Skip to main content
SpringerLink
Log in

Multi-relational PageRank for tree structure sense ranking

  • Published:
World Wide Web Aims and scope Submit manuscript

Abstract

In this paper, we study the problem of structural sense ranking for tree data using a multi-relational PageRank approach. By considering multiple types of structural relations, the original tree structural context is better leveraged and hence used to improve the ranking of the senses associated to the tree elements. Upon this intuition, we advance research on the application of PageRank-style methods to semantic graphs inferred from semistructured/plain text data by developing the first PageRank-based formulations that exploit heterogeneity of links to address the problem of structural sense ranking in tree data. Experiments on a large real-world benchmark have confirmed the performance improvement hypothesis of our proposed multi-relational approach.

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

Similar content being viewed by others

References

  1. Agirre, E., Soroa, A.: Using the Multilingual Central Repository for Graph-Based Word Sense Disambiguation Proc. Int. Conf. on Language Resources and Evaluation (LREC), pp. 1388–1392 (2008)

  2. Agirre, E., Soroa, A.: Personalizing PageRank for Word Sense Disambiguation Proc. 12th Conf. of the European Chapter of the Association for Computational Linguistics (EACL), pp. 33–41 (2009)

  3. Avrachenkov, K., Litvak, N., Nemirovsky, D., Osipova, N.: Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient. SIAM J. Numer. Anal. 45 (2), 890–904 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  4. Balmin, A., Hristidis, V., Papakonstantinou, Y.: ObjectRank: Authority-Based Keyword Search in Databases Proc. Int. Conf. on Very Large Data Bases (VLDB), pp. 564–575 (2004)

  5. Davis, D.A., Lichtenwalter, R., Chawla, N.V.: Multi-relational link prediction in heterogeneous information networks Proc. Int. Conf. on Advances in Social Networks Analysis and Mining (ASONAM), pp. 281–288 (2011)

  6. Deng, H., Han, J., Lyu, M.R., King, I.: Modeling and exploiting heterogeneous bibliographic networks for expertise ranking Proc. Int. Joint Conf. on Digital Libraries (JCDL), pp. 71–80 (2012)

  7. Erkan, G., Radev, D.R.: LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. J. Artif. Intell. Res. (JAIR) 22, 457–479 (2004)

    Google Scholar 

  8. Gabrilovich, E., Markovitch, S.: Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis Proc. Int. Joint Conf. on Artificial Intelligence (IJCAI), pp. 1606–1611 (2007)

  9. Gollapalli, S.D., Mitra, P., Giles, C.L.: Ranking authors in digital libraries Proc. Int. Joint Conf. on Digital Libraries (JCDL), pp. 251–254 (2011)

  10. Gracia, J., Mena, E.: Web-Based Measure of Semantic Relatedness Proc. Int. Conf. on Web Information Systems Engineering (WISE), pp. 136–150 (2008)

  11. Helou, S.E., Salzmann, C., Gillet, D.: The 3A Personalized, Contextual and Relation-based Recommender System. J. UCS 16 (16), 2179–2195 (2010)

    Google Scholar 

  12. Interdonato, R., Tagarelli, A.: Multi-relational PageRank for Tree Structure Sense Ranking Proc. Int. Conf. on Web Information Systems Engineering (WISE) - Part I, pp. 306–319 (2013)

  13. Kashyap, A., Amini, R., Hristidis, V.: SonetRank: leveraging social networks to personalize search Proc. ACM Conf. on Information and Knowledge Management (CIKM), pp. 2045–2049 (2012)

  14. Lao, N., Cohen, W.W.: Relational retrieval using a combination of path-constrained random walks. Mach. Learn 81 (1), 53–67 (2010)

    Article  MathSciNet  Google Scholar 

  15. Lee, S., Song, S., Kahng, M., Lee, D., Lee, S.: Random walk based entity ranking on graph for multidimensional recommendation Proc. ACM Conf. on Recommender Systems (RecSys), pp. 93–100 (2011)

