Abstract
Citation indexes are valuable tools for research, in part because they provide a means with which to measure the relative impact of articles in a collection of scientific literature. Recent efforts demonstrate some value in retrieval systems for citation indexes based on measures of impact. However, such approaches use weak measures of relevance, ranking together a few useful documents with many that are frequently cited but irrelevant. We propose an indexing technique that joins measures of relevance and impact in a single retrieval metric. This approach, called Reference Directed Indexing (RDI) is based on a comparison of the terms authors use in reference to documents. Initial retrieval experiments with RDI indicate that it retrieves documents of a quality on par with current ranking metrics, but with significantly improved relevance.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bharat, K., Mihaila, G.A.: When experts agree: Using non-affiliated experts to rank popular topics. In: Proc. of the 10th World Wide Web Conf. (2001)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks 30(1-7), 107–117 (1998)
Chakrabarti, S., Dom, B., Raghavan, P., Rajagopalan, S., Gibson, D., Kleinberg, J.: Automatic resource compilation by analyzing hyperlink structure and associated text. Computer Networks 30(1-7), 65–74 (1998)
Craswell, N., Hawking, D., Robertson, S.: Effective site finding using link anchor information. In: Proc. of the ACM SIGIR Conf. on Research and Development in Information Retrieval (2001)
Davison, B.D.: Topical locality in the Web. In: Proc. of the ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 272–279 (2000)
Davison, B.D.: Predicting web actions from html content. In: Proc. the ACM Conf. on Hypertext and Hypermedia, College Park, MD, June 2002, pp. 159–168 (2002)
Furnkranz, J.: Exploiting structural information for text classification on the WWW. Intelligent Data Analysis, 487–498 (1999)
Garfield, E.: Citation Indexing: Its Theory and Application in Science, Technology and Humanities. The ISI Press, Philadelphia (1983)
Hitchcock, S., Bergmark, D., Brody, T., Gutteridge, C., Carr, L., Hall, W., Lagoze, C., Harnad, S.: Open citation linking. D-Lib Magazine 8(10) (2002)
Jones, S., Cunningham, S.J., McNab, R.J., Boddie, S.J.: A transaction log analysis of a digital library. Int. Journal on Digital Libraries 3(2), 152–169 (2000)
Kessler, M.M.: Technical information flow patterns. In: Proc. of the Western Joint Computing Conf., Los Angeles, CA, pp. 247–257 (1961)
Kleinberg, J.: Authoritative sources in a hyperlinked environment. Journal of the ACM 46(5), 604–632 (1999)
Lawrence, S., Bollacker, K., Lee Giles, C.: Indexing and retrieval of scientific literature. In: Proc. of the 8th Int. Conf. on Information and Knowledge Management, Kansas City, MO, November 2–6, vol. 6, pp. 139–146 (1999)
McBryan, O.A.: GENVL and WWWW: Tools for taming the web. In: Proc. of the First Int. World Wide Web Conf., Geneva, Switzerland (May 1994)
Menczer, F., Belew, R.K.: Adaptive retrieval agents: Internalizing local context and scaling up to the Web. Machine Learning 39(2-3), 203–242 (2000)
Rennie, J., McCallum, A.K.: Using reinforcement learning to spider the Web efficiently. In: Proc. of the 16th Int. Conf. on Machine Learning, pp. 335–343. Morgan Kaufmann, San Francisco (1999)
Richardson, M., Domingos, P.: The intelligent surfer: Probabilistic combination of link and content information in pagerank. In: Advances in Neural Information Processing Systems, vol. 14. MIT Press, Cambridge (2002)
Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620 (1975)
Salton, G., Buckley, C.: Term weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)
Salton, G., McGill, M.J.: The SMART and SIRE Experimental Retrieval Systems. In: Introduction to Modern Information Retrieval, pp. 118–155. McGraw-Hill, New York (1983)
Sparck-Jones, K.: A statistical interpretation of term specificity and its application to retrieval. Journal of Documentation 28(1), 11–20 (1972)
Spertus, E.: ParaSite: Mining the Structural Information on the World-Wide Web. PhD thesis, MIT (February 1998)
Spink, A., Wolfram, D., Jansen, B., Saracevic, T.: The public and their queries. Journal of the American Society for Information Science and Technology 52(3), 226–234 (2001)
Iwazume, M., Takeda, H., Nishida, T.: Ontology-based information gathering and text categorization from the internet. In: Proc. of the 9th Int. Conf. in Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, pp. 305–314 (1996)
Westbrook, J.H.: Identifying significant research. Science 132 (October 1960)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bradshaw, S. (2003). Reference Directed Indexing: Redeeming Relevance for Subject Search in Citation Indexes. In: Koch, T., Sølvberg, I.T. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2003. Lecture Notes in Computer Science, vol 2769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45175-4_45
Download citation
DOI: https://doi.org/10.1007/978-3-540-45175-4_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40726-3
Online ISBN: 978-3-540-45175-4
eBook Packages: Springer Book Archive