Abstract
This research is to investigate a method that enables social networks to provide a semi-automatic system. The system will allow users to organize their target photos, using the concept of ownership attributes that describe the relationships between objects in the photos. In this paper, we propose formulating a visual semantic relationships query for photo retrieval. A Visual Semantic Relationship Query interface helps users describe their perspectives about the desired photo in a semantic manner. In the ranking process, by interpreting both concepts and relationships, a user’s query is transformed into a SPARQL, which is then sent to the JOSEKI server, and the returned photos are evaluated in terms of relevance to each photo. The experimental results demonstrate the effectiveness of the proposed system.
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References
Stone, Z., Zickler, T., Darrell, T.: Autotagging Facebook: Social Network Context Improves Photo Annotation. In: IEEE Workshop on Internet Vision, pp. 1–8 (2008)
Jung, J.J., Lee, K.S., Park, S.B., Jo, G.S.: Efficient web browsing with semantic annotation: A case study of product images in e-commerce sites. IEICE Transactions on Information and Systems, 843–850 (2005)
Wang, C., Li, Z., Zhang, L.: MindFinder: Image search by interactive sketching and tagging. In: 19th International Conference on World Wide Web, pp. 1309–1312 (2010)
Xu, H., Wang, J., Hua, X.S., Li, S.: Image search by concept map. In: 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 275–282 (2010)
Mathur, P., Karahalios, K.: Using bookmark Visualizations for Self-Reflection and Navigation. In: 27th International Conference Extended Abstracts on Human Factors in Computing Systems, pp. 4657–4662 (2009)
Perlibakas, V.: Distance measures for PCA-based face recognition. Pattern Recognit Lett., 711–724 (2004)
Kumar, N., Belhumeur, P.N., Nayar, S.K.: FaceTracer: A search engine for large collections of images with faces. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 340–353. Springer, Heidelberg (2008)
Davis, I., Jr, E.V.: RELATIONSHIP: A vocabulary for describing relationships between people, http://vocab.org/relationship/
Liu, Y., Zhang, D., Lu, G., Ma, W.Y.: A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 262–282 (2007)
Kherfi, M.L., Ziou, D.: Image retrieval from the World Wide Web: Issues, techniques and systems. ACM Computing Surveys, 35–67 (2004)
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Lee, KS., Jung, JG., Oh, KJ., Jo, GS. (2011). U2Mind: Visual Semantic Relationships Query for Retrieving Photos in Social Network. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6591. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20039-7_35
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DOI: https://doi.org/10.1007/978-3-642-20039-7_35
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