  16. Li, L., Xu, G., Zhang, Y., Kitsuregawa, M.: Random walk based rank aggregation to improving web search. Knowl. Based Syst. 24 (7), 943–951 (2011)

    Article  Google Scholar 

  17. Mihalcea, R., Tarau, P.: TextRank: Bringing Order into Text Proc. European Conf. on Empirical Methods in Natural Language Processing (EMNLP), pp. 404–411 (2004)

  18. Mihalcea, R., Tarau, P., Figa, E.: PageRank on Semantic Networks, with Application to Word Sense Disambiguation Proc. 20th Int. Conf. on Computational Linguistics (COLING) (2004)

  19. Nie, Z., Zhang, Y., Wen, J.R., Ma, W.Y.: Object-level ranking: bringing order to Web objects Proc. ACM Conf. on World Wide Web (WWW), pp. 567–574 (2005)

  20. Ramage, D., Rafferty, A.N., Manning, C.D.: Random Walks for Text Semantic Similarity Proc. ACL Workshop on Graph-based Methods for Natural Language Processing, pp. 23–31 (2009)

  21. Sun, Y., Han, J.: Mining Heterogeneous Information Networks: Principles and Methodologies. Synthesis Lectures on Data Mining and Knowledge Discovery. Morgan & Claypool Publishers (2012)

  22. Sun, Y., Han, J., Yan, X., Yu, P.S., Wu, T.: PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB) 4 (11), 992–1003 (2011)

    Google Scholar 

  23. Sun, Y., Han, J., Zhao, P., Yin, Z., Cheng, H., Wu, T.: RankClus: integrating clustering with ranking for heterogeneous information network analysis Proc. Int. Conf. on Extending Database Technology (EDBT), pp. 565–576 (2009)

  24. Sun, Y., Yu, Y., Han, J.: Ranking-based clustering of heterogeneous information networks with star network schema Proc. ACM Int. Conf. on Knowledge Discovery and Data Mining (KDD), pp. 797–806 (2009)

  25. Tagarelli, A.: Exploring Dictionary-based Semantic Relatedness in Labeled Tree Data. Inf. Sci. 220, 244–268 (2013)

    Article  Google Scholar 

  26. Tagarelli, A., Gullo, F.: Evaluating PageRank methods for structural sense ranking in labeled tree data Proc. 2nd Int. Conf. on Web Intelligence, Mining and Semantics (WIMS) 36 (2012)

  27. Tsatsaronis, G., Varlamis, I.: Nørvåg, K.: SemanticRank: Ranking Keywords and Sentences Using Semantic Graphs Proc. Int. Conf. on Computational Linguistics (COLING), pp. 1074–1082 (2010)

  28. Wang, Y., Lin, X., Zhang, Q.: Towards metric fusion on multi-view data: a cross-view based graph random walk approach Proc. ACM Conf. on Information and Knowledge Management (CIKM), pp. 805–810 (2013)

  29. Wu, J., Aberer, K.: Using a layered markov model for distributed web ranking computation Proc. Int. Conf. on Distributed Computing Systems, pp. 533–542 (2005)

  30. Zhang, M., Feng, S., Tang, J., Ojokoh, B.A., Liu, G.: Co-Ranking Multiple Entities in a Heterogeneous Network: Integrating Temporal Factor and Users’ Bookmarks Proc. Int. Conf. on Asian Digital Libraries (ICADL), pp. 202–211 (2011)

Download references

Author information

Authors and Affiliations

  1. Department Computer Engineering, Modeling, Electronics and Systems Sciences, University of Calabria, Rende (CS), Italy

    Roberto Interdonato & Andrea Tagarelli

Authors
  1. Roberto Interdonato
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrea Tagarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andrea Tagarelli.

Additional information

An abridged version of this paper appeared in [12]

Electronic supplementary material

Below is the link to the electronic supplementary material.

(PDF 818 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Interdonato, R., Tagarelli, A. Multi-relational PageRank for tree structure sense ranking. World Wide Web 18, 1301–1329 (2015). https://doi.org/10.1007/s11280-014-0302-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-014-0302-4

Keywords

Search

Navigation