Data Mining and Knowledge Discovery

, Volume 24, Issue 3, pp 663–696 | Cite as

Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interaction

  • Maristella Agosti
  • Franco Crivellari
  • Giorgio Maria Di Nunzio
Article

Abstract

In the last decade, the importance of analyzing information management systems logs has grown, because log data constitute a relevant aspect in evaluating the quality of such systems. A review of 10 years of research on log analysis is presented in this paper. About 50 papers and posters from five major conferences and about 30 related journal papers have been selected to trace the history of the state-of-the-art in this field. The paper presents an overview of two main themes: Web search engine log analysis and Digital Library System log analysis. The problem of the analysis of different sources of log data and the distribution of data are investigated.

Keywords

Web log Query log Search log User study 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agosti, M (eds) (2008a) Information access through search engines and digital libraries. Springer, BerlinMATHGoogle Scholar
  2. Agosti M (2008b) Log data in digital libraries. In: Agosti M, Esposito F, Thanos C (eds) Post-proceedings of the fourth Italian research conference on digital library systems (IRCDL 2008). DELOS: an Association for Digital Libraries, pp 115–122Google Scholar
  3. Agosti M, Di Nunzio GM (2007) Gathering and mining information from web log files. In: Thanos C, Borri F, Candela L (eds) DELOS conference. Lecture notes in computer science, vol 4877. Springer, pp 104–113Google Scholar
  4. Agosti M, Crivellari F, Di Nunzio GM (2009) A method for combining and analyzing implicit interaction data and explicit preferences of users. In: Doan BL, Jose JM, Melucci M, Tamine-Lechani L (eds) Proceedings of the workshop on contextual information access, seeking and retrieval evaluation (held in conjunction with the 31st European conference on information retrieval—ECIR 2009), pp 13–16Google Scholar
  5. Agosti M, Ferro N, Peters C, de Rijke M, Smeaton AF (eds) (2010) Multilingual and multimodal information access evaluation, international conference of the cross-language evaluation forum, CLEF 2010, Padua, Italy, September 20–23, 2010. Proceedings, lecture notes in computer science, vol 6360. SpringerGoogle Scholar
  6. Anick PG (2003) Using terminological feedback for web search refinement: a log-based study. In: Proceedings of the 26th annual international ACM SIGIR conference on research and development in information retrieval, July 28–August 1, 2003, Toronto, Canada. ACM, pp 88–95Google Scholar
  7. Arya S, Malamatos T, Mount DM (2009) Space-time tradeoffs for approximate nearest neighbor searching. JACM 57: 1–54MathSciNetCrossRefGoogle Scholar
  8. Assadi H, Beauvisage T, Lupovici C, Cloarec T (2003) Users and uses of online digital libraries in France. In: Koch T, Sølvberg I (eds) Proceedings of the 7th European conference on research and advanced technology for digital libraries (ECDL 2003). Lecture notes in computer science, vol 2769. Springer, pp 1–12Google Scholar
  9. Baeza-Yates RA, Ribeiro-Neto B (1999) Modern information retrieval. Addison-Wesley Longman Publishing Co., Inc., BostonGoogle Scholar
  10. Bar-Yossef Z, Gurevich M (2008) Mining search engine query logs via suggestion sampling. PVLDB 1(1): 54–65Google Scholar
  11. Bar-Yossef Z, Gurevich M (2009) Estimating the impressionrank of web pages. In: Quemada J, León G, Maarek YS, Nejdl W (eds) Proceedings of the 18th international conference on World Wide Web, WWW 2009, Madrid, Spain, April 20–24, 2009. ACM, pp 41–50Google Scholar
