Abstract
A problem with traditional information retrieval systems is that they typically retrieve information without an explicitly defined domain of interest to the user. Consequently, the system presents a lot of information that is of little relevance to the user. Ideally, the queries’ real intentions should be exposed and reflected in the way the underlying retrieval machinery can deal with them. In this paper we propose using abstraction layers to differentiate on the query terms. We explain why we believe this differentiation of query terms is necessary and the potentials of this approach. The whole retrieval system is under development as part of a Semantic Web standardization project for the Norwegian oil and gas industry.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11915072_109.
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References
Gulla, J.A., Auran, P.G., Risvik, K.M.: Linguistic Techniques in Large-Scale Search Engines. Fast Search & Transfer, 15 (2002)
Spink, A., Wolfram, D., Jansen, M.B.J., Saracevic, T.: Searching the Web: the public and their queries. J. Am. Soc. Inf. Sci. Technol. 52, 226–234 (2001)
Ozcan, R., Aslangdogan, Y.A.: Concept Based Information Access Using Ontologies and Latent Semantic Analysis. Technical Report CSE-2004-8. University of Texas at Arlington, 16 (2004)
Rajapakse, R.K., Denham, M.: Text retrieval with more realistic concept matching and reinforcement learning. Information Processing & Management 42, 1260–1275 (2006)
Grootjen, F.A., van der Weide, T.P.: Conceptual query expansion. Data & Knowledge Engineering 56, 174–193 (2006)
Qiu, Y., Frei, H.-P.: Concept based query expansion. In: Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 160–169. ACM Press, Pittsburgh (1993)
Chang, Y., Ounis, I., Kim, M.: Query reformulation using automatically generated query concepts from a document space. Information Processing and Management 42, 453–468 (2006)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199–220 (1993)
Tomassen, S.L., Gulla, J.A., Strasunskas, D.: Document Space Adapted Ontology: Application in Query Enrichment. In: Kop, C., Fliedl, G., Mayr, H.C., Métais, E. (eds.) NLDB 2006. LNCS, vol. 3999, pp. 46–57. Springer, Heidelberg (2006)
Song, J.-F., Zhang, W.-M., Xiao, W., Li, G.-H., Xu, Z.-N.: Ontology-Based Information Retrieval Model for the Semantic Web. In: Proceedings of EEE 2005, pp. 152–155. IEEE Computer Society, Los Alamitos (2005)
Rocha, C., Schwabe, D., de Aragao, M.P.: A hybrid approach for searching in the semantic web. In: Proceeding of WWW 2004, pp. 374–383. ACM, New York (2004)
Ciorăscu, C., Ciorăscu, I., Stoffel, K.: knOWLer - Ontological Support for Information Retrieval Systems. In: Proceedings of Sigir 2003 Conference, Workshop on Semantic Web, Toronto, Canada (2003)
Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D.: Semantic Annotation, Indexing, and Retrieval. Journal of Web Semantics 2(1) (2005)
Braga, R.M.M., Werner, C.M.L., Mattoso, M.: Using Ontologies for Domain Information Retrieval. In: Proceedings of the 11th International Workshop on Database and Expert Systems Applications, pp. 836–840. IEEE Computer Society, Los Alamitos (2000)
Borghoff, U.M., Pareschi, R.: Information Technology for Knowledge Management. Journal of Universal Computer Science 3, 835–842 (1997)
Shah, U., Finin, T., Joshi, A., Cost, R.S., Mayfield, J.: Information Retrieval On The Semantic Web. In: Proceedings of Conference on Information and Knowledge Management, pp. 461–468. ACM Press, McLean, Virginia (2002)
Vallet, D., Fernández, M., Castells, P.: An Ontology-Based Information Retrieval Model. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 455–470. Springer, Heidelberg (2005)
Nagypál, G.: Improving Information Retrieval Effectiveness by Using Domain Knowledge Stored in Ontologies. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM-WS 2005. LNCS, vol. 3762, pp. 780–789. Springer, Heidelberg (2005)
Paralic, J., Kostial, I.: Ontology-based Information Retrieval. Information and Intelligent Systems, Croatia, 23–28 (2003)
Adi, T., Ewell, O.K., Adi, P.: High Selectivity and Accuracy with READWARE’s Automated System of Knowledge Organization. Management Information Technologies, Inc. (MITi) (1999)
Chenggang, W., Wenpin, J., Qijia, T., et al.: An information retrieval server based on ontology and multiagent. Journal of computer research & development 38(6), 641–647 (2001)
Det Norske Veritas: Tyrihans Terminology for Subsea Equipment and Subsea Production Data. Det Norske Veritas (DNV), p. 60 (2005)
Tomassen, S.L.: Research on Ontology-Driven Information Retrieval. In: Meersman, R., Tari, Z., Herrero, P., et al. (eds.) OTM 2006, Springer, Montpellier (2006)
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Tomassen, S.L., Strasunskas, D. (2006). Query Terms Abstraction Layers. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. OTM 2006. Lecture Notes in Computer Science, vol 4278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11915072_85
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DOI: https://doi.org/10.1007/11915072_85
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