Skip to main content
SpringerLink
Log in

Using Concept Lattices for Text Retrieval and Mining

  • Chapter
Formal Concept Analysis

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3626))

Abstract

The potentials of formal concept analysis (FCA) for information retrieval (IR) have been highlighted by a number of research studies since its inception. With the proliferation of small-size specialised text databases available in electronic format and the advent of Web-based graphical interfaces, FCA has then become even more appealing and practical for searching text collections. The main advantage of FCA for IR is the possibility of eliciting context, which may be used both to improve the retrieval of specific items from a text collection and to drive the mining of its contents. In this paper, we will focus on the unique features of FCA for building contextual IR applications as well as on its most critical aspects. The development of a FCA-based application for mining the web results returned by a major search engine is envisaged as the next big challenge for the field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agosti, M., Melucci, M., Crestani, F.: Automatic authoring and construction of hypertexts for information retrieval. ACM Multimedia Systems 3, 15–24 (1995)

    Article  Google Scholar 

  2. Amati, G., Carpineto, C., Romano, G.: FUB at TREC-10 Web Track: A Probabilistic Framework for Topic Relevance Term Weighting. In: Proceedings of the 10th Text REtrieval Conference (TREC-10), NIST Special Publication 500-250, pp. 182–191, Gaithersburg, MD, USA (2001)

    Google Scholar 

  3. Berenci, E., Carpineto, C., Giannini, V., Mizzaro, S.: Effectiveness of keywordbased display and selection of retrieval results for interactive searches. International Journal on Digital Libraries 3(3), 249–260 (2000)

    Article  Google Scholar 

  4. Bordat, J.P.: Calcul pratique du treillis de Galois d’une correspondance. Math. Sci. Hum. 96, 31–47 (1986)

    MATH  MathSciNet  Google Scholar 

  5. Card, S., Moran, T., Newell, A.: The psychology of human-computer interaction. Lawrence Erlbaum Associates, London (1983)

    Google Scholar 

  6. Carpineto, C., De Mori, R., Romano, G., Bigi, B.: An information theoretic approach to automatic query expansion. ACM Transactions on Information Systems 19(1), 1–27 (2001)

    Article  Google Scholar 

  7. Carpineto, C., Romano, G.: An order-theoretic approach to conceptual clustering. In: Proceedings of the 10th International Conference on Machine Learning, Amherst, MA, USA, pp. 33–40 (1993)

    Google Scholar 

  8. Carpineto, C., Romano, G.: Dynamically bounding browsable retrieval spaces: an application to Galois lattices. In: Proceedings of RIAO 1994: Intelligent Multimedia Information Retrieval Systems and Management, New York, New York USA, pp. 520–533 (1994)

    Google Scholar 

  9. Carpineto, C., Romano, G.: ULYSSES: A lattice-based multiple interaction strategy retrieval interface. In: Blumenthal, U., Gornostaev (eds.) Human- Computer Interaction, 5th International Conference, EWHCI, Selected Papers, pp. 91–104. Springer, Berlin (1995)

    Google Scholar 

  10. Carpineto, C., Romano, G.: Information retrieval through hybrid navigation of lattice representations. International Journal of Human-Computer Studies 45(5), 553–578 (1996)

    Article  Google Scholar 

  11. Carpineto, C., Romano, G.: A lattice conceptual clustering system and its application to browsing retrieval. Machine Learning 24(2), 1–28 (1996)

    Google Scholar 

  12. Carpineto, C., Romano, G.: Effective reformulation of Boolean queries with concept lattices. In: Proceedings of the 3rd International Conference on Flexible Query-Answering Systems, Roskilde, Denmark, pp. 83–94 (1998)

    Google Scholar 

  13. Carpineto, C., Romano, G.: Order-Theoretical Ranking. Journal of the American Society for Information Science 51(7), 587–601 (2000)

    Article  Google Scholar 

  14. Carpineto, C., Romano, G., Giannini, V.: Improving retrieval feedback with multiple term-ranking function combination. ACM Transactions on Information Systems 20(3), 259–290 (2002)

    Article  Google Scholar 

  15. Cole, R., Eklund, P.: Browsing semi-structured web texts using formal concept analysis. In: Proceedings of the 9th International Conference on Conceptual Structures, Stanford, CA, USA, pp. 319–332 (2001)

    Google Scholar 

  16. Cole, R., Eklund, P., Stumme, G.: Document retrieval for e-mail search and discovery using formal concept analysis. Applied Artificial Intelligence 17(3), 257–280 (2003)

    Article  Google Scholar 

  17. Cole, R., Stumme, G.: CEM: A Conceptual Email Manager. In: Proceedings of the 8th International Conference on Conceptual Structures, Darmstadt, Germany, pp. 438–452 (2000)

    Google Scholar 

  18. Efthimiadis, E.: Query expansion. In: Williams, M.E. (ed.) Annual Review of Information Systems and Technology, vol. 31, pp. 121–187. American Society for Information Science, Silver Spring, Maryland, USA (1996)