  12. Beitzel SM, Jensen EC, Chowdhury A, Grossman DA, Frieder O (2004) Hourly analysis of a very large topically categorized web query log. In: Sanderson M, Järvelin K, Allan J, Bruza P (eds) Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, pp 321–328Google Scholar
  13. Beitzel SM, Jensen EC, Chowdhury A, Frieder O, Grossman DA (2007a) Temporal analysis of a very large topically categorized web query log. JASIST 58(2): 166–178CrossRefGoogle Scholar
  14. Beitzel SM, Jensen EC, Lewis DD, Chowdhury A, Frieder O (2007) Automatic classification of web queries using very large unlabeled query logs. ACM Trans Inf Syst 25(2): 9CrossRefGoogle Scholar
  15. Buzikashvili N (2006) An exploratory web log study of multitasking. In: Efthimiadis EN, Dumais ST, Hawking D, Järvelin K (eds) SIGIR 2006: proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval, Seattle, Washington, USA, 2006. ACM, pp 623–624Google Scholar
  16. Buzikashvili N (2007) Sliding window technique for the web log analysis. In: Williamson CL, Zurko ME, Patel-Schneider PF, Shenoy PJ (eds) Proceedings of the 16th international conference on World Wide Web, WWW 2007, Banff, Alberta, Canada, 2007. ACM, pp 1213–1214Google Scholar
  17. Cao H, Jiang D, Pei J, Chen E, Li H (2009) Towards context-aware search by learning a very large variable length hidden markov model from search logs. In: Quemada J, León G, Maarek YS, Nejdl W (eds) Proceedings of the 18th international conference on World Wide Web, WWW 2009, Madrid, Spain, April 20–24, 2009. ACM, pp 191–200Google Scholar
  18. Carman MJ, Baillie M, Gwadera R, Crestani F (2009) A statistical comparison of tag and query logs. In: Allan J, Aslam JA, Sanderson M, Zhai C, Zobel J (eds) Proceedings of the 32nd annual international ACM SIGIR conference on research and development in information retrieval, SIGIR 2009, Boston, MA, USA, July 19–23, 2009. ACM, pp 123–130Google Scholar
  19. Chen R, Rose A, Bederson BB (2009) How people read books online: mining and visualizing web logs for use information. In: Agosti M, Borbinha JL, Kapidakis S, Papatheodorou C, Tsakonas G (eds) Proceedings of the 13th European conference on Research and advanced technology for digital libraries. Lecture notes in computer science, vol 5714. Springer, pp 364–369Google Scholar
  20. Christel MG, Maher B, Li H (2009) Analysis of transaction logs for insights into use of life oral histories. In: Heath F, Rice-Lively ML, Furuta R (eds) Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries, JCDL ’09. ACM, pp 371–372Google Scholar
  21. Chuang SL, Chien LF (2003a) Automatic query taxonomy generation for information retrieval applications. Online Inf Rev 27(4): 243–255CrossRefGoogle Scholar
  22. Chuang SL, Chien LF (2003b) Enriching web taxonomies through subject categorization of query terms from search engine logs. Decis Support Syst 35(1): 113–127CrossRefGoogle Scholar
  23. Chuang SL, Pu HT, Lu WH, Chien LF (2000) Auto-construction of a live thesaurus from search term logs for interactive web search. In: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’00, pp 334–336Google Scholar
  24. Clough P, Berendt B (2009) Report on the TrebleCLEF query log analysis workshop 2009. SIGIR Forum 43(2):71–77. http://doi.acm.org/10.1145/1670564.1670578
  25. Cooper A (2008) A survey of query log privacy-enhancing techniques from a policy perspective. ACM TWEB 2: 19–11927. doi:10.1145/1409220.1409222 Google Scholar
  26. Cui H, Wen JR, Nie JY, Ma WY (2002) Probabilistic query expansion using query logs. In: Proceedings of the 11th international conference on World Wide Web, WWW 2002, WWW ’02, pp 325–332Google Scholar
  27. Cui H, Wen JR, Nie JY, Ma WY (2003) Query expansion by mining user logs. IEEE Trans Knowl Data Eng 15(4): 829–839CrossRefGoogle Scholar
  28. Di Nunzio GM, Leveling J, Mandl T (2011) Multilingual log analysis: Logclef. In: Proceedings of the 33rd European conference on Advances in information retrieval, ECIR’11. Springer-Verlag, Berlin, Heidelberg, pp. 675–678Google Scholar
  29. Freyne J, Smyth B, Coyle M, Balfe E, Briggs P (2004) Further experiments on collaborative ranking in community-based web search. Artif Intell Rev 21(3–4): 229–252CrossRefGoogle Scholar
  30. Fuhr N, Tsakonas G, Aalberg T, Agosti M, Hansen P, Kapidakis S, Klas CP, Kovács L, Landoni M, Micsik A, Papatheodorou C, Peters C, Sølvberg I (2007) Evaluation of digital libraries. Int J Digit Libr 8(1): 21–38CrossRefGoogle Scholar
  31. Gao W, Niu C, Nie JY, Zhou M, Hu J, Wong KF, Hon HW (2007) Cross-lingual query suggestion using query logs of different languages. In: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’07. ACM, New York, pp 463–470. doi:10.1145/1277741.1277821
  32. Gao W, Niu C, Nie JY, Zhou M, Wong KF, Hon HW (2010) Exploiting query logs for cross-lingual query suggestions. ACM Trans Inf Syst 28(2): 1–33CrossRefGoogle Scholar
  33. Gonçalves MA, Fox EA (2002) 5sl: a language for declarative specification and generation of digital libraries. In: Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries, JCDL ’02. ACM, pp 263–272Google Scholar
  34. Gonçalves MA, Luo M, Shen R, Ali MF, Fox EA (2002) An xml log standard and tool for digital library logging analysis. In: Agosti M, Thanos C (eds) Proceedings of the 6th European conference on research and advanced technology for digital libraries. Lecture notes in computer science, vol 2458. Springer, pp 129–143Google Scholar
  35. Gonçalves MA, Panchanathan G, Ravindranathan U, Krowne A, Fox EA, Jagodzinski F, Cassel LN (2003) The XML log standard for digital libraries: analysis, evolution, and deployment. In: Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries, JCDL ’03. IEEE Computer Society, pp 312–314Google Scholar
  36. Grimes C, Tang D, Russell DM (2007) Query logs alone are not enough. In: Amiaty E, Teevan J, Murray GC (eds) Query log analysis: social and technological challenges. A workshop at the 16th international World Wide Web Conference (WWW 2007)Google Scholar
  37. Hopfgartner F (2008) Studying interaction methodologies in video retrieval. PVLDB 1(2): 1604–1608Google Scholar
  38. Hopfgartner F, Urruty T, Villa R, Gildea N, Jose JM (2008) Exploiting log files in video retrieval. In: Larsen RL, Paepcke A, Borbinha JL, Naaman M (eds) Proceedings of the 8th ACM/IEEE-CS joint conference on digital libraries. ACM, p 454Google Scholar
  39. Hu R, Chen W, Bai P, Lu Y, Chen Z, Yang Q (2008) Web query translation via web log mining. In: Myaeng SH, Oard DW, Sebastiani F, Chua TS, Leong MK (eds) Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’08. ACM, pp 749–750Google Scholar
  40. Huang CC, Chuang SL, Chien LF (2004) Using a web-based categorization approach to generate thematic metadata from texts. ACM Trans Asian Lang Inf Process 3(3): 190–212CrossRefGoogle Scholar
  41. Hung CM, Chien LF (2007) Web-based text classification in the absence of manually labeled training documents. JASIST 58(1): 88–96CrossRefGoogle Scholar
  42. Ingwersen P, Järvelin K (2005) The turn. Springer, The NetherlandsMATHGoogle Scholar
  43. Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31(3): 264–323CrossRefGoogle Scholar
  44. Jansen BJ (2006) Search log analysis: what it is, what’s been done, how to do it. Libr Inf Sci Res 28(3):407–432. doi:10.1016/j.lisr.2006.06.005. http://www.sciencedirect.com/science/article/B6W5R-4KSD84F-1/2/d131e3e1b135d3533787b301a941f893
  45. Jones R, Diaz F (2007) Temporal profiles of queries. ACM Trans Inf Syst 25: 14–11431. doi:10.1145/1247715.1247720 CrossRefGoogle Scholar
  46. Jones S, Cunningham SJ, McNab RJ, Boddie SJ (2000) A transaction log analysis of a digital library. Int J Digit Libr 3(2): 152–169CrossRefGoogle Scholar
