Implementing Recommendations in the PATHS System

  • Paul CloughEmail author
  • Arantxa Otegi
  • Eneko Agirre
  • Mark Hall
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 416)


In this paper we describe the design and implementation of non-personalized recommendations in the PATHS system. This system allows users to explore items from Europeana in new ways. Recommendations of the type “people who viewed this item also viewed this item” are powered by pairs of viewed items mined from Europeana. However, due to limited usage data only 10.3 % of items in the PATHS dataset have recommendations (4.3 % of item pairs visited more than once). Therefore, “related items”, a form of content-based recommendation, are offered to users based on identifying similar items. We discuss some of the problems with implementing recommendations and highlight areas for future work in the PATHS project.


Digital libraries Recommendations Europeana 



The research leading to these results was carried out as part of the PATHS project ( funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 270082.


  1. 1.
    Smeaton, A., Callan, J.: Personalisation and recommender systems in digital libraries. Int. J. Digit. Libr. 5(4), 299–308 (2005)CrossRefGoogle Scholar
  2. 2.
    Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRefGoogle Scholar
  3. 3.
    Ardissono, L., Kuflik, T., Petrelli, D.: Personalization in cultural heritage: the road travelled and the one ahead. User Model. User-Adap. Inter. 22(1–2), 73–99 (2012)CrossRefGoogle Scholar
  4. 4.
    Agirre, E., et al.: PATHS: a system for accessing cultural heritage collections. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL’13), Sofia, Bulgaria, 4–9 August 2013, pp. 151–156 (2013)Google Scholar
  5. 5.
    Fernie, K., et al.: PATHS: personalising access to cultural heritage spaces. In: Proceedings of 18th International Conference on Virtual Systems and Multimedia (VSMM 2012), pp. 469–474 (2012)Google Scholar
  6. 6.
    Tanasa, D., Trousse, B.: Advanced data preprocessing for intersites Web usage mining. IEEE Intell. Syst. 19(2), 59–65 (2004)CrossRefGoogle Scholar
  7. 7.
    Catledge, L., Pitkow, J.: Characterizing browsing strategies in the world-wide web. In: Proceedings of the Third International World-Wide Web Conference on Technology, Tools and Applications, vol. 27 (1995)Google Scholar
  8. 8.
    Jones, R., Klinkner, K.: Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM’08), pp. 699–708. ACM, New York (2008)Google Scholar
  9. 9.
    Aletras, N., Stevenson, M., Clough, P.: Computing similarity between items in a digital library of cultural heritage. J. Comput. Cult. Heritage 5(4), Article 16, 1–19 (2013). doi: 10.1145/2399180.2399184.
  10. 10.
    Sinha, R., Swearingen, K.: The role of transparency in recommender systems. In: Proceedings of the Conference of Human Factors in Computing Systems, 20–25 April 2002, Minneapolis, MN, pp. 830–831. ACM, New York (2002)Google Scholar
  11. 11.
    Agirre, E., et al.: UBC UOS-TYPED: regression for typed-similarity. In: Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*SEM 2013), vol. 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity, Atlanta, Georgia, 13–14 June 2013, pp. 132–137 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Paul Clough
    • 1
    Email author
  • Arantxa Otegi
    • 2
  • Eneko Agirre
    • 2
  • Mark Hall
    • 3
  1. 1.Information SchoolSheffield UniversitySheffieldUK
  2. 2.IXA taldeaUniversity of the Basque CountryDonostiaBasque Country
  3. 3.Department of ComputingEdge Hill UniversityOrmskirkUK

Personalised recommendations