Skip to main content
SpringerLink
Log in

Leveraging link pattern for entity-centric exploration over Linked Data

  • Published:
World Wide Web Aims and scope Submit manuscript

Abstract

The increasing amount of Linked Data on the Web can be reused to facilitate numerous applications. One of the first steps is to explore these structured data to determine whether there is relevant information. Since an entity-centric model closely reflects the real world, it provides an intuitive way to explore Linked Data. However, large numbers of linked entities and high diversity of links between entities, often make it difficult for users to understand the overall structure, as well as find the entities of interest quickly for further exploration. In this paper, we present a link pattern discovery approach to facilitate entity exploration. Link patterns describe explicit and implicit relationships between entities and can be used to categorize linked entities. On top of link patterns, we construct a hierarchy to allow exploration of linked entities in a hierarchical multiscale fashion. To lighten users’ exploration burden further, we select top-k link patterns from hierarchy as navigation options. The proposed approach is implemented in a Linked Data browser called SView. We compare it with two conventional Linked Data browsers by conducting a task-based user study. The experiment results show that our approach provides effective support for entity exploration.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14

Similar content being viewed by others

Notes

  1. http://lod-cloud.net/

  2. http://wifo5-03.informatik.uni-mannheim.de/bizer/ng4j/disco/

  3. http://ws.nju.edu.cn/sview_ext/

  4. 4 http://dbpedia.org/resource/Steven_Spielberg

  5. Object properties link entities to entities; Inverse of properties: Properties have a direction.In practice, people often find it useful to define relations in both directions (e.g., persons owncars, cars are owned by persons). https://www.w3.org/TR/owl-ref/

  6. We use l −1 to denote the inverse of link l.

  7. http://wiki.dbpedia.org

  8. https://musicbrainz.org/

  9. http://data.semanticweb.org/

  10. https://www.google.com/trends/topcharts

  11. The tasks are available online. https://github.com/waynezheng/linkpattern

  12. http://ws.nju.edu.cn/sview_ext/

  13. http://dbpedia.org/fct/

  14. http://rhizomik.net/html/rhizomer/

  15. http://ws.nju.edu.cn/linkpattern/. Also, our project code is uploaded and downloaded freely on https://github.com/waynezheng/linkpattern

References

  1. Alahmari, F., Thom, J.A., Magee, L., Wong, W.: Evaluating semantic browsers for consuming Linked Data. In: Australasian Database Conference, pp. 89–98 (2012)

  2. Araujo, S., Schwabe, D., Barbosa, S.: Experimenting with explorator: a direct manipulation generic rdf browser and querying tool. In: Visual Interfaces to the Social and the Semantic Web (2009)

  3. Becker, C., Bizer, C.: DBpedia mobile-a location-aware semantic Web client. In: Proceedings of the Semantic Web Challenge (2008)

  4. Belohlavek, R., Macko, J.: Selecting important concepts using weights. In: 9th International Conference on Formal Concept Analysis, pp. 65–80 (2011)

  5. Berners-Lee, T., et al.: Tabulator: exploring and analyzing linked data on the semantic Web. In: 3rd International Semantic Web User Interaction Workshop (2006)

  6. Bikakis, N., Sellis, T.: Exploration and visualization in the Web of big linked data: a survey of the state of the art. In: 6th International Workshop on Linked Web Data Management (2016)

  7. Bikakis, N., Skourla, M., Papastefanatos, G.: rdf:SynopsViz: a framework for hierarchical linked data visual exploration and analysis. In: ESWC, pp. 292–297 (2014)

  8. Bizer, C., Heath, T., Berners-Lee, T.: Linked Data-the story so far. Int. J. Semant. Web Inf. Syst. 5(3), 1–22 (2009)

    Article  Google Scholar 

  9. Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia-a crystallization point for the Web of data. Web Semant. Sci. Serv. Agents World Wide Web 7(3), 154–165 (2009)

    Article  Google Scholar 

  10. Bojars, U., Passant, A., Giasson, F., Breslin, J.: An architecture to discover and query decentralized RDF data. In: 3rd Extended Semantic Web Conference Workshop (2007)

  11. Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: SIGMOD, pp. 1247–1250 (2008)

  12. Bordat, J.P.: Calcul pratique du treillis de Galois dune correspondance. Math. Sci. Hum. (96), 31–47 (1986)

  13. Brooke, J.: SUS-a quick and dirty usability scale. Usability Eval. Indust. 189 (194), 4–7 (1996)

    Google Scholar 

  14. Carpineto, C., Romano, G., Bordoni, F.U.: Exploiting the potential of concept lattices for information retrieval with CREDO. J. UCS 10(8), 985–1013 (2004)

    MATH  Google Scholar 

  15. Cheng, G., Qu, Y.: Searching linked objects with falcons: Approach, implementation and evaluation. Int. J. Semant. Web Inf. Syst. 5(3), 49–70 (2009)

    Article  Google Scholar 

  16. Chierichetti, F., Kumar, R., Tomkins, A.: Max-cover in map-reduce. In: 19th International World Wide Web Conference, pp. 231–240 (2010)

  17. De Berg, M., Cabello, S., Har-Peled, S.: Covering many or few points with unit disks. Theory Comput. Syst. 45(3), 446–469 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  18. Ducrou, J., Eklund, P.: An intelligent user interface for browsing and search MPEG-7 images using concept lattices. Int. J. Found. Comput. Sci. World Sci. 19(2), 359–381 (2008)

