Abstract
For bridging the gap between information retrieval (IR) and databases (DB), this article focuses on the logical view. We claim that IR should adopt three major concepts from DB, namely inference, vague predicates and expressive query languages. By regarding IR as uncertain inference, probabilistic versions of relational algebra and Datalog yield very powerful inference mechanisms for IR as well as allowing for more flexible systems. For dealing with various media and data types, vague predicates form a natural extension of text retrieval methods to attribute values, thus switching from propositional to predicate logic. A more expressive IR query language should support joins, be able to compute aggregated results, and allow for restructuring of the result objects.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Belnap, N.: A useful four-valued logic. In: Modern Uses of Multiple-Valued Logic. Reidel, Dordrecht (1977)
Case, P., Dyck, M., Holstege, M., Amer-Yahia, S., Botev, C., Buxton, S., Doerre, J., Melton, J., Rys, M., Shanmugasundaram, J.: Xquery and xpath full text 1.0 (2011), http://www.w3.org/TR/xpath-full-text-10/
Ceri, S., Gottlob, G., Tanca, L.: Logic Programming and Databases. Springer, Heidelberg (1990)
Dalvi, N.N., Suciu, D.: Efficient query evaluation on probabilistic databases. VLDB J. 16(4), 523–544 (2007)
Forst, J.F., Tombros, A., Roelleke, T.: Polis: A probabilistic logic for document summarisation. In: Proceedings of the 1st International Conference on Theory of Information Retrieval (ICTIR 2007) - Studies in Theory of Information Retrieval, pp. 201–212 (2007)
Frommholz, I., Fuhr, N.: Probabilistic, object-oriented logics for annotation-based retrieval in digital libraries. In: Nelson, M., Marshall, C., Marchionini, G. (eds.) Opening Information Horizons – Proc. of the 6th ACM/IEEE Joint Conference on Digital Libraries (JCDL 2006), pp. 55–64. ACM, New York (2006)
Fuhr, N.: A probabilistic framework for vague queries and imprecise information in databases. In: Proceedings of the 16th International Conference on Very Large Databases, Los Altos, California, pp. 696–707. Morgan Kaufman (1990)
Fuhr, N.: Probabilistic Datalog: Implementing logical information retrieval for advanced applications. Journal of the American Society for Information Science 51(2), 95–110 (2000)
Fuhr, N., Rölleke, T.: A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Transactions on Information Systems 14(1), 32–66 (1997)
Fuhr, N., Rölleke, T.: HySpirit – a probabilistic inference engine for hypermedia retrieval in large databases. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 24–38. Springer, Heidelberg (1998)
Lalmas, M., Roelleke, T., Fuhr, N.: Intelligent hypermedia retrieval. In: Szczepaniak, P.S., Segovia, F., Zadeh, L.A. (eds.) Intelligent Exploration of the Web, pp. 324–344. Springer, Heidelberg (2002)
McGuinness, D.L., van Harmelen, F.: OWL. Technical report, World Wide Web Consortium (2004), http://www.w3.org/TR/owl-features/
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufman, San Mateo (1988)
Rölleke, T., Fuhr, N.: Probabilistic reasoning for large scale databases. In: Datenbanksysteme in Büro, Technik und Wissenschaft (BTW 1997), pp. 118–132. Springer, Heidelberg (1997)
Rölleke, T., Wu, H., Wang, J., Azzam, H.: Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes. The International Journal on Very Large Data Bases (VLDB) 17(1), 5–37 (2007)
Suciu, D., Olteanu, D., Ré, C., Koch, C.: Probabilistic Databases. Synthesis Lectures on Data Management. Morgan & Claypool Publishers (2011)
Ullman, J.D.: Principles of Database and Knowledge-Base Systems, vol. I. Computer Science Press, Rockville (1988)
van Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworths, London (1979)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Fuhr, N. (2014). Bridging Information Retrieval and Databases. In: Ferro, N. (eds) Bridging Between Information Retrieval and Databases. PROMISE 2013. Lecture Notes in Computer Science, vol 8173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54798-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-54798-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54797-3
Online ISBN: 978-3-642-54798-0
eBook Packages: Computer ScienceComputer Science (R0)