Skip to main content

Advertisement

Log in

An interaction model between human and system for intuitive graphical search interface

  • Regular Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

Our objective was to propose a new model which provides real interactions like human conversations. In this paper, we defined “interaction” to mean not only superficial interactions between human and systems but also internal elements inspiring one another. We proposed a new interaction model by defining four user elements namely user knowledge, information needs, thinking, and  feelings, and five system elements namely system knowledge, interaction algorithm, knowledge base, retrieval algorithm, and database. The key point is that users can understand inside the systems gradually and operate them flexibly in their own way to provide real interactions where users and systems inspire one another’s internal elements. We then defined system requirements to realize this model so that users can change and comprehend system knowledge and that users interact with the system constantly. We constructed an image retrieval system applying our proposed graphical search interface named Concentric Ring View and confirmed that all system requirements were satisfied. In a usability test with 12 university students, we confirmed that the proposed interaction model provided intuitive searches to users by inspiring internal elements between users and systems. Users could continuously change and comprehend system knowledge, synchronize user knowledge, shifting thinking and feeling, and changing information needs.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Bandura A (1986) Self-regulation of motivation and action through internal standards and goal system. In: Lawrence AP (ed) Goal concepts in personality and social psychology. Lawrence Erilbaum Association, Hillsdale, NJ, pp 19–85

    Google Scholar 

  2. Baeza-Yates R, Ribeiro-Neto B (1999) Modern information retrieval. Addison-Wesley, Reading, MA

    Google Scholar 

  3. Basu C, Hirsh H, Cohen WW, Nevill-Manning C (2001) Technical paper recommendation: a study in combining multiple information sources. J Artif Intell Res 14(1):231–252

    MATH  Google Scholar 

  4. Bates MJ (1989) The design of browsing and berrypicking techniques for the online search interface. Online Rev 13(5):407–424

    Article  Google Scholar 

  5. Bederson BB (2001) PhotoMesa a zoomable image browser using quantum treemaps and bubblemaps. UIST’01, 71–80. doi:10.1145/502348.502359

  6. Bederson BB, Hollan JD (1994) Pad++: a zooming graphical interface for exploring alternative interface, physics. UIST’94, 17–26. doi:10.1145/192426.192435

  7. Bikakis A, Antoniou G, Hasapis P (2011) Strategies for contextual reasoning with conflicts in ambient intelligence. Knowl Inf Syst 27(1):45–84. doi:10.1007/s10115-010-0293-0

    Article  Google Scholar 

  8. Bilal D (2002) Children’s use of the yahooligans! web search engine: III. Cognitive and physical behaviors on fully self-generated search tasks. J Am Soc Inf Sci Technol 53(13):1170–1183

    Article  Google Scholar 

  9. Bilal D, Kirby J (2002) Differences and similarities in information seeking: children and adults as web users. Inf Process Manag 38(5):649–670

    Article  MATH  Google Scholar 

  10. Brookes BC (1980) The foundation of information science: part 1: philosophical aspects. J Inf Sci 2:125–133

    Google Scholar 

  11. Burke RD, Hammond KJ, Young BC (1996) Knowledge-based navigation of complex information spaces. In: Proceedings of the 13th national conference on, artificial intelligence, pp 462–468

  12. Chen C, Tseng FSC, Liang T (2011) An integration of fuzzy association rules and wordNet for document clustering. Knowl Inf Syst 28(3):687–708. doi:10.1007/s10115-010-0364-2

    Article  Google Scholar 

  13. Choi Y (2010) Effects of contextual factors on image searching on the web. J Am Soc Inf Sci Technol 61(10):2011–2028. doi:10.1002/asi.21386

    Article  Google Scholar 

  14. Cole C (2011) A theory of information need for information retrieval that connects information to knowledge. J Am Soc Inf Sci Technol 72(7):1216–1231. doi:10.1002/asi.21541

    Article  Google Scholar 

  15. Cui J, Liu H, He J, Li P, Du X, Wang P (2011) TagClus: a random walk-based method for tag clustering. Knowl Inf Syst 27(2):193–225. doi:10.1007/s10115-010-0307-y

    Article  MATH  Google Scholar 

  16. Debowski S (2001) Wrong way: go back! An exploration of novice search behaviors while conducting an information search. Electron Libr 19(60):371–382

    Article  Google Scholar 

  17. Dix AJ, Finlay J, Abowd G, Beale R (1998) Human-computer interaction, 2nd edn. Prentice Hall, Englewood Cliffs

  18. Du JT, Spink A (2011) Toward a web search model: integrating multitasking, cognitive coordination, and cognitive shifts. J Am Soc Inf Sci Technol 62(8):1446–1472. doi:10.1002/asi.21551