  47. Jones R, Bartz K, Subasic P, Rey B (2006) Automatically generating related queries in japanese. Lang Resour Eval 40(3–4): 219–232Google Scholar
  48. Jones R, Zhang WV, Rey B, Jhala P, Stipp E (2008) Geographic intention and modification in web search. Int J Geogr Inf Sci 22(3): 229–246CrossRefGoogle Scholar
  49. Kamvar M, Kellar M, Patel R, Xu Y (2009) Computers and iphones and mobile phones, oh my!: a logs-based comparison of search users on different devices. In: Quemada J, León G, Maarek YS, Nejdl W (eds) Proceedings of the 18th international conference on World Wide Web, WWW 2009, Madrid, Spain, April 20–24, 2009. ACM, pp 801–810Google Scholar
  50. Kim S, Murthy U, Ahuja K, Vasile S, Fox EA (2005) Effectiveness of implicit rating data on characterizing users in complex information systems. In: Rauber A, Christodoulakis S, Tjoa AM (eds) Proceedings of Research and Advanced Technology for Digital Libraries, 9th European Conference. Lecture notes in computer science, vol 3652. Springer, pp 186–194Google Scholar
  51. Klas CP, Albrechtsen H, Fuhr N, Hansen P, Kapidakis S, Kovács L, Kriewel S, Micsik A, Papatheodorou C, Tsakonas G, Jacob EK (2006) A logging scheme for comparative digital library evaluation. In: Gonzalo J, Thanos C, Verdejo MF, Carrasco RC (eds) Proceedings of Research and Advanced Technology for Digital Libraries, 10th European Conference. Lecture notes in computer science, vol 4172. Springer, pp 267–278Google Scholar
  52. Kleinberg JM (1999) Authoritative sources in a hyperlinked environment. JACM 46(5): 604–632. doi:10.1145/324133.324140 MathSciNetMATHCrossRefGoogle Scholar
  53. Koch T, Ardö A, Golub K (2004) Browsing and searching behavior in the renardus web service a study based on log analysis. In: Chen H, Wactlar HD, chih Chen C, Lim EP, Christel MG (eds) Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries, JCDL ’04. ACM, p 378Google Scholar
  54. Korolova A, Kenthapadi K, Mishra N, Ntoulas A (2009) Releasing search queries and clicks privately. In: Quemada J, León G, Maarek YS, Nejdl W (eds) Proceedings of the 18th international conference on World Wide Web, WWW 2009, Madrid, Spain, April 20–24, 2009. ACM, pp 171–180Google Scholar
  55. Krauth W, Mezard M (1987) Learning algorithms with optimal stability in neural networks. J Phys A Math Gen 20(11):L745. http://stacks.iop.org/0305-4470/20/i=11/a=013 Google Scholar
  56. Lavrenko V, Croft WB (2001) Relevance-based language models. In: Croft WB, Harper DJ, Kraft DH, Zobel J (eds) SIGIR 2001: Proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval, September 9–13, 2001, New Orleans, LA, USA. ACM, pp 120–127Google Scholar
  57. Levene M (2010) An introduction to search engines and web navigation, 2nd edn. Wiley, UKCrossRefGoogle Scholar
  58. Levenshtein V (1966) Binary codes capable of correcting deletions, insertions, and reversals. Sov Phys Doklady 10(8):707–710. http://sascha.geekheim.de/wp-content/uploads/2006/04/levenshtein.pdf
  59. Mahoui M, Cunningham SJ (2000) A comparative transaction log analysis of two computing collections. In: Borbinha JL, Baker T (eds) Proceedings of research and advanced technology for digital libraries, 4th European conference. Lecture notes in computer science, vol 1923. Springer, pp 418–423Google Scholar
  60. Mahoui M, Cunningham SJ (2001) Search behavior in a research-oriented digital library. In: Constantopoulos P, Sølvberg I (eds) Proceedings of research and advanced technology for digital libraries, 5th European conference. Lecture notes in computer science, vol 2163. Springer, pp 13–24Google Scholar
