): 1069 - 1081
http://ieeexplore.ieee.org/document/7842559/

26. Robustness Analysis on Dual Neural Network-based k WTA With Input Noise
Author(s): Ruibin Feng; Chi-Sing Leung; John Sum
Page(s): 1082 - 1094
http://ieeexplore.ieee.org/document/7843595/

27. Differentiation-Free Multiswitching Neuroadaptive Control of Strict-Feedback Systems
Author(s): Jeng-Tze Huang; Thanh-Phong Pham
Page(s): 1095 - 1107
http://ieeexplore.ieee.org/document/7845704/

28. Pattern-Based NN Control of a Class of Uncertain Nonlinear Systems
Author(s): Feifei Yang; Cong Wang
Page(s): 1108 - 1119
http://ieeexplore.ieee.org/document/7845701/

29. Fast-Solving Quasi-Optimal LS-S3VM Based on an Extended Candidate Set
Author(s): Yuefeng Ma; Xun Liang; James T. Kwok; Jianping Li; Xiaoping Zhou; Haiyan Zhang
Page(s): 1120 - 1131
http://ieeexplore.ieee.org/document/7855768/

30. Homotopy Methods Based on L0-Norm for Compressed Sensing
Author(s): Zhengshan Dong; Wenxing Zhu
Page(s): 1132 - 1146
http://ieeexplore.ieee.org/document/7857060/

31. Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions
Author(s): Zhaoxu Yu; Shugang Li; Zhaosheng Yu; Fangfei Li
Page(s): 1147 - 1160
http://ieeexplore.ieee.org/document/7864447/

32. Probabilistic Distance for Mixtures of Independent Component Analyzers
Author(s): Gonzalo Safont; Addisson Salazar; Luis Vergara; Enriqueta Gómez; Vicente Villanueva
Page(s): 1161 - 1173
http://ieeexplore.ieee.org/document/7864437/

33. Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning
Author(s): Wei He; Yiting Dong
Page(s): 1174 - 1186
http://ieeexplore.ieee.org/document/7865986/

34. Simultaneous Bayesian Clustering and Feature Selection Through Student’s t Mixtures Model
Author(s): Jianyong Sun; Aimin Zhou; Simeon Keates; Shengbin Liao
Page(s): 1187 - 1199
http://ieeexplore.ieee.org/document/7865964/

35. Finite-Horizon H_infty Tracking Control for Unknown Nonlinear Systems With Saturating Actuators
Author(s): Huaguang Zhang; Xiaohong Cui; Yanhong Luo; He Jiang
Page(s): 1200 - 1212
http://ieeexplore.ieee.org/document/7867059/

36. Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming
Author(s): Behzad Talaei; Sarangapani Jagannathan; John Singler
Page(s): 1213 - 1225
http://ieeexplore.ieee.org/document/7869406/

37. Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors
Author(s): Qinglai Wei; Benkai Li; Ruizhuo Song
Page(s): 1226 - 1238
http://ieeexplore.ieee.org/document/7866891/

38. Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design
Author(s): Lei Liu; Zhanshan Wang; Huaguang Zhang
Page(s): 1239 - 1251
http://ieeexplore.ieee.org/document/7866865/

39. Partition-Based Solutions of Static Logical Networks With Applications
Author(s): Yupeng Qiao; Hongsheng Qi; Daizhan Cheng
Page(s): 1252 - 1262
http://ieeexplore.ieee.org/document/7872489/

40. Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming
Author(s): Behzad Talaei; Sarangapani Jagannathan; John Singler
Page(s): 1263 - 1274
http://ieeexplore.ieee.org/document/7872449/

41. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure
Author(s): Juntao Fei; Cheng Lu
Page(s): 1275 - 1286
http://ieeexplore.ieee.org/document/7872457/

42. SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture
Author(s): Junxiu Liu; Jim Harkin; Liam P. Maguire; Liam J. McDaid; John J. Wade
Page(s): 1287 - 1300
http://ieeexplore.ieee.org/document/7872403/

43. Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data
Author(s): Ke Gu; Dacheng Tao; Jun-Fei Qiao; Weisi Lin
Page(s): 1301 - 1313
http://ieeexplore.ieee.org/document/7872424/

44. Person Reidentification Based on Elastic Projections
Author(s): Xuelong Li; Lina Liu; Xiaoqiang Lu
Page(s): 1314 - 1327
http://ieeexplore.ieee.org/document/7896623/

45. k-Times Markov Sampling for SVMC
Author(s): Bin Zou; Chen Xu; Yang Lu; Yuan Yan Tang; Jie Xu; Xinge You
Page(s): 1328 - 1341
http://ieeexplore.ieee.org/document/7993056/

46. Neural Network Learning and Robust Stabilization of Nonlinear Systems With Dynamic Uncertainties
Author(s): Ding Wang; Derong Liu; Chaoxu Mu; Yun Zhang
Page(s): 1342 - 1351
http://ieeexplore.ieee.org/document/8053899/

47. Groupwise Retargeted Least-Squares Regression
Author(s): Lingfeng Wang; Chunhong Pan
Page(s): 1352 - 1358
http://ieeexplore.ieee.org/document/7833165/

48. Consensus of Hybrid Multi-Agent Systems
Author(s): Yuanshi Zheng; Jingying Ma; Long Wang
Page(s): 1359 - 1365
http://ieeexplore.ieee.org/document/7835664/

49. Decomposition of Rotor Hopfield Neural Networks Using Complex Numbers
Author(s): Masaki Kobayashi
Page(s): 1366 - 1370
http://ieeexplore.ieee.org/document/7839978/

50. A Stochastic Spiking Neural Network for Virtual Screening
Author(s): A. Morro; V. Canals; A. Oliver; M. L. Alomar; F. Galán-Prado; P. J. Ballester; J. L. Rosselló
Page(s): 1371 - 1375
http://ieeexplore.ieee.org/document/7845709/

51. State Estimation for Static Neural Networks With Time-Varying Delays Based on an Improved Reciprocally Convex Inequality
Author(s): Xian-Ming Zhang; Qing-Long Han
Page(s): 1376 - 1381
http://ieeexplore.ieee.org/document/7857836/

52. Improving KPCA Online Extraction by Orthonormalization in the Feature Space
Author(s): João B. O. Souza Filho; Paulo S. R. Diniz
Page(s): 1382 - 1387
http://ieeexplore.ieee.org/document/7859414/

53. Observability of Automata Networks: Fixed and Switching Cases
Author(s): Rui Li; Yiguang Hong; Xingyuan Wang
Page(s): 1388 - 1394
http://ieeexplore.ieee.org/document/7875406/