    Article  MATH  Google Scholar 

  19. Ferre, S.: Camelis: a logical information system to organise and browse a collection of documents. Int. J. Gen. Syst. 38(4), 379–403 (2009)

    Article  MATH  Google Scholar 

  20. Freitas, A., Curry, E., Oliveira, J.G., O’Riain, S.: Querying heterogeneous datasets on the linked data Web: challenges, approaches, and trends. IEEE Internet Comput. 16(1), 24–33 (2012)

    Article  Google Scholar 

  21. Ganter, B., Wille, R.: Formal concept analysis: mathematical foundations. Springer Science and Business Media (2012)

  22. Garca, R., Gimeno, J.M., Perdrix, F., Gil, R., et al.: Building a usable and accessible semantic Web interaction platform. World Wide Web 13(12), 143–167 (2010)

    Article  Google Scholar 

  23. Harth, A.: VisiNav: A system for visual search and navigation on Web data. J. Web Sem. 8(4), 348–354 (2010)

    Article  Google Scholar 

  24. Hearst, M.A.: Clustering versus faceted categories for information exploration. Commun. ACM 49(4), 59–61 (2006)

    Article  Google Scholar 

  25. Heath, T., Bizer, C.: Linked data: evolving the Web into a global data space. In: Synthesis Lectures on the Semantic Web: Theory and Technology, Morgan&Claypool Publishers (2011)

  26. Heim, P., Ertl, T., Ziegler, J.: Facet graphs: complex semantic querying made easy. In: 7th Extended Semantic Web Conference, pp 288–302 (2010)

  27. Heim, P., Lohmann, S., Tsendragchaa, D., Ertl, T.: SemLens: visual analysis of semantic data with scatter plots and semantic lenses. In: I-SEMANTICS, pp. 175–178 (2011)

  28. Hildebrand, M., Ossenbruggen, J.V., Hardman, L.: /facet: a browser for heterogeneous semantic Web repositories. In: 14th International Semantic Web Conference, pp. 272–285 (2006)

  29. Hogan, A., Harth, A., Umrich, J., Decker, S.: Towards a scalable search and query engine for the Web. In: 16th International World Wide Web Conference, pp. 1301–1302 (2007)

  30. Huynh, D.F., Karger, D.: Parallax and companion: set-based browsing for the data Web. In: 18th International World Wide Web Conference, pp. 6–16 (2009)

  31. Khuller, S., Moss, A., Naor, J.S.: The budgeted maximum coverage problem. Inf. Process. Lett. 70(1), 39–45 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  32. Klyne, G., Carroll, J.J.: Resource Description Framework (RDF): concepts and abstract syntax-W3C Recommendation (2004)

  33. Kumar, R., Tomkins, A.: A characterization of online browsing behavior. In: 19th International World Wide Web Conference, pp. 561–570 (2010)

  34. Kuznetsov, S.O., Obiedkov, S.A.: Comparing performance of algorithms for generating concept lattices. J. Exp. Theor. Artif. Intell. 14(2-3), 189–216 (2002)

    Article  MATH  Google Scholar 

  35. Lin, T., Pantel, P., Gamon, M., Kannan, A., Fuxman, A.: Active objects: actions for entity-centric search. In: 21st International World Wide Web Conference, pp. 589–598 (2012)

  36. Manning, C.D., Raghavan, P., Schütze, H.: Introduction to information retrieval. Cambridge University Press (2008)

  37. Marie, N., Gandon, F.L.: Survey of linked data based exploration systems. In: 3rd International Conference on Intelligent Exploration of Semantic Data (IESD), pp. 66–77 (2014)

  38. Oren, E., Delbru, R., Decker, S.: Extending faceted navigation for rdf data. In: 14th International Semantic Web Conference, pp. 559–572 (2006)

  39. Popov, I.O., Schraefel, M.C., Hall, W., Shadbolt, N.: Connecting the dots: a multipivot approach to data exploration. In: 10th International Semantic Web Conference, pp 553–568 (2011)

    Google Scholar 

  40. Pound, J., Mika, P., Zaragoza, H.: Ad-hoc object retrieval in the Web of data. In: 19th International World Wide Web Conference, pp. 771–780 (2010)

    Google Scholar 

  41. Selke, J., Homoceanu, S., Balke, W.T.: Conceptual views for entity-centric search: turning data into meaningful concepts. Comput. Sci.-Res. Dev. 27(1), 65–79 (2012)

    Article  Google Scholar 

  42. Stoica, E., Hearst, M.: Nearly automated metadata hierarchy creation. In: HLT-NAACL, pp. 117–120 (2004)

  43. Tummarello, G., Cyganiak, R., Catasta, M., Danielczyk, S., Delbru, R., Decker, S.: Sig.ma: live views on the Web of data. J. Web Sem. 8(4), 355–364 (2010)

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported in part by the National Science Foundation of China under Grant Nos. 61572247 and 61370019, and in part by the 863 Program under Grant 2015AA015406. We are also grateful to all the participants in the experiments of this work.

Author information

Authors and Affiliations

  1. National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

    Liang Zheng, Yuzhong Qu & Gong Cheng

Authors
  1. Liang Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuzhong Qu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gong Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuzhong Qu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zheng, L., Qu, Y. & Cheng, G. Leveraging link pattern for entity-centric exploration over Linked Data. World Wide Web 21, 421–453 (2018). https://doi.org/10.1007/s11280-017-0464-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-017-0464-y

Keywords

Search

Navigation