  61. Mandl T, Agosti M, Di Nunzio G, Yeh A, Mani I, Doran C, Schulz JM (2010) LogCLEF 2009: the CLEF 2009 cross-language logfile analysis track overview. In: Peters C, Di Nunzio G, Kurimo M, Mandl T, Mostefa D, Peñas A, Roda G (eds) Multilingual information access evaluation. Vol I Text retrieval experiments: proceedings 10th workshop of the cross-language evaluation forum, CLEF 2009, Corfu, Greece. LNCS. SpringerGoogle Scholar
  62. Maslov M, Golovko A, Segalovich I, Braslavski P (2006) Extracting news-related queries from web query log. In: Carr L, Roure DD, Iyengar A, Goble CA, Dahlin M (eds) Proceedings of the 15th international conference on World Wide Web, WWW 2006, Edinburgh, Scotland, UK, May 23–26, 2006. ACM, pp 931–932Google Scholar
  63. Miller JC, Rae G, Schaefer F (2001) Modifications of kleinberg’s hits algorithm using matrix exponentiation and weblog records. In: Croft WB, Harper DJ, Kraft DH, Zobel J (eds) SIGIR 2001: proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval, September 9–13, 2001, New Orleans, LA, USA. ACM, pp 444–445Google Scholar
  64. Murray GC, Teevan J (2007) Query log analysis: social and technological challenges. SIGIR Forum 41(2): 112–120CrossRefGoogle Scholar
  65. Parikh J, Kapur S (2006) Unity: relevance feedback using user query logs. In: Efthimiadis EN, Dumais ST, Hawking D, Järvelin K (eds) SIGIR 2006: proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval, Seattle, WA, USA, 2006. ACM, pp 689–690Google Scholar
  66. Pharo N, Järvelin K (2004) The SST method: a tool for analysing Web information search processes. Inf Process Manag 40(4): 633–654CrossRefGoogle Scholar
  67. Poblete B, Spiliopoulou M, Baeza-Yates R (2010) Privacy-preserving query log mining for business confidentiality protection. ACM TWEB 4:10:1–10:26. doi:10.1145/1806916.1806919 Google Scholar
  68. Pu HT, Chuang SL, Yang C (2002) Subject categorization of query terms for exploring web users’ search interests. JASIST 53(8): 617–630CrossRefGoogle Scholar
  69. Sakai T, Nogami K (2009) Serendipitous search via Wikipedia: a query log analysis. In: Allan J, Aslam JA, Sanderson M, Zhai C, Zobel J (eds) Proceedings of the 32nd annual international ACM SIGIR conference on research and development in information retrieval, SIGIR 2009, Boston, MA, USA, July 19–23, 2009. ACM, pp 780–781Google Scholar
  70. Sekine S, Suzuki H (2007) Acquiring ontological knowledge from query logs. In: Williamson CL, Zurko ME, Patel-Schneider PF, Shenoy PJ (eds) Proceedings of the 16th international conference on World Wide Web, WWW 2007, Banff, Alberta, Canada, 2007. ACM, pp 1223–1224Google Scholar
  71. Shi X, Yang CC (2006) Mining related queries from search engine query logs. In: Carr L, Roure DD, Iyengar A, Goble CA, Dahlin M (eds) Proceedings of the 15th international conference on World Wide Web, WWW 2006, Edinburgh, Scotland, UK, May 23–26, 2006. ACM, pp 943–944Google Scholar
  72. Shi X, Yang CC (2007) Mining related queries from web search engine query logs using an improved association rule mining model. JASIST 58(12): 1871–1883MathSciNetCrossRefGoogle Scholar
  73. Smola AJ, Schölkopf B (2004) A tutorial on support vector regression. Stat Comput 14(3): 199–222MathSciNetCrossRefGoogle Scholar
  74. Smyth B, Balfe E (2006) Anonymous personalization in collaborative web search. Inf Retr 9(2): 165–190CrossRefGoogle Scholar
  75. Smyth B, Balfe E, Freyne J, Briggs P, Coyle M, Boydell O (2004) Exploiting query repetition and regularity in an adaptive community-based web search engine. User Model User-Adapt Interact 14(5): 383–423CrossRefGoogle Scholar
  76. Srikant R, Yang Y (2001) Mining web logs to improve website organization. In: WWW 2001, pp 430–437Google Scholar
  77. Subasic I, Berendt B (2010) Discovery of interactive graphs for understanding and searching time-indexed corpora. Knowl Inf Syst 23(3): 293–319CrossRefGoogle Scholar
