Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Exploration of Web Search Results Based on the Formal Concept Analysis

  • Conference paper
  • First Online:
Semantic Keyword-Based Search on Structured Data Sources (IKC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10546))

Included in the following conference series:

  • 857 Accesses

Abstract

In this paper, we present an approach to support exploratory search by structuring search results based on concept lattices, which are created on the fly using advanced methods from the area of Formal Concept Analysis (FCA). The main aim of the approach is to organize query based search engine results (e.g. web documents) as a hierarchy of clusters that are composed of documents with similar attributes. The concept lattice provides a structured view on the query-related domains and hence can improve the understanding of document properties and shared features. Additionally, we applied a fuzzy extension of FCA in order to support the usage of different types of attributes within the analyzed query results set. The approach has been integrated into an interactive web search interface. It provides a smooth integration of keyword-based web search and interactive visualization of concept lattice and its concepts in order to support complex search tasks.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Similar content being viewed by others

Notes

  1. 1.

    D3: https://d3js.org/.

  2. 2.

    gojs: https://gojs.net/.

  3. 3.

    Note that \(2^S\) denotes the power set of the set S, i.e., the set of all subsets of S.

References

  1. Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Heidelberg (1999). https://doi.org/10.1007/978-3-642-59830-2

  2. Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49, 41–46 (2006)

    Article  Google Scholar 

  3. Gossen, T., Nitsche, M., Haun, S., Nürnberger, A.: Data exploration for bisociative knowledge discovery: a brief overview of tools and evaluation methods. In: Berthold, M.R. (ed.) Bisociative Knowledge Discovery. LNCS (LNAI), vol. 7250, pp. 287–300. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31830-6_20

    Chapter  Google Scholar 

  4. Medina, J., Ojeda-Aciego, M., Ruiz-Calviño, J.: Formal concept analysis via multi-adjoint concept lattices. Fuzzy Set. Syst. 160, 130–144 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  5. Pocs, J.: Note on generating fuzzy concept lattices via Galois connections. Inf. Sci. 185(1), 128–136 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  6. Antoni, L., Krajči, S., Krídlo, O., Macek, B., Pisková, L.: On heterogeneous formal contexts. Fuzzy Set. Syst. 234, 22–33 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  7. Pócs, J., Pócsová, J.: Basic theorem as representation of heterogeneous concept lattices. Front. Comput. Sci. 9(4), 636–642 (2015)

    Article  Google Scholar 

  8. Krajči, S.: Cluster based efficient generation of fuzzy concepts. Neural Netw. World 13(5), 521–530 (2003)

    Google Scholar 

  9. Butka, P., Pocs, J.: Generalization of one-sided concept lattices. Comput. Inform. 32(2), 355–370 (2013)

    MathSciNet  Google Scholar 

  10. Kumar, C.A., Srinivas, S.: Concept lattice reduction using fuzzy K-Means clustering. Expert Syst. Appl. 37(3), 2696–2704 (2010)

    Article  Google Scholar 

  11. Antoni, L., Krajči, S., Krídlo, O.: On stability of fuzzy formal concepts over randomized one-sided formal context. Fuzzy Set. Syst. 333, 36–53 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kardoš, F., Pócs, J., Pócsová, J.: On concept reduction based on some graph properties. Knowl. Based Syst. 93, 67–74 (2016)

    Article  Google Scholar 

  13. Butka, P., Pócs, J., Pócsová, J.: Reduction of concepts from generalized one-sided concept lattice based on subsets quality measure. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds.) New Research in Multimedia and Internet Systems. AISC, vol. 314, pp. 101–111. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10383-9_10

    Google Scholar 

  14. Butka, P., Pócs, J., Pócsová, J.: On intent stability index for one-sided concept lattices. In: Proceedings of 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI 2015), pp. 79–84 (2015)

    Google Scholar 

  15. Butka, P., Pócs, J., Pócsová, J.: Two-step reduction of GOSCL based on subsets quality measure and stability index. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds.) Multimedia and Network Information Systems. AISC, vol. 506, pp. 419–429. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-43982-2_36

    Chapter  Google Scholar 

  16. Smatana, M., Butka, P., Cöveková, L.: Tree based reduction of concept lattices based on conceptual indexes. In: Borzemski, L., Grzech, A., Świątek, J., Wilimowska, Z. (eds.) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I. AISC, vol. 521, pp. 211–220. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-46583-8_17

    Google Scholar 

  17. Haun, S., Nürnberger, A., Kötter, T., Thiel, K., Berthold, M.R.: CET: a tool for creative exploration of graphs. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS (LNAI), vol. 6323, pp. 587–590. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15939-8_39

    Chapter  Google Scholar 

  18. Butka, P., Low, T., Kotzyba, M., Haun, S., Nurnberger, A.: FCA-supported exploratory web search. In: 1st International Symposium on Companion-Technology (ISCT 2015), pp. 131–136 (2015)

    Google Scholar 

  19. Poelmans, J., Ignatov, D.I., Viaene, S., Dedene, G., Kuznetsov, S.O.: Text mining scientific papers: a survey on FCA-based information retrieval research. In: Perner, P. (ed.) ICDM 2012. LNCS (LNAI), vol. 7377, pp. 273–287. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31488-9_22

    Chapter  Google Scholar 

  20. Carpineto, C., Romano, G.: Exploiting the potential of concept lattices for information retrieval with CREDO. J. Univ. Comput. 10(8), 985–1013 (2004)

    MATH  Google Scholar 

  21. Nauer, E., Toussaint, Y.: CreChainDo: an iterative and interactive Web information retrieval system based on lattices. Int. J. Gen. Syst. 38(4), 363–378 (2009)

    Article  MATH  Google Scholar 

  22. Spyratos, N., Meghini, C.: Preference-based query tuning through refinement/enlargement in a formal context. In: Dix, J., Hegner, S.J. (eds.) FoIKS 2006. LNCS, vol. 3861, pp. 278–293. Springer, Heidelberg (2006). https://doi.org/10.1007/11663881_16

    Chapter  Google Scholar 

  23. Butka, P., Pócsová, J., Pócs, J.: A proposal of the information retrieval system based on the generalized one-sided concept lattices. In: Precup, R.E., Kovács, S., Preitl, S., Petriu, E. (eds.) Applied Computational Intelligence in Engineering and Information Technology. Topics in Intelligent Engineering and Informatics, vol. 1, pp. 59–70. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28305-5_5

    Chapter  Google Scholar 

Download references

Acknowledgments

This work was done with the help of Short Term Scientific Mission visit supported by the COST action IC1302 KEYSTONE (semantic KEYword-based Search on sTructured data sOurcEs), and partially within the Transregional Collaborative Research Centre SFB/TRR 62 “A Companion-Technology for Cognitive Technical Systems” funded by the German Research Foundation (DFG) and Slovak VEGA research grant 1/0493/16.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peter Butka .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Butka, P., Low, T., Kotzyba, M., Haun, S., Nürnberger, A. (2018). Exploration of Web Search Results Based on the Formal Concept Analysis. In: Szymański, J., Velegrakis, Y. (eds) Semantic Keyword-Based Search on Structured Data Sources. IKC 2017. Lecture Notes in Computer Science(), vol 10546. Springer, Cham. https://doi.org/10.1007/978-3-319-74497-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-74497-1_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74496-4

  • Online ISBN: 978-3-319-74497-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics