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Relating ontologies with a fuzzy information model

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Abstract

More people than ever before have access to information with the World Wide Web; information volume and number of users both continue to expand. Traditional search methods based on keywords are not effective, resulting in large lists of documents, many of which unrelated to users’ needs. One way to improve information retrieval is to associate meaning to users’ queries by using ontologies, knowledge bases that encode a set of concepts about one domain and their relationships. Encoding a knowledge base using one single ontology is usual, but a document collection can deal with different domains, each organized into an ontology. This work presents a novel way to represent and organize knowledge, from distinct domains, using multiple ontologies that can be related. The model allows the ontologies, as well as the relationships between concepts from distinct ontologies, to be represented independently. Additionally, fuzzy set theory techniques are employed to deal with knowledge subjectivity and uncertainty. This approach to organize knowledge and an associated query expansion method are integrated into a fuzzy model for information retrieval based on multi-related ontologies. The performance of a search engine using this model is compared with another fuzzy-based approach for information retrieval, and with the Apache Lucene search engine. Experimental results show that this model improves precision and recall measures.

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References

  1. Apache Project (2009) Apache Lucene overview, internet page, the Apache Software Foundation http://lucene.apache.org/java/docs/index.html

  2. Baeza-Yates RA, Ribeiro-Neto BA (1999) Modern information retrieval. ACM Press/Addison-Wesley, New York

    Google Scholar 

  3. Bhogal J, Macfarlane A, Smith P (2007) A review of ontology based query expansion. Inf Process Manag 43(4): 866–886

    Article  Google Scholar 

  4. Bobillo F, Straccia U (2009) An owl ontology for fuzzy owl 2. In: Rauch J, Ras Z, Berka P, Elomaa T (eds) Foundations of intelligent systems, vol 5722 of Lecture Notes in computer science. Springer, Berlin/Heidelberg, pp 151–160

    Google Scholar 

  5. Broughton V (2001) Faceted classification as a basis for knowledge organization in a digital environment; the bliss bibliographic classification as a model for vocabulary management and the creation of multidimensional knowledge structures. New Rev Hypermed Multimed 7(1): 67–102

    Article  Google Scholar 

  6. Chen S-M, Horng Y-J, Lee C-H (2003) Fuzzy information retrieval based on multi-relationship fuzzy concept networks. Fuzzy Sets Syst 140(1): 183–205

    Article  MathSciNet  MATH  Google Scholar 

  7. Choi N, Song I-Y, Han H (2006) A survey on ontology mapping. SIGMOD Rec 35(3): 34–41

    Article  Google Scholar 

  8. Cruz IF, Rajendran A (2003) Semantic data integration in hierarchical domains. IEEE Intell Syst 18(2): 66–73

    Article  Google Scholar 

  9. de Souza KXS, Davis J (2005) Expanding queries in knowledge management systems. In: Katarzyniak RP (ed) Ontologies and soft methods in knowledge management. Advanced Knowledge International Pty Ltd., Poland, pp 3–18

    Google Scholar 

  10. Embrapa (2008) Bases de Dados da Pesquisa Agropecuária, Internet page, Empresa Brasileira de Pesquisa Agropecuária. http://www.bdpa.cnptia.embrapa.br/

  11. Embrapa (2009) Brazilian Agricultural Research Corporation, Internet page, Embrapa http://www.embrapa.br/english

  12. Ensan F, Du W (2011) A knowledge encapsulation approach to ontology modularization. Knowl Inf Syst 26(2): 249–283

    Article  Google Scholar 

  13. Finin T, Mayfield J, Joshi A, Cost RS, Fink C (2005) Information retrieval and the semantic web. In: Proceedings of the 38th annual Hawaii international conference on system sciences (HICSS’05)—Track 4, IEEE Computer Society, Washington, DC, USA, p 113.1

  14. Fodeh S, Punch B, Tan P-N (2011) On ontology-driven document clustering using core semantic features. Knowl Inf Syst 28(2): 395–421

    Article  Google Scholar 

  15. Gomez-Pérez A, Fernández-Lopez M, Corcho O (2003) Ontological engineering. Springer, Berlin

    Google Scholar 

  16. Hernandez N, Mothe J, Poulain S (2005) Customizing information access according to domain and task knowledge: the ontoexplo system. In: SIGIR ’05: Proceedings of the 28th annual international ACM SIGIR conference on research and development in information retrieval. ACM Press, New York, NY, USA, pp 607–608

  17. Horng Y-J, Chen S-M, Lee C-H (2003) Automatically constructing multi-relationship fuzzy concept networks for document retrieval. Appl Artif Intell 17(1): 303–328

    Article  MathSciNet  Google Scholar 

  18. Jalali V, Matash Borujerdi M (2010) Information retrieval with concept-based pseudo-relevance feedback in medline. Knowl Inf Syst 29(1): 237–248

    Article  Google Scholar 

  19. Jin W, Srihari RK, Ho HH, Wu X (2007) Improving knowledge discovery in document collections through combining text retrieval and link analysis techniques. In: Proceedings of the 2007 seventh IEEE international conference on data mining. IEEE Computer Society, Washington, DC, USA, pp 193–202

  20. Jung JJ (2008) Taxonomy alignment for interoperability between heterogeneous virtual organizations. Exp Syst Appl 34(4): 2721–2731

    Article  Google Scholar 

  21. Kalfoglou Y, Schorlemmer M (2003) Ontology mapping: the state of the art. Knowl Eng Rev 18(1): 1–31

    Article  Google Scholar 

  22. Klein M (2001) Combining and relating ontologies: an analysis of problems and solutions. In: Gomez-Perez A, Gruninger M, Stuckenschmidt H, Uschold M (eds) Workshop on ontologies and information sharing, IJCAI’01. Seattle, USA

  23. Kolte SG, Bhirud SG (2009) Exploiting links in wordnet hierarchy for word sense disambiguation of nouns. In: Proceedings of the international conference on advances in computing, communication and control, ICAC3 ’09. ACM, New York, NY, USA, pp 20–25

  24. Lau RYK, Li Y, Xu Y (2007) Mining fuzzy domain ontology from textual databases. In: Proceedings of the IEEE/WIC/ACM international conference on web intelligence. IEEE Computer Society, Washington, DC, USA, pp 156–162

  25. Leite MAA, Ricarte ILM (2008a) Document retrieval using fuzzy related geographic ontologies. In: GIR ’08: Proceeding of the 2nd international workshop on geographic information retrieval. ACM, New York, NY, USA, pp 47–54

  26. Leite MAA, Ricarte ILM (2008b) Fuzzy information retrieval model based on multiple related ontologies. In: 20th IEEE international conference on tools with artificial intelligence. IEEE Computer Society, Washington, DC, USA, pp 309–316

  27. Leite MA, Ricarte IL (2008c) A framework for information retrieval based on fuzzy relations and multiple ontologies. In: IBERAMIA ’08: Proceedings of the 11th Ibero-American conference on AI. Springer, Berlin, Heidelberg, pp 292–301

  28. Luaces MR, Parama JR, Pedreira O, Seco D (2008) An ontology-based index to retrieve documents with geographic information. In: SSDBM ’08: Proceedings of the 20th international conference on scientific and statistical database management. Springer, Berlin, Heidelberg, pp 384–400

  29. Luaces MR, Parama JR, Pedreira O, Seco D, Viqueira JRR (2007) An index structure to retrieve documents with geographic information. In: DEXA ’07: Proceedings of the 18th international conference on database and expert systems applications. IEEE Computer Society, Washington, DC, USA, pp 64–68

  30. Madin JS, Bowers S, Schildhauer MP, Jones MB (2008) Advancing ecological research with ontologies. Trends Ecol Evol 23(3): 159–168

    Article  Google Scholar 

  31. Leite MAA, Ricarte ILM (2010) Multiple ontologies with fuzzy relations, Internet page, School of Electrical and Computer Engineering—University of Campinas—UNICAMP. http://www.dca.fee.unicamp.br/~ricarte/MORFuzz/

  32. McGuinness DL, Chang C (2009) Wine Agent 1.0, Internet page, Stanford University. http://onto.stanford.edu:8080/wino/index.jsp

  33. McGuinness DL, Fikes R, Rice J, Wilder S (2000) An environment for merging and testing large ontologies. In: Proceedings of the seventh international conference on principles of knowledge representation and reasoning (KR2000), pp 483–493

  34. Mothe J, Chrisment C, Dousset B, Alaux J (2003) Doccube: multi-dimensional visualisation and exploration of large document sets. J Am Soc Inf Sci Technol 54(7): 650–659

    Article  Google Scholar 

  35. Nachtegael M, Cock MD, der Weken DV, Kerre EE (2002) Fuzzy relational images in computer science, Lecture Notes In Computer Science, vol 2561, Springer, London, UK, pp 134–151

  36. Noy NF (2004) Semantic integration: a survey of ontology-based approaches. SIGMOD Rec 33(4): 65–70

    Article  Google Scholar 

  37. Noy NF, Musen MA (2000) Prompt: algorithm and tool for automated ontology merging and alignment. In: Proceedings of the seventeenth national conference on artificial intelligence and twelfth conference on innovative applications of artificial intelligence. AAAI Press/The MIT Press, pp 450–455

  38. Ogawa Y, Morita T, Kobayashi K (1991) A fuzzy document retrieval system using the keyword connection matrix and a learning method. Fuzzy Sets Syst 39(2): 163–179

    Article  MathSciNet  Google Scholar 

  39. On B-W, Lee I, Lee D (2012) Scalable clustering methods for the name disambiguation problem. Knowl Inf Syst 31(1):129–151. http://dx.doi.org/10.1007/s10115-011-0397-1

  40. Parry D (2006) Fuzzy ontologies for information retrieval on the www, Elie Sanchez. (Org.). Fuzzy logic and the semantic web. Elsevier, Amsterdan, pp 21–48

  41. Paz-Trillo C, Wassermann R, Braga PP (2005) An information retrieval application using ontologies. J Braz Comput Soc 11(2):17–31. http://dx.doi.org/10.1007/BF03192373

    Google Scholar 

  42. Pedrycz W, Gomide F (1998) An introduction to fuzzy sets: analysis and Design. MIT Press, Cambridge

    MATH  Google Scholar 

  43. Pedrycz W, Gomide F (2007) Fuzzy systems engineering: toward human–centric computing. Wiley, New York

    Book  Google Scholar 

  44. Pereira R, Ricarte I, Gomide F (2006) Fuzzy relational ontological model in information search systems, Elie Sanchez. (Org.). Fuzzy logic and the semantic web. Elsevier, Amsterdan, pp 395–412

  45. Pinto HS, Gómez-Pérez A, Martins JP (1999) Some issues on ontology integration. In: Proceedings of the IJCAI-99 workshop on ontologies and problem solving methods

  46. Plangprasopchok A, Lerman K, Getoor L (2010) Growing a tree in the forest: constructing folksonomies by integrating structured metadata. In: Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining, KDD ’10. ACM, New York, NY, USA, pp 949–958

  47. Projeto SISGA (2009) Mapa do Clima no Brasil, Internet page, Universidade Regional de Blumenau. http://www2.inf.furb.br/sisga/educacao/ensino/mapaClima.php

  48. Quan TT, Hui SC, Cao TH (2007) Ontology-based fuzzy retrieval for digital library. In: Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers, ICADL’07. Springer, Berlin, Heidelberg, pp 95–98

  49. Shah U, Finin T, Joshi A (2002) Information retrieval on the semantic web. In: CIKM ’02: Proceedings of the eleventh international conference on information and knowledge management. ACM Press, New York, NY, USA, pp 461–468

  50. Shehata S, Karray F, Kamel M (2006) Enhancing text retrieval performance using conceptual ontological graph. In: Proceedings of the sixth IEEE international conference on data mining—workshops, IEEE Computer Society, Washington, DC, USA, pp 39–44

  51. Shehata S, Karray F, Kamel M (2007) A concept-based model for enhancing text categorization. In: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’07. ACM, New York, NY, USA, pp 629–637

  52. Silva N, Rocha J (2003) Complex semantic web ontology mapping. Web Intell Agent Syst 1(3,4): 235–248

    Google Scholar 

  53. Straccia U, Lopes N, Lukacsy G, Polleres A (2010) A general framework for representing and reasoning with annotated semantic web data. In: Proceedings of the twenty-fourth AAAI conference on artificial intelligence (AAAI-10). AAAI Press, pp 1437–1442

  54. Tvarozek M, Bielikova M (2007) Personalized faceted navigation for multimedia collections. In: SMAP ’07: Proceedings of the second international workshop on semantic media adaptation and personalization. IEEE Computer Society, Washington, DC, USA, pp 104–109

  55. Widyantoro DH, Yen J (2001) A fuzzy ontology-based abstract search engine and its user studies. In: Proceedings of the IEEE international conference on fuzzy systems. IEEE Computer Society, Washington, DC, USA, pp 1291–1294

  56. Wikipedia (2009) Köppen climate classification, Internet page, Wikimedia Foundation http://en.wikipedia.org/wiki/Köppen_climate_classification

  57. Zhang L, Yu Y, Zhou J, Lin C, Yang Y (2005) An enhanced model for searching in semantic portals. In: WWW ’05: Proceedings of the 14th international conference on World Wide Web. ACM, New York, NY, USA, pp 453–462

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Authors and Affiliations

  1. Embrapa Agriculture Informatics, Campinas, SP, Brazil

    Maria Angelica Andrade Leite

  2. School of Electrical and Computer Engineering, University of Campinas, Campinas, SP, Brazil

    Ivan Luiz Marques Ricarte

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  1. Maria Angelica Andrade Leite
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  2. Ivan Luiz Marques Ricarte
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Correspondence to Maria Angelica Andrade Leite.

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Leite, M.A.A., Ricarte, I.L.M. Relating ontologies with a fuzzy information model. Knowl Inf Syst 34, 619–651 (2013). https://doi.org/10.1007/s10115-012-0482-0

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