Skip to main content
SpringerLink
Log in

Index design and query processing for graph conductance search

  • Regular Paper
  • Published:
The VLDB Journal Aims and scope Submit manuscript

Abstract

Graph conductance queries, also known as personalized PageRank and related to random walks with restarts, were originally proposed to assign a hyperlink-based prestige score to Web pages. More general forms of such queries are also very useful for ranking in entity-relation (ER) graphs used to represent relational, XML and hypertext data. Evaluation of PageRank usually involves a global eigen computation. If the graph is even moderately large, interactive response times may not be possible. Recently, the need for interactive PageRank evaluation has increased. The graph may be fully known only when the query is submitted. Browsing actions of the user may change some inputs to the PageRank computation dynamically. In this paper, we describe a system that analyzes query workloads and the ER graph, invests in limited offline indexing, and exploits those indices to achieve essentially constant-time query processing, even as the graph size scales. Our techniques—data and query statistics collection, index selection and materialization, and query-time index exploitation—have parallels in the extensive relational query optimization literature, but is applied to supporting novel graph data repositories. We report on experiments with five temporal snapshots of the CiteSeer ER graph having 74–702 thousand entity nodes, 0.17–1.16 million word nodes, 0.29–3.26 million edges between entities, and 3.29–32.8 million edges between words and entities. We also used two million actual queries from CiteSeer’s logs. Queries run 3–4 orders of magnitude faster than whole-graph PageRank, the gap growing with graph size. Index size is smaller than a text index. Ranking accuracy is 94–98% with reference to whole-graph PageRank.

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. Abiteboul, S., Preda, M., Cobena, G.: Adaptive on-line page importance computation. In: WWW Conference, pp. 280–290 (2003)

  2. Adler, M., Mitzenmacher, M.: Towards compressing Web graphs. In: Data Compression Conference, pp. 203–212 (2001)

  3. Agrawal, S., Chaudhuri, S., Das, G.: DBXplorer: A system for keyword-based search over relational databases. In: ICDE. IEEE, San Jose, CA (2002)

  4. Amer-Yahia, S., Botev, C., Shanmugasundaram, J.: TeXQuery: A full-text search extension to XQuery. In: WWW Conference, pp. 583–594. New York (2004)

  5. Babcock, B., Datar, M., Motwani, R., O’Callaghan, L.: Maintaining variance and k-medians over data stream windows. In: PODS Conference, pp. 234–243. ACM (2003)

  6. Balmin, A., Hristidis, V., Papakonstantinou, Y.: Authority-based keyword queries in databases using ObjectRank. In: VLDB Conference, Toronto (2004)

  7. Bar-Yossef, Z., Broder, A.Z., Kumar, R., Tomkins, A.: Sic Transit Gloria Telae: Towards an understanding of the Web’s decay. In: WWW Conference, pp. 328–337 (2004)

  8. Berkhin, P.: Bookmark-coloring approach to personalized pagerank computing. Internet Math. 3(1), (2007)

  9. Bhalotia, G., Hulgeri, A., Nakhe, C., Chakrabarti, S., Sudarshan, S.: Keyword searching and browsing in databases using BANKS. In: ICDE IEEE (2002)

  10. Bharat, K., Bröder, A., Henzinger, M., Kumar, P., Venkatasubramanian, S.: The connectivity server: fast access to linkage information on the Web. In: WWW Conference, Brisbane, Australia (1998)

  11. Borthwick, A., Sterling, J., Agichtein, E., Grishman, R.: Exploiting diverse knowledge sources via maximum entropy in named entity recognition. In: Sixth Workshop on Very Large Corpora. Association for Computational Linguistics (1998)

  12. Chakrabarti, S.: Dynamic personalized PageRank in entity-relation graphs. In: WWW Conference, Banff (2007)

  13. Chakrabarti, S., Agarwal, A.: Learning parameters in entity relationship graphs from ranking preferences. In: PKDD Conference, LNCS, vol. 4213, pp. 91–102. Berlin (2006)

  14. Chakrabarti, S., Mirchandani, J., Nandi, A.: SPIN: Searching personal information networks. In SIGIR Conference, pp. 674–674 (2005)

  15. Chakrabarti, S., Puniyani, K., Das, S.: Optimizing scoring functions and indexes for proximity search in type-annotated corpora. In: WWW Conference. Edinburgh (2006)

  16. Chazelle B.: The soft heap: an approximate priority queue with optimal error rate. JACM 47(6), 1012–1027 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  17. Cohen, E.: Estimating the size of the transitive closure in linear time. In: FOCS Conference, pp. 190–200 (1994)

  18. Craswell, N., Szummer, M.: Random walks on the click graph. In: SIGIR Conference, pp. 239–246. ACM (2007)

  19. Dalvi, B., Kshirsagar, M., Sudarshan, S.: Keyword search on external memory data graphs. In: VLDB Conference (2008)

  20. Doyle, P., Snell, L.: Random walk and electric networks. In: Mathematical Association of America (1984)

  21. Fagin R., Lotem A., Naor M.: Optimal aggregation algorithms for middleware. JCSS 66(4), 614–656 (2003)

    MathSciNet  MATH  Google Scholar 

  22. Faloutsos, C., McCurley, K.S., Tomkins, A.: Connection subgraphs in social networks. In: Workshop on Link Analysis, Counterterrorism, and Privacy. SDM Conference (2004)

  23. Faloutsos, M., Faloutsos, P., Faloutsos, C.: On power-law relationships of the internet topology. In: SIGCOMM, pp. 251–262 (1999)