    Google Scholar 

  19. Ferré, S., Ridoux, O.: A file system based on concept analysis. In: Proceedings of the 1st International Conference on Computational Logic, London, UK, pp. 1033–1047 (2000)

    Google Scholar 

  20. Ganter, B.: Two basic algorithms in concept analysis. Technical Report FB4– Preprint No. 831, TU Darmstadt, Germany (1984)

    Google Scholar 

  21. Ganter, B., Wille, R.: Formal Concept Analysis – Mathematical Foundations. Springer, Heidelberg (1999)

    MATH  Google Scholar 

  22. Gershon, N., Card, S.K., Eick, S.G.: Information visualization tutorial. In: Proceedings of ACM CHI 1998: Human Factors in Computing Systems, Los Angeles, CA, USA, pp. 109–110 (1998)

    Google Scholar 

  23. Gifford, D.K., Jouvelot, P., Sheldon, M.A., JrO’Toole, J.W.: Semantic file systems. In: Proceedings of the 13th ACM Symposium on Operating Systems Principles, pp. 16–25 (1991)

    Google Scholar 

  24. Godin, R., Gecsei, J., Pichet, C.: Design of a browsing interfaces for information retrieval. In: Proceedings of the 12th Annual International ACM SIGIR Conference on Reasearch and Development in Information Retrieval, pp. 32–39 (1989)

    Google Scholar 

  25. Godin, R., Mili, H.: Building and Maintaining Analysis Level Class Hierarchies Using Galois Lattices. In: Proceedings of the 8th Annual Conference on Object Oriented Programming Systems Languages and Applications, Washington, D.C., USA, pp. 394–410 (1993)

    Google Scholar 

  26. Godin, R., Missaoui, R., Alaoui, H.: Incremental concept formation algorithms based on Galois lattices. Computational Intelligence 11(2), 246–267 (1995)

    Article  Google Scholar 

  27. Godin, R., Missaoui, R., April, A.: Experimental comparison of navigation in a Galois lattice with conventional information retrieval methods. International Journal of Man-Machine Studies 38, 747–767 (1993)

    Article  Google Scholar 

  28. Godin, R., Saunders, E., Jecsei, J.: Lattice model of browsable data spaces. Journal of Information Sciences 40, 89–116 (1986)

    Article  MATH  Google Scholar 

  29. Gopal, B., Manber, U.: Integrating content-based access mechanisms with hierarchical file systems. In: Proceedings of 3rd Symposium on Operating Systems Design and Implementation, New Orleans, Louisiana, USA, pp. 265–278 (1999)

    Google Scholar 

  30. Hearst, M.: User interfaces and visualization. In: Baeza-Yates, R., Ribeiro- Neto, B. (eds.) Modern Information Retrieval, pp. 257–322. ACM Press, New York (1999)

    Google Scholar 

  31. Hearst, M.A.: Untangling text data mining. In: Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL 1999), College Park, MD, USA (1999)

    Google Scholar 

  32. Hoaglin, D.C., Mosteller, F., Tukey, J.W.: Understanding robust and exploratory data analysis. John Wiley & Sons, Inc., Chichester (1983)

    MATH  Google Scholar 

  33. Joho, H., Sanderson, M., Beaulieu, M.: Hierarchical approach to term suggestion device. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, p. 454 (2002)

    Google Scholar 

  34. Karp, D., Schabes, Y., Zaidel, M., Egedi, D.: A freely available wide coverage morphological analyzer for English. In: Proceedings of the 14th International Conference on Computational Linguistics (COLING 1992), Nantes, France, pp. 950–955 (1992)

    Google Scholar 

  35. Kuznetsov, S.O., Obiedkov, S.A.: Comparing performance of algorithms for generating concept lattices. Journal of Experimental and Theoretical Artificial Intelligence 14(2–3), 189–216 (2002)

    Article  MATH  Google Scholar 

  36. Lindig, C.: Concept-based component retrieval. In: Working notes of the IJCAI 1995 workshop: Formal Approaches to the Reuse of Plans, Proofs, and Programs, Montreal, Canada, pp. 21–25 (1995)

    Google Scholar 

  37. Lindig, C.: Fast concept analysis. In: Working with conceptual structures – Contribution to the 8th International Conference on Conceptual Structures, Darmstadt, Germany, pp. 152–161 (2000)

    Google Scholar 

  38. Lucarella, D., Parisotto, S., Zanzi, A.: MORE: Multimedia Object Retrieval Environment. In: Proceedings of ACM Hypertext 1993, Seattle, WA, USA, pp. 39–50 (1993)

    Google Scholar 

  39. Maarek, Y., Berry, D., Kaiser, G.: An information retrieval approach for automatically constructing software libraries. IEEE Transactions on software Engineering 17(8), 800–813 (1991)

    Article  Google Scholar 

  40. Norman, D.: Cognitive engineering. In: Norman, D., Draper, S. (eds.) User centered system design, pp. 31–61. Lawrence Erlbaum Associates, Hillsdale (1986)

