Abstract
Concept-based information retrieval is known to be a powerful and reliable process. It relies on a semantically annotated corpus, i.e. resources indexed by concepts organized within a domain ontology. The conception and enlargement of such index is a tedious task, which is often a bottleneck due to the lack of (semi-)automated solutions. In this paper, we first introduce a solution to assist experts during the indexing process thanks to semantic annotation propagation. The idea is to let them position the new resource on a semantic map, containing already indexed resources and to propose an indexation of this new resource based on those of its neighbors. To further help users, we then introduce indicators to estimate the robustness of the indexation with respect to the indicated position and to the annotation homogeneity of nearby resources. By computing these values before any interaction, it is possible to visually inform users on their margins of error, therefore reducing the risk of having a non-optimal, thus unsatisfying, annotation.
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References
Haav, H.M., Lubi, T.L.: A survey of concept-based information retrieval tools on the web. In: Proceedings of the 5th East-European Conference ADBIS, vol. 2, pp. 29–41 (2001)
Crampes, M., Ranwez, S., Velickovski, F., Mooney, C., Mille, N.: An integrated visual approach for music indexing and dynamic playlist composition. In: Electronic Imaging 2006, p. 607103. International Society for Optics and Photonics (2006)
Crampes, M., de Oliveira-Kumar, J., Ranwez, S., Villerd, J.: Visualizing social photos on a hasse diagram for eliciting relations and indexing new photos. IEEE Transactions on Visualization and Computer Graphics 15(6), 985–992 (2009)
Lazaridis, M., Axenopoulos, A., Rafailidis, D., Daras, P.: Multimedia search and retrieval using multimodal annotation propagation and indexing techniques. Signal Processing: Image Communication 28(4), 351–367 (2013)
Marchiori, M.: The limits of web metadata, and beyond. Computer Networks and ISDN Systems 30(1), 1–9 (1998)
Abrouk, L., Gouaïch, A.: Automatic annotation using citation links and co-citation measure: Application to the water information system. In: Mizoguchi, R., Shi, Z.-Z., Giunchiglia, F. (eds.) ASWC 2006. LNCS, vol. 4185, pp. 44–57. Springer, Heidelberg (2006)
Jeon, J., Manmatha, R.: Using maximum entropy for automatic image annotation. In: Enser, P.G.B., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds.) CIVR 2004. LNCS, vol. 3115, pp. 24–32. Springer, Heidelberg (2004)
Zhang, H., Su, Z.: Improving cbir by semantic propagation and cross modality query expansion. In: Proc. of the Int. Workshop on Multimedia Content-based Indexing and Retrieval, Brescia, pp. 19–21 (2001)
Shevade, B., Sundaram, H.: Vidya: an experiential annotation system. In: Proceedings of the 2003 ACM SIGMM Workshop on Experiential Telepresence, pp. 91–98. ACM (2003)
Lin, D.: An information-theoretic definition of similarity. In: ICML, vol. 98, pp. 296–304 (1998)
Schlicker, A., Domingues, F.S., Rahnenführer, J., Lengauer, T.: A new measure for functional similarity of gene products based on gene ontology. BMC Bioinformatics 7(1), 302 (2006)
Harispe, S., Janaqi, S., Ranwez, S., Montmain, J.: From theoretical framework to generic semantic measures library. In: Demey, Y.T., Panetto, H. (eds.) OTM 2013 Workshops. LNCS, vol. 8186, pp. 739–742. Springer, Heidelberg (2013)
Harispe, S., Ranwez, S., Janaqi, S., Montmain, J.: The Semantic Measures Library and Toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies (2013), doi:10.1093/bioinformatics
Seco, N., Veale, T., Hayes, J.: An intrinsic information content metric for semantic similarity in wordnet. In: ECAI, vol. 16, p. 1089. Citeseer (2004)
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Fiorini, N., Ranwez, S., Montmain, J., Ranwez, V. (2014). Coping with Imprecision During a Semi-automatic Conceptual Indexing Process. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 444. Springer, Cham. https://doi.org/10.1007/978-3-319-08852-5_2
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DOI: https://doi.org/10.1007/978-3-319-08852-5_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08851-8
Online ISBN: 978-3-319-08852-5
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