  24. Fogaras D., Rácz B., Csalogány K., Sarlós T.: Towards scaling fully personalized PageRank: algorithms, lower bounds, and experiments. Internet Math. 2(3), 333–358 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  25. Graefe G.: Query evaluation techniques for large databases. ACM Computing Survey 25(2), 73–170 (1993)

    Article  Google Scholar 

  26. Grishman, R., Sundheim, B.: Message understanding conference-6: A brief history. In: Proceedings of the 16th conference on Computational linguistics, pp. 466–471. Association for Computational Linguistics (1996)

  27. Gupta, M., Pathak, A., Chakrabarti, S.: Fast algorithms for top-k personalized PageRank queries. In: WWW Conference, pp. 1225–1226 (2008)

  28. Gyöngyi, Z., Garcia-Molina, H., Pedersen, J.: Combating web spam with TrustRank. In: VLDB Conference, pp. 576–587. (2004)

  29. Han J., Pei J., Yin Y., Mao R.: Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Min Knowl Discov 8(1), 53–87 (2004)

    Article  MathSciNet  Google Scholar 

  30. Hwang, H., Balmin, A., Reinwald, B., Nijkamp, E.: BinRank: scaling dynamic authority-based search using materialized subgraphs. In: ICDE, pp. 66–77. IEEE Computer Society (2009)

  31. Järvelin, K., Kekäläinen, J.: IR evaluation methods for retrieving highly relevant documents. In: SIGIR Conference, pp. 41–48 (2000)

  32. Jeh, G., Widom, J.: Scaling personalized web search. In: WWW Conference, pp. 271–279 (2003)

  33. Kamvar, S.D., Haveliwala, T.H., Manning, C.D., Golub, G.H.: Extrapolation methods for accelerating PageRank computations. In: WWW Conference, pp. 261–270 (2003)

  34. Kleinberg J.M.: Authoritative sources in a hyperlinked environment. JACM 46(5), 604–632 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  35. Koren, Y., North, S.C., Volinsky, C.: Measuring and extracting proximity in networks. In: SIGKDD Conference, pp. 245–255. ACM (2006)

  36. Koudas, N., Srivastava, D.: Data stream query processing. In: ICDE p. 1145 (2005)

  37. Lempel R., Moran S.: Rank-stability and rank-similarity of link-based web ranking algorithms in authority-connected graphs. Information Retrieval 8(2), 245–264 (2005)

    Article  Google Scholar 

  38. Manning C.D., Schütze H.: Foundations of Statistical Natural Language Processing. MIT, Cambridge (1999)

    MATH  Google Scholar 

  39. McSherry, F.: A uniform approach to accelerated pagerank computation. In: WWW Conference, pp. 575–582 (2005)

  40. Miller, G., Beckwith, R., FellBaum, C., Gross, D., Miller, K., Tengi, R.: Five Papers on WordNet. Princeton University (1993)

  41. Minkov, E., Ng, A., Cohen, W.W.: Contextual search and name disambiguation in email using graphs. In: SIGIR Conference (2006)

  42. Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: bringing order to the Web. Manuscript, Stanford University (1998)

  43. Pan, J.-Y., Yang, H.-J., Faloutsos, C., Duygulu, P.: Automatic multimedia cross-modal correlation discovery. In: SIGKDD Conference, pp. 653–658 (2004)

  44. Pandurangan, G., Raghavan, P., Upfal, E.: Using PageRank to characterize web structure. In: COCOON, LNCS 2387, pp. 330–339 (2002)

  45. Pathak, A., Chakrabarti, S., Gupta, M.S.: Index design for dynamic personalized PageRank. In: ICDE, pp. 1489–1491 (2008)

  46. Sarkar, P., Moore, A.W.: A tractable approach to finding closest truncated-commute-time neighbors in large graphs. In: UAI Conference (2007)

  47. Sarkar, P., Moore, A.W., Prakash, A.: Fast incremental proximity search in large graphs. In: ICML, pp. 896–903 (2008)

  48. Silverstein, C., Henzinger, M., Marais, H., Moricz, M.: Analysis of a very large AltaVista query log. Technical Report 1998-014, COMPAQ System Research Center (1998)

  49. Sleator, D.D., Temperley, D.: Parsing English with a link grammar. In: Third International Workshop on Parsing Technologies (1993)

  50. Theobald, M., Weikum, G., Schenkel, R.: Top-k query evaluation with probabilistic guarantees. In: VLDB Conference, pp. 648–659 (2004)

  51. Tong, H., Faloutsos, C.: Center-piece subgraphs: problem definition and fast solutions. In: SIGKDD Conference (2006)

  52. Tong, H., Faloutsos, C., Koren, Y.: Fast direction-aware proximity for graph mining. In: SIGKDD Conference, pp. 747–756. ACM (2007)

  53. Tong, H., Faloutsos, C., Pan, J.-Y.: Fast random walk with restart and its applications. In: ICDM (2006)

Download references

Author information

Authors and Affiliations

  1. IIT Bombay, Powai, Mumbai, Maharashtra, India

    Soumen Chakrabarti, Amit Pathak & Manish Gupta

Authors
  1. Soumen Chakrabarti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amit Pathak
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manish Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Soumen Chakrabarti.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chakrabarti, S., Pathak, A. & Gupta, M. Index design and query processing for graph conductance search. The VLDB Journal 20, 445–470 (2011). https://doi.org/10.1007/s00778-010-0204-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00778-010-0204-8

Keywords

Search

Navigation