Intent and its discontents: The user at the wheel of the online video search engine

MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia

Volumn , Issue , 2012, Pages 1239-1248

  Hanjalic, Alan ^a   Kofler, Christoph ^a   Larson, Martha ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

multimedia indexing; multimedia information retrieval; retrieval algorithms; search; user intent

Indexed keywords

MULTIMEDIA INDEXING; MULTIMEDIA INFORMATION RETRIEVAL; RETRIEVAL ALGORITHMS; SEARCH; USER INTENT;

EXPERIMENTS; INFORMATION SCIENCE;

SEARCH ENGINES;

EID: 84871362687     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2393347.2396424     Document Type: Conference Paper

References (31)

1. Baeza-Yates, R., Caldern-Benavides, L. and Gonzlez-Caro, C. The intention behind web queries. In String Proc. and IR (2006). Springer-Verlag, 98-109.
2. Broder, A. A taxonomy of web search. SIGIR Forum, 36, 2, 2002, 3-10.
3. Cao, H., Hu, D. H., Shen, D., Jiang, D., Sun, J.-T., Chen, E. and Yang, Q. Context-aware query classification. In SIGIR (2009). ACM, 3-10.
4. Chang, S.-F. Content based multimedia retrieval: lessons learned from two decades of research. In MM (2011). ACM, 1-2.
5. Datta, R., Joshi, D., Li, J. and Wang, J. Z. Image retrieval: Ideas, influences, and trends of the new age. ACM Comput. Surv., 40, 2, 2008, 1-60.
6. Fidel, R. The image retrieval task: implications for the design and evaluation of image databases. New Review of Hypermedia and Multimedia, 3, 1, 1997, 181-199.
7. Fox, S., Karnawat, K., Mydland, M., Dumais, S. and White, T. Evaluating implicit measures to improve web search. ACM Trans. Inf. Syst., 23, 2, 2005, 147-168.
8. Guo, J., Cheng, X., Xu, G. and Zhu, X. Intent-aware query similarity. In CIKM (2011). ACM, 259-268.
9. Hsu, W. H., Kennedy, L. S. and Chang, S.-F. Reranking Methods for Visual Search. IEEE MultiMedia, 14, 3, 2007, 14-22.
10. Ionescu, B., Seyerlehner, K., Rasche, C., Vertan, C. and Lambert, P. An audio-visual approach to web video categorization. MTAP 2012, 1-26.
11. Jansen, B. J., Spink, A. and Pedersen, J. The effect of specialized multimedia collections on web searching. J. Web Eng., 3, 3, 2004, 182-199.
12. Joachims, T. Text categorization with support vector machines: learning with many relevant features. Springer Verlag, Heidelberg, DE, 1998.
13. Kennedy, L., Shih-Fu, C. and Natsev, A. Query-Adaptive Fusion for Multimodal Search. IEEE, 96, 4, 2008, 567-588.
14. Kofler, C. and Lux, M. Dynamic presentation adaptation based on user intent classification. In MM (2009). ACM, 1117-1118.
15. Lamel, L. and Gauvain, J.-L. Speech Processing for Audio Indexing. In Advances in NLP (2008). Springer, 4-15.
16. Larson, M., Eskevich, M., Ordelman, R., Kofler, C., Schmiedeke, S. and Jones, G. Overview of MediaEval 2011 Rich Speech Retrieval Task and Genre Tagging Task. 2011.
17. Larson, M., Soleymani, M., Serdyukov, P., Rudinac, S., Wartena, C., Murdock, V., Friedland, G., Ordelman, R. and Jones, G. Automatic tagging and geotagging in video collections and communities. In ICMR (2011). ACM, 1-8.
18. Lux, M., Kofler, C. and Marques, O. A classification scheme for user intentions in image search. In CHI (2010). ACM, 3913-3918.
19. Mezaris, V., Gidaros, S., Kasper, W., Steffen, J., Ordelman, R., Huijbregts, M., Jong, F. d., Kompatsiaris, I. and Strintzis, M. G. A system for the semantic multimodal analysis of news audio-visual content. EURASIP J. Adv. Signal Process, 20102010, 1-16.
20. Montagnuolo, M. and Messina, A. TV Genre Classification Using Multimodal Information and Multilayer Perceptrons. Springer Berlin / Heidelberg, 2007.
21. Naphade, M., Smith, J. R., Tesic, J., Chang, S.-F., Hsu, W., Kennedy, L., Hauptmann, A. and Curtis, J. Large-Scale Concept Ontology for Multimedia. IEEE MultiMedia, 13, 3, 2006, 86-91.
22. Rose, D. E. and Levinson, D. Understanding user goals in web search. In WWW (2004). ACM, 13-19.
23. Rugg, G. and McGeorge, P. The sorting techniques: a tutorial paper on card sorts, picture sorts and item sorts Expert Systems, 22, 3, 2005.
24. Santos, R. L. T., Macdonald, C. and Ounis, I. Intent-aware search result diversification. In SIGIR (2011). ACM, 595-604.
25. Schmiedeke, S., Kelm, P. and Sikora, T. Cross-Modal Categorisation of User-Generated Video Sequences. In ICMR (2012), 1-8.
26. Snoek, C. G. M. and Worring, M. Concept-Based Video Retrieval. Found. Trends Inf. Retr., 2, 4, 2009, 215-322.
27. Truong, B. T. and Dorai, C. Automatic Genre Identification for Content-Based Video Categorization. In ICPR (2000). IEEE Computer Society, 4230.
28. Vliegendhart, R., Larson, M. and Pouwelse, J. Discovering User Perceptions of Semantic Similarity in Near-duplicate Multimedia Files. In CrowdSearch (WWW) (2012)
29. Yan, R., Yang, J. and Hauptmann, A. G. Learning queryclass dependent weights in automatic video retrieval. In MM (2004). ACM, 548-555.
30. Yang, L. and Hanjalic, A. Supervised reranking for web image search. In MM (2010). ACM, 183-192.
31. Zha, Z.-J., Yang, L., Mei, T., Wang, M., Wang, Z., Chua, T.-S. and Hua, X.-S. Visual query suggestion: Towards capturing user intent in internet image search. ACM Trans. Multimedia Comput. Commun. Appl., 6, 3, 2010, 1-19.