    Google Scholar 

  41. Nourine, L., Raynaud, O.: A fast algorithm for building lattices. Information. Information Processing Letters 71, 199–204 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  42. Pedersen, G.: A browser for bibliographic information retrieval based on an application of lattice theory. In: Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Pittsburgh, PA, USA, pp. 270–279 (1993)

    Google Scholar 

  43. Porter, M.F.: An algorithm for suffix stripping. Program 14, 130–137 (1980)

    Google Scholar 

  44. Priss, U.: A graphical interface for document retrieval based on Formal Concept Analysis. In: Proceedings of the 8th Midwest Artificial Intelligence and Cognitive Science Conference, Dayton, Ohio, USA, pp. 66–70 (1997)

    Google Scholar 

  45. Priss, U.: Lattice-based information retrieval. Knowledge Organization 27(3), 132–142 (2000)

    Google Scholar 

  46. Robertson, S.E., Walker, S., Beaulieu, M.M.: Okapi at TREC-7: Automatic Ad Hoc, Filtering, VLC, and Interactive track. In: Proceedings of the 7th Text REtrieval Conference (TREC-7), NIST Special Publication 500-242, Gaithersburg, MD, USA, pp. 253–264 (1998)

    Google Scholar 

  47. Rock, T., Wille, R.: Ein Toscana-Erkundungssystem zur Literatursuche. In: Stumme, G., Wille, R. (eds.) Begriffliche Wissensverarbeitung. Methoden und Anwendungen, pp. 239–253. Springer, Berlin (2000)

    Google Scholar 

  48. Salton, G.: Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley, Reading (1989)

    Google Scholar 

  49. Snelting, G., Tip, F.: Reengineering class hierarchies using concept analysis. In: Proceedings of ACM SIGSOFT 6th International Symposium on Foundations of Software Engineering, Lake Buena Vista, FL, USA, pp. 99–110 (1998)

    Google Scholar 

  50. Soergel, D.: Mathematical analysis of documentation systems. Information storage and retrieval 3, 129–173 (1967)

    Article  Google Scholar 

  51. Spink, A., Saracevic, T.: Interaction in information retrieval: selection and effectiveness of search terms. Journal of the American Society for Information Science 48(8), 741–761 (1997)

    Article  Google Scholar 

  52. Spoerri, A.: InfoCrystal: Integrating exact and partial matching approaches through visualization. In: Proceedings of RIAO 1994: Intelligent Multimedia Information Retrieval, New York, New York USA, pp. 687–696 (1994)

    Google Scholar 

  53. Stumme, G.: Local scaling in conceptual data systems. In: Proceedings of the 6th International Conference on Conceptual Structures, Montpellier, France, pp. 308–320 (1998)

    Google Scholar 

  54. van der Merwe, F.J., Kourie, D.G.: Compressed pseudo-lattices. Journal of Experimental and Theoretical Artificial Intelligence 14(2–3), 229–254 (2002)

    Article  MATH  Google Scholar 

  55. Vogt, F., Wachter, C., Wille, R.: Data analysis based on a conceptual file. In: Bock, H.-H., Lenski, W., Ihm, P. (eds.) Classification, Data Analysis and Knowledge Organization, pp. 131–140. Springer, Berlin (1991)

    Google Scholar 

  56. Vogt, F., Wille, R.: TOSCANA – A graphical tool for analyzing and exploring data. In: Tammassia, R., Tollis, I.G. (eds.) Graph Drawing 1994, pp. 226–233. Springer, Berlin (1995)

    Google Scholar 

  57. Wille, R.: Line diagrams of hierarchical concept systems. Int. Classif. 11(2), 77–86 (1984)

    Google Scholar 

  58. Willet, P.: Recent trends in hierarchic document clustering: a critical review. Information Processing & Management 24(5), 577–597 (1988)

    Article  Google Scholar 

  59. Zamir, O., Etzioni, O.: Grouper: A dynamic clustering interface to web search results. WWW8/Computer Networks 31(11–16), 1361–1374 (1999)

    Article  Google Scholar 

  60. Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to ad hoc information retrieval. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, LA, USA, pp. 334–342 (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fondazione Ugo Bordoni, Via Baldassarre Castiglione 59, 00142, Rome, Italy

    Claudio Carpineto & Giovanni Romano

Authors
  1. Claudio Carpineto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Giovanni Romano
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Algebra, University of Technology, Dresden, Germany

    Bernhard Ganter

  2. Research Center L3S, Appelstr. 9a, D-30167, Hannover, Germany

    Gerd Stumme

  3. Fachbereich Mathematik, Technische Universität Darmstadt, D–64289, Darmstadt

    Rudolf Wille

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Carpineto, C., Romano, G. (2005). Using Concept Lattices for Text Retrieval and Mining. In: Ganter, B., Stumme, G., Wille, R. (eds) Formal Concept Analysis. Lecture Notes in Computer Science(), vol 3626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11528784_9

Download citation

  • DOI: https://doi.org/10.1007/11528784_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27891-7

  • Online ISBN: 978-3-540-31881-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation