Skip to main content
Log in

Formal concept analysis based user model for distributed systems

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

User profile has contributed to customize user access and adjusts applications to its needs. In this respect, automatically building of user profiles issue is an important research area. Nevertheless, standardizing these profiles in terms of representation and acquisition schemes, more especially in large scale systems like Peer-to-Peer systems (P2P), is a complex task. In this paper, we introduce a distributed user profile modelling approach based on user search topics history without the need of any external knowledge resource (e.g., ontology). This model learns from past interests to guess correlations between user requests, associated topics, relevant documents and nodes (i.e., peers) to enhance any information retrieval process. The solution is based on an extension of Formal Concept Analysis (FCA) theory. We also study, the integration of our model in query routing (i.e., content discovery) and results aggregation processes for P2P systems. Carried out experiments, performed under a P2P simulator environment, showed that our model outperforms its competitors in terms of effectiveness and efficiency.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Abid A, Tagliasacchi M (2013) Provisional reporting for rank joins. J Intell Inf Syst 40(3):479–500

    Article  Google Scholar 

  2. Arour K, Yeferny T (2015) Learning model for efficient query routing in p2p information retrieval systems. Peer-to-Peer Netw Appl 8(5):741–757

    Article  Google Scholar 

  3. Aslam JA, Montague M (2001) Models for metasearch. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’01. ACM, New York, pp 276–284

  4. Blanco R, Lioma Ca (2012) Graph-based term weighting for information retrieval. Inf Retriev 15(1):54–92

    Article  Google Scholar 

  5. Bradley K, Rafter R, Smyth B (2000) Case-based user profiling for content personalisation. In: Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH ’00. Springer-Verlag, Trento, pp 62–72

  6. Brambilla M, Tziviskou C (2008) Modeling ontology-driven personalization of web contents. In: Eighth International Conference on web Engineering, 2008. ICWE ’08, pp 247 –260

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

    MATH  Google Scholar 

  8. Cerf L, Besson J, Robardet C, Boulicaut J-F (2008) Data-Peeler: constraint-based closed pattern mining in n-ary relations. In: SIAM International Conference on Data Mining SDM’08, pp 37–48

  9. Chernov S, Serdyukov P, Bender M, Michel S, Weikum G, Zimmer C (2005) Database selection and result merging in p2p web search. In: Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005), Volume 4125 of Lecture Notes in Computer Science. Springer Verlag, Heidelberg, pp 26–37

  10. Bruce Croft W., Cronen-Townsend S, Lavrenko V (2001) Relevance feedback and personalization: a language modeling perspective. In: DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries

  11. Dominguez-Sal D, Perez-Casany M, Larriba-Pey JL (2009) Cache-aware load balancing vs. cooperative caching for distributed search engines. In: Proceedings of the 11th IEEE International Conference on High Performance Computing and Communications. IEEE Computer Society, Washington, pp 415–423

  12. Dwork C, Kumar R, Naor M, Sivakumar D (2001) Rank aggregation methods for the web. In: World wide web conference series, pp 613–622

  13. Farah M, Vanderpooten D (2007) An outranking approach for rank aggregation in information retrieval. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’07. ACM, New York, pp 591–598

  14. Ferreira J, Mysdi AS (2001) A generic architecture to develop sdi personalised services. In: Proceedings of the 3rd International Conference on Enterprise Information Systems, Setubal, pp 7–10

  15. Ganter B, Wille R (1999) Formal concept analysis: mathematical foundations. Springer-Verlag, Heidelberg-Berlin-New York

    Book  MATH  Google Scholar 

  16. Gnutella (2011) Gnutella Web site. http://www.gnutella.com/

  17. Godin R, Missaoui R, Alaoui H (1995) Incremental concept formation algorithms based on galois (concept) lattice. Comput Intell 11:246–267

    Article  Google Scholar 

  18. Greengrass E (2000) Information retrieval: a survey

  19. Han K, Park J, Yi MY (2015) Adaptive and multiple interest-aware user profiles for personalized search in folksonomy: a simple but effective graph-based profiling model. In: International Conference on Big Data and Smart Computing, (BIGCOMP), pp 225–231

  20. Hawalah A, Fasli M (2015) Dynamic user profiles for web personalisation. Expert Syst Appl Elsevier 42(5):2547–2569

    Article  Google Scholar 

  21. He K, He L, Lin X, Wei L (2010) Social view based user modeling for recommendation in tagging systems by association rules. In: 2nd International Workshop on Intelligent systems and Applications. IEEE, pp 1–5

  22. Ignatov DI, Gnatyshak DV, Kuznetsov SO, Mirkin BG (2015) Triadic formal concept analysis and triclustering: searching for optimal patterns. Mach Learn 101(1–3):271–302

    Article  MathSciNet  MATH  Google Scholar 

  23. Ismail A, Hajjar M, Quafafou M, Durand N, El-Sayed M (2013) Clustering using hypergraph for P2P query routing - simulation and evaluation. In: ICEIS 2013 - Proceedings of the 15th International Conference on Enterprise Information Systems, vol 1. Angers, pp 247–254

  24. Jelasity M, Montresor A, Jesi GP, Voulgaris S (2007) The Peersim simulator. http://peersim.sf.net

  25. Jelassi MN, Yahia SB, Nguifo EM (2012) A scalable mining of frequent quadratic concepts in d-folksonomies. CoRR, abs/1212.0087

  26. Jin H, Ning X, Chen H, Yin Z (2006) Efficient query routing for information retrieval in semantic overlays. In: Proceedings of the 21st Annual ACM Symposium on Applied Computing. ACM Press, Dijon, France, pp 23–27

  27. Kalogeraki V, Gunopulos D, Zeinalipour-Yazti D (2002) A local search mechanism for peer-to-peer networks. In: Proceedings of the Eleventh International Conference on Information and Knowledge Management, CIKM ’02. ACM, pp 300–307

  28. Kelly D, Teevan J (2003) Implicit feedback for inferring user preference: a bibliography. SIGIR Forum 37:18–28

    Article  Google Scholar 

  29. Kobsa A (2001) Generic user modeling systems. User Model User-Adapt Interact 11(1-2):49–63

    Article  MATH  Google Scholar 

  30. Kostadinov D (2008) Data Personalization: an approach for profile management and query reformulation. PhD thesis, Universit de Versailles Saint-Quentin-En-Yvelines

  31. Luna V, Quintero R, Torres M, Moreno-Ibarra M, Guzmȧn G, Escamilla I (2015) An ontology-based approach for representing the interaction process between user profile and its context for collaborative learning environments. Comput Human Behav 51:1387–1394

    Article  Google Scholar 

  32. Mahmoud A, Niu N (2010) An experimental investigation of reusable requirements retrieval. In: Proceedings of the IEEE International Conference on Information Reuse and Integration, IRI 2010. IEEE Systems, Man, and Cybernetics Society, Nevada, USA, pp 330–335

  33. Piwowarski B, Gallinari P, Dupret G (2007) Precision recall with user modelling (prum): Application to structured information retrieval. ACM Trans Inf Syst 25(1):1–37

    Article  Google Scholar 

  34. Poelmans J, Elzinga P, Viaene S, Dedene G (2010) Formal concept analysis in knowledge discovery: A survey. In: Proceedings of the 18th international conference on Conceptual structures: from information to intelligence, volume 6208 of ICCS’10. Springer, pp 139-153

  35. Qi X (2010) Research on user profiling technology for personalized demands. In: Proceedings of the 2010 International Conference on Intelligent Computation Technology and Automation - Volume 03, ICICTA ’10. IEEE Computer Society, DC, USA, pp 198–201

  36. RARE (2010) RARE project. In: http://www-inf.it-sudparis.eu

  37. Renda EM, Straccia U (2003) Web metasearch: rank vs. score based rank aggregation methods. In: Proceedings of the 2003 ACM Symposium on Applied Computing, SAC 03. ACM, pp 841– 846

  38. Routray R, Zhang R, Eyers DM, Willcocks D, Pietzuch P, Sarkar P (2010) Policy generation framework for large-scale storage infrastructures. In: IEEE International Symposium on Policies for Distributed Systems and Networks (Policy’10). IEEE, VA, US

  39. Salton G (1989) Automatic text processing – the transformation, analysis, and retrieval of information by computer. Addison–Wesley

  40. Savoy J, Rasolofo Y, Abbaci F (2001) Recherche d’informations dans des sources distribuées, pp 237–252

  41. Soltysiak SJ, Crabtree IB (1998) Automatic learning of user profiles: Towards the personalisation of agent services. BT Technol J 16:110–117

    Article  Google Scholar 

  42. (2010) TREC. Text REtrival Conference., http://trec.nist.gov/

  43. Valtchev P, Grosser D, Roume C, Hacene MR (2003) Galicia: an open platform for lattices. In: Using Conceptual Structures: Contributions to the 11th International Conference on Conceptual Structures (ICCS’03). Shaker Verlag, pp 241–254

  44. Wahlster W, Kobsa A (1986) Dialogue-based user models. IEEE Comput Soc 74(7):948–960

    Google Scholar 

  45. Wan X, Jamaliding Q, Anma F, Okamoto T (2010) Applying keyword map based learner profile to a recommender system for group learning support. Int Work Educ Technol Comput Sci 1:3–6

    Google Scholar 

  46. Witschel HF (2008) Global and local resources for peer-to-peer text retrieval. Technical report. Der Fakultat fur Mathematik und Informatik der Universite Leipzig eingereichte

  47. Zhang Z, Yang M, Li S, Qi H, Song C (2009) Sogou query log analysis: A case study for collaborative recommendation or personalized ir. IEEE Computer Society, DC, USA, pp 304-307

  48. Zhou X, Wang W, Jin Q (2015) Multi-dimensional attributes and measures for dynamical user profiling in social networking environments. Multimed Tools Appl, Springer 74(14):5015–5028

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Khedija Arour.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arour, K., Yeferny, T. Formal concept analysis based user model for distributed systems. Multimed Tools Appl 76, 16085–16105 (2017). https://doi.org/10.1007/s11042-016-3896-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3896-y

Keywords

Navigation