Swarming in the urban web space to discover the optimal region

Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014

Volumn 2, Issue , 2014, Pages 234-241

  Kumar, Chandan ^a   Gruenefeld, Uwe ^a   Heuten, Wilko ^b   Boll, Susanne ^a  

^a UNIVERSITY OF OLDENBURG   (Germany)

^b OFFIS Institute of Information Technology   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COLLECTIVE BEHAVIOR; COMPUTATIONALLY EFFICIENT; HIGH-PRECISION; LANDSCAPE STRUCTURES; MULTI-CRITERIA; MULTIPLE CRITERIA; OPTIMAL REGIONS; SEARCH PROCESS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84912524537     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2014.103     Document Type: Conference Paper

References (20)

1. D. Ahlers and S. Boll. Location-based Web search. In A. Scharl and K. Tochtermann, editors, The Geospatial Web. How Geo-Browsers, Social Software and the Web 2.0 are Shaping the Network Society. Springer, London, 2007.
2. P. I. Borkar and L. H. Patil. Web information retrieval using genetic algorithm-particle swarm optimization. International Journal of Future Computer and Communication, 2(6):595-599, 2013.
3. J. Chen, Z. Qin, Y. Liu, and J. Lu. Particle swarm optimization with local search. In Neural Networks and Brain, 2005. ICNN&B'05. International Conference on, volume 1, pages 481-484. IEEE, 2005.
4. E. Diaz-Aviles, W. Nejdl, and L. Schmidt-Thieme. Swarming to rank for information retrieval. In Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 9-16. ACM, 2009.
5. H. Drias. Web information retrieval using particle swarm optimization based approaches. In Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on, volume 1, pages 36-39, Aug 2011.
6. R. C. Eberhart and J. Kennedy. A new optimizer using particle swarm theory. In Proceedings of the sixth international symposium on micro machine and human science, volume 1, pages 39-43. New York, NY, 1995.
7. J. Kennedy, R. Eberhart, et al. Particle swarm optimization. In Proceedings of IEEE international conference on neural networks, volume 4, pages 1942-1948. Perth, Australia, 1995.
8. C. Kumar. Relevance and ranking in geographic information retrieval. In Proceedings of the Fourth BCS-IRSG Conference on Future Directions in Information Access, FDIA'11, pages 2-7, Swinton, UK, UK, 2011. British Computer Society.
9. C. Kumar, W. Heuten, and S. Boll. A visual interactive system for spatial querying and ranking of geographic regions. In S. N. Lindstaedt and M. Granitzer, editors, I-KNOW, page 30. ACM, 2013.
10. C. Kumar, W. Heuten, and S. Boll. Visualization support for multicriteria decision making in geographic information retrieval. In A. Cuzzocrea, C. Kittl, D. Simos, E. Weippl, and L. Xu, editors, Availability, Reliability, and Security in Information Systems and HCI, volume 8127 of Lecture Notes in Computer Science, pages 363-375. Springer Berlin Heidelberg, 2013.
11. C. Kumar, B. Poppinga, D. Haeuser, W. Heuten, and S. Boll. Assessing end-user interaction for multi-criteria local search with heatmap and icon-based visualizations. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on MapInteraction, pages 13-19. ACM, 2013.
12. C. Kumar, B. Poppinga, D. Haeuser, W. Heuten, and S. Boll. Geovisual interfaces to find suitable urban regions for citizens: A user-centered requirement study. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 741-744. ACM, 2013.
13. J. Lane, A. Engelbrecht, and J. Gain. Particle swarm optimization with spatially meaningful neighbours. In Swarm Intelligence Symposium, 2008. SIS 2008. IEEE, pages 1-8. IEEE, 2008.
14. S. Ma, J. He, F. Liu, and Y. Yu. Land-use spatial optimization based on pso algorithm. Geo-spatial Information Science, 14(1):54-61, 2011.
15. K. E. Parsopoulos and M. N. Vrahatis. Particle swarm optimization method in multiobjective problems. In Proceedings of the 2002 ACM symposium on Applied computing, pages 603-607. ACM, 2002.
16. R. Poli, J. Kennedy, and T. Blackwell. Particle swarm optimization. Swarm intelligence, 1(1):33-57, 2007.
17. G. Qian, S. Sural, Y. Gu, and S. Pramanik. Similarity between euclidean and cosine angle distance for nearest neighbor queries. In Proceedings of the 2004 ACM symposium on Applied computing, SAC '04, pages 1232-1237, New York, NY, USA, 2004. ACM.
18. J. Shao, Z. Huang, H. T. Shen, J. Shen, and X. Zhou. Distributionbased similarity measures for multi-dimensional point set retrieval applications. In Proceedings of the 16th ACM international conference on Multimedia, MM '08, pages 429-438, New York, NY, USA, 2008. ACM.
19. Y. Sun, Z. Wang, and B. Wyk. Local and global search based pso algorithm. In Y. Tan, Y. Shi, and H. Mo, editors, Advances in Swarm Intelligence, volume 7928 of Lecture Notes in Computer Science, pages 129-136. Springer Berlin Heidelberg, 2013.
20. Z. Wang, Q. Zhang, and D. Zhang. A pso-based web document classification algorithm. In Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on, volume 3, pages 659-664. IEEE, 2007.