Advertisement

Unified Retrieval Model of Big Data

  • Asma Al-DreesEmail author
  • Reem Bin-Hezam
  • Ruba Al-Muwayshir
  • Wafa’ Haddoush
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 529)

Abstract

With the huge growth of big data, effective information retrieval methods have gained research focus. This paper addresses the difficulty of retrieving relevant information for a large system that involves fusion of data. We propose a retrieval model to enhance and improve the retrieving process along with the user’s metadata learning to develop and enhance a retrieval system.

Keywords

Big data Indexing data Storage Retrieval model Challenges and issues Location-based service Metadata 

References

  1. 1.
    Agrawal, D., Bernstein, P., Davidson, S.: Challenges and Opportunities with Big Data. A community white paper developed by leading researchers across the United States, p. 17 (2011)Google Scholar
  2. 2.
    Arai, A., Fujikawa, K., Sunahara, H.: A proposal of information retrieval method based on TPO metadata (2009)Google Scholar
  3. 3.
    Bakshi, K.: Considerations for Big Data: Architecture and Approach (2012)Google Scholar
  4. 4.
    Begoli, E., Horey, J.: Design principles for effective knowledge discovery from big data. In: Joint Working Conference on Software Architecture & 6th European Conference on Software Architecture, p. 4 (2012)Google Scholar
  5. 5.
    Big Data for Development: Challenges & Opportunities. Global Pluse, 47 (2012)Google Scholar
  6. 6.
    Big Data Survey. Giga Spaces, 5 (2011)Google Scholar
  7. 7.
    Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, 156 (2011)Google Scholar
  8. 8.
    Bindra, A., Ashish Bindra, S., Ashish Bindra, K.: Distributed big advertiser data mining. In: IEEE 12th International Conference on Data Mining Workshops, p. 1 (2012)Google Scholar
  9. 9.
    Borkar, V., Carey, M.J., Li, C.: Inside “Big Data Management”: ogres, onions, or parfaits? In: EDBT/ICDT 2012 Joint Conference, Berlin, Germany, p. 12 (2012)Google Scholar
  10. 10.
    Cavoukian, A.: Privacy, security, big data–yes, you can! In: Information and Privacy Commissioner Ontario, Canada, p. 26 (2013)Google Scholar
  11. 11.
    Chandramouli, B., Goldstein, J., Duan, S.: Temporal analytics on big data for web advertising. In: IEEE 28th International Conference on Data Engineering, p. 12 (2012)Google Scholar
  12. 12.
    Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. Bus. Intell. Res., 25 (2012)Google Scholar
  13. 13.
    Clement, M., Sokol, L., Gary, L.: Robust decision engineering: collaborative big data and its application to international development/aid. In: 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing, p. 8 (2012)Google Scholar
  14. 14.
    CS4103 Distributed Systems Coursework Part 1: Big Data (2012)Google Scholar
  15. 15.
    Demchenko, Y., Zhao, Z., Grosso, P., Wibisono, A., de Laat, C.: Addressing big data challenges for scientific data infrastructure. In: IEEE 4th International Conference on Cloud Computing Technology and Science, p. 4 (2012)Google Scholar
  16. 16.
    Distributed Systems Coursework Part 1: Big Data (2012). http://www.luisramalho.com/wp-content/uploads/2012/04/bigdata.pdf
  17. 17.
    Dumbill, E.: Making sense of big data. 2BD, 2 (2013)Google Scholar
  18. 18.
    Geron, T.: Live: Facebook Launches Graph Search, A Social Search Engine, With Bing Partnership (2013). http://www.forbes.com/sites/tomiogeron/2013/01/15/live-facebook-announces-graph-search/
  19. 19.
    Greengrass, E.D.: Information Retrieval: A Survey (2000)Google Scholar
  20. 20.
    Guo, Z., Wang, J.: Information Retrieval from Large Data Sets via Multiple-winners-take-all (2011)Google Scholar
  21. 21.
    Han, X., Tian, L., Yoon, M., Lee, M.: A big data model supporting information recommendation in social networks. In: Second International Conference on Cloud and Green Computing, p. 4 (2012)Google Scholar
  22. 22.
    HPCC Systems (n.d.). HPCC Systems: Models for Big Data. White paper, 17Google Scholar
  23. 23.
    IBM big data success stories. IBM Corporation, 76 (2011)Google Scholar
  24. 24.
    Intel IT Center. Big Data Analytics. Intel’s IT Manager Survey on How Organizations are Using Big Data, 27 (2012)Google Scholar
  25. 25.
    Jain, M., Singh, S.K.: A survey on: content based image retrieval systems using clustering techniques for large data sets. Int. J. Manag. Inf. Technol. (IJMIT) 3(4), 17 (2011)Google Scholar
  26. 26.
    Ji, C., Li,, Y., Qiu, W., Awada, U., Li, K.: Big data processing in cloud computing environments. In: International Symposium on Pervasive Systems, Algorithms and Networks, p. 7 (2012)Google Scholar
  27. 27.
    Borrero, J.D., Gualda, E.: Crawling big data in a new frontier for socioeconomic research: testing with social tagging. J. Spat. Organ. Dyn. - Discussion Papers Number 12, 23 (2012)Google Scholar
  28. 28.
    Kaisler, S., Armour, F., Alberto Espinosa, J., Money, W.: Big data: issues and challenges moving forward. In: 46th Hawaii International Conference on System Sciences, p. 10 (2013)Google Scholar
  29. 29.
    Kejariwal, A.: Big data challenges a program optimization perspective. In: Second International Conference on Cloud and Green Computing, p. 6 (2012)Google Scholar
  30. 30.
    Kirkpatrick, R.: BIG data for development. BD3, 1(1), 2 (2013)Google Scholar
  31. 31.
    Kraska, T.: Finding the Needle in the Big Data Systems Haystack, p. 3. Brown University (2013)Google Scholar
  32. 32.
    Laurila, J.K., Imad Aad, I., Perez, D.J. (n.d.).: The Mobile Data Challenge: Big Data for Mobile Computing ResearchGoogle Scholar
  33. 33.
    Lioma, C.: Big Data Challenges for Information Retrieval. University of Copenhagen- Department of Computer Science, p. 12 (2012)Google Scholar
  34. 34.
    Logothetis, D., Yocum, K.: Data Indexing for Stateful, Large-scale Data Processing (2009)Google Scholar
  35. 35.
    Lumley, T., Rice, K.: Storing and retrieving large data. UW Biostatistics, p. 18 (2009)Google Scholar
  36. 36.
    Meij, E.: Large-scale Data Processing for Information Retrieval #nlhug, 12 April 2012. http://www.slideshare.net/edgar.meij/largescale-data-processing-for-information-retrieval-nlhug. (Retrieved)
  37. 37.
    Miller, S.: How “Big Data” will change your life….. Pew Research Center’s Internet & American Life Project, p. 29 (2012)Google Scholar
  38. 38.
    Nambiar, U.: Answering Imprecise Queries Over Autonomous Databases (2005). http://rakaposhi.eas.asu.edu/ullas-thesis.pdf. (Retrieved)
  39. 39.
    Navint Enterprise. Why is BIG Data Important?. A Navint Partners White Paper, 5 (2012). www.navint.com. (Retrieved)
  40. 40.
    Oracle Information Architecture: An Architect’s Guide to Big Data. An Oracle White Paper in Enterprise Architecture, 25 (2012)Google Scholar
  41. 41.
    Oracle. Oracle: Big data for Enterprise. Oracle Enterprise, 16 (2012)Google Scholar
  42. 42.
    Oracle. Combining big data tools with traditional data management offers enterprises the complete view. White paper: Integrate for Insight, 4 (2012)Google Scholar
  43. 43.
    Part III: IBM’s strategy for big data and analytics. IBM Corporation, 5 (2012)Google Scholar
  44. 44.
    Bennett, P.N., El-Arini, K.: Enriching Information Retrieval. In: SIGIR Workshop Report, p. 6 (2011)Google Scholar
  45. 45.
    Paz-Trillo, C., Wassermann, R., Braga, P.P.: An Information Retrieval application using Ontologies (2005). http://www.ime.usp.br/~rmcobe/onair/files/jsbc_onair.pdf
  46. 46.
    Provost, F., Fawcett, T.: DATA science and its relationship to big data and data-driven decision making. BD51 1(1), 9 (2013)Google Scholar
  47. 47.
    Rabinowitz, J.: Indexing arbitrary data with SWISH-E. In: The Proceedings of the 2004 USENIX Technical Conference, p. 7 (2004)Google Scholar
  48. 48.
  49. 49.
    Rouse, M.: What is Graph Search? (2013). http://whatis.techtarget.com/definition/Graph-Search
  50. 50.
    Smith, M., Szongott, S., Henne, B., Voigt, G.: Big Data Privacy Issues in Public Social Media (2013)Google Scholar
  51. 51.
    Sun Yanhou, Y.: Big data in enterprise challenges & opportunities. Software and Service Group, p. 15 (2011)Google Scholar
  52. 52.
    Venkatraman, S., Kamatkar, S.J.: Intelligent information retrieval and recommender system framework. Int. J. Future Comput. Commun. 2(2), 5 (2013)Google Scholar
  53. 53.
    Zhu, J.: Data Modeling for Big Data (2011)Google Scholar
  54. 54.
    Zhou, B., Yao, Y.: Evaluating Information Retrieval System Performance Based on User Preference. http://www2.cs.uregina.ca/~zhou200b/4-zhou.pdf
  55. 55.
    Zikopoulos, P., Deustch, T.: The big deal about big data. IBM Corporation, 43 (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Asma Al-Drees
    • 1
    Email author
  • Reem Bin-Hezam
    • 2
  • Ruba Al-Muwayshir
    • 3
  • Wafa’ Haddoush
    • 4
  1. 1.Information Systems Department, College of Computer and Information SciencesKing Khaled UniversityAbhaSaudi Arabia
  2. 2.Princess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia
  3. 3.Information Systems Department, College of Computer and Information SciencesAljouf UniversitySakakahSaudi Arabia
  4. 4.Information Systems Department, College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

Personalised recommendations