  78. Sun Y, Xie K, Liu N, Yan S, Zhang B, Chen Z (2007) Causal relation of queries from temporal logs. In: Williamson CL, Zurko ME, Patel-Schneider PF, Shenoy PJ (eds) Proceedings of the 16th international conference on World Wide Web, WWW 2007, Banff, Alberta, Canada, 2007. ACM, pp 1141–1142Google Scholar
  79. Teevan J (2008) How people recall, recognize, and reuse search results. ACM TOIS 26:19:1–19:27. doi:10.1145/1402256.1402258 Google Scholar
  80. Teevan J, Adar E, Jones R, Potts MAS (2006) History repeats itself: repeat queries in yahoo’s logs. In: Efthimiadis EN, Dumais ST, Hawking D, Järvelin K (eds) SIGIR 2006: proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval, Seattle, WA, USA, 2006. ACM, pp 703–704Google Scholar
  81. Teevan J, Adar E, Jones R, Potts MAS (2007) Information re-retrieval: repeat queries in yahoo’s logs. In: Kraaij W, de Vries AP, Clarke CLA, Fuhr N, Kando N (eds) SIGIR 2007: proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval, Amsterdam, The Netherlands, July 23–27, 2007. ACM, pp 151–158Google Scholar
  82. Tolle J (1983) Transactional log analysis: online catalogs. In: Kuehn JJ (ed) Proceedings of the 6th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’83. ACM, pp 147–160Google Scholar
  83. Wang X, Zhai C (2007) Learn from web search logs to organize search results. In: Kraaij W, de Vries AP, Clarke CLA, Fuhr N, Kando N (eds) SIGIR 2007: proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval, Amsterdam, The Netherlands, July 23–27, 2007. ACM, pp 87–94Google Scholar
  84. Wang JH, Teng JW, Lu WH, Chien LF (2006) Exploiting the web as the multilingual corpus for unknown query translation. JASIST 57(5): 660–670CrossRefGoogle Scholar
  85. Wang G, Hu J, Zhu Y, Li H, Chen Z (2009) Competitive analysis from click-through log. In: Quemada J, León G, Maarek YS, Nejdl W (eds) Proceedings of the 18th international conference on World Wide Web, WWW 2009, Madrid, Spain, April 20–24, 2009. ACM, pp 1051–1052Google Scholar
  86. White R, Ruthven I, Jose JM (2002) The use of implicit evidence for relevance feedback in web retrieval. In: Crestani F, Girolami M, van Rijsbergen CJ (eds) ECIR. Lecture notes in computer science, vol 2291. Springer, pp 93–109Google Scholar
  87. White RW, Ruthven I, Jose JM, van Rijsbergen CJ (2005) Evaluating implicit feedback models using searcher simulations. ACM Trans Inf Syst 23(3): 325–361CrossRefGoogle Scholar
  88. White RW, Clarke CLA, Cucerzan S (2007) Comparing query logs and pseudo-relevance feedback for web-search query refinement. In: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’07. ACM, New York, pp 831–832. doi:10.1145/1277741.1277931
  89. Wu LC, Horng JT, Liu BJ, Wang CY, Chen GD (2000) Indexing semistructured data using patricia tree. In: Ibrahim MT, Küng J, Revell N (eds) DEXA. Lecture notes in computer science, vol 1873. Springer, pp 859–868Google Scholar
  90. Xiao X, Luo Q, Li Z, Xie X, Ma WY (2010) A large-scale study on map search logs. TWEB 4(3):8:1–8:33Google Scholar
  91. Zhang Z, Nasraoui O (2006) Mining search engine query logs for query recommendation. In: Carr L, Roure DD, Iyengar A, Goble CA, Dahlin M (eds) Proceedings of the 15th international conference on World Wide Web, WWW 2006, Edinburgh, Scotland, UK, May 23–26, 2006. ACM, pp 1039–1040Google Scholar
  92. Zhang Z, Nasraoui O (2008) Mining search engine query logs for social filtering-based query recommendation. Appl Soft Comput 8(4): 1326–1334CrossRefGoogle Scholar

Copyright information

© The Author(s) 2011

Authors and Affiliations

  • Maristella Agosti
    • 1
  • Franco Crivellari
    • 1
  • Giorgio Maria Di Nunzio
    • 1
  1. 1.Department of Information EngineeringUniversity of PaduaPadovaItaly

Personalised recommendations