    Article  Google Scholar 

  19. Furnas GW (1986) Generalized fisheye view. In: SIGCHI’86, pp 16–23

  20. Hansen HP, Draborg E, Kristensen FB (2011) Exploring qualitative research synthesis the role of patients’ perspectives in health policy design and decision making. Patient-Patient Cent Outcomes Res 4(3):143–152. doi:10.2165/11539880-000000000-00000

    Article  Google Scholar 

  21. Hasan MA, Salem S, Zaki MJ (2011) SimClus: an effective algorithm for clustering with a lower bound on similarity. Knowl Inf Syst 28(3):665–685. doi:10.1007/s10115-010-0360-6

    Article  Google Scholar 

  22. Hearst MA (2006) Clustering versus faceted categories for information exploration. Commun ACM 49(4):59–61. doi:10.1145/1121949.1121983

    Article  Google Scholar 

  23. Hjorland B (2011) Theoretical clarity is not ’Manicheanism’: a reply to Marcia Bates. J Inf Sci 37(5):546–550. doi:10.1177/0165551511423169

    Article  Google Scholar 

  24. Hutchinson HB, Bederson BB, Druin A (2006) The evolution of the international children’s digital library searching and browsing interface. In: Proceedings of the 2006 conference on interaction design and, children, pp 105–112

  25. Jakobsen MR, Hornbæk K (2011) Fisheye interfaces—research problems and practical challenges. In: Ebert A, Dix A, Gershon N, Pohl M (eds) Human aspects of visualization, LNCS 6431. Springer, Berlin, pp 76–91

  26. Jiao QG, Onwuegbuzie AJ, Bostick SL (2006) The relationship between race and library anxiety among graduate students: a replication study. Inf Process Manag 42(3):843–851

    Article  Google Scholar 

  27. Jun S, Rho S, Hwang E (2010) Music retrieval and recommendation scheme based on varying mood sequences. Int J Semant Web Inf Syst 6(2):1–16

    Article  Google Scholar 

  28. Kajiyama T, Kando N, Satoh S (2005) Examination and enhancement of a ring-structured graphical search interface based on usability testing. SIGIR’05, pp 623–624. doi:10.1145/1076034.1076159

  29. Kajiyama T, Nakamaru K, Ohno Y, Kando N (2004) Concentric ring view: an interactive environment for integrating searching and browsing. In: Proceedings of the joint 2nd international conference on soft computing and intelligent systems and the 5th international symposium on advanced intelligent systems, 6 p

  30. Keßler C (2012) What is the difference? A cognitive dissimilarity measure for information retrieval result sets. Knowl Inf Syst 30(2):319–340. doi:10.1007/s10115-011-0382-8

    Article  Google Scholar 

  31. Kim JK, Kim HK, Oh HY, Ryu YU (2010) A group recommendation system for online communities. Int J Inf Manag 30(3):212–219

    Article  Google Scholar 

  32. Kuhlthau CC (1988) Seeking meaning: a process approach to library and information services. Ablex, Norwood

    Google Scholar 

  33. Kuhlthau C, Tama S (2001) Information search process of lawyers: a call for “Just for Me” information services. J Doc 57(1):25–43

    Article  Google Scholar 

  34. Matsubara Y, Sakurai Y, Yoshikawa M (2011) D-search: an efficient and exact search algorithm for large distribution sets. Knowl Inf Syst 29(1):131–157. doi:10.1007/s10115-010-0336-6

    Article  Google Scholar 

  35. Onwuegbuzie AJ, Jiao QG (2004) Information search performance and research achievement: an empirical test of the anxiety-expectation mediation model of library anxiety. J Am Soc Inf Sci Technol 55(1):41–54

    Article  Google Scholar 

  36. Pattuelli MC (2011) Modeling a domain ontology for cultural heritage resources: a user-centered approach. J Am Soc Inf Sci Technol 62(2):314–342. doi:10.1002/asi.21453

    Article  Google Scholar 

  37. Pearson M, Moxham T, Ashton K (2011) Effectiveness of search strategies for qualitative research about barriers and facilitators of program delivery, evaluation and the health professions. SI 34(3):297–308. doi:10.1177/0163278710388029

    Google Scholar 

  38. Rose DE, Belew RK (1991) A connectionist and symbolic hybrid for improving legal research. Int J Man Mach Stud 35(1):1–33

    Article  Google Scholar 

  39. Saleh B, Masseglia F (2011) Discovering frequent behaviors: time is an essential element of the context. Knowl Inf Syst 28(2):311–331. doi:10.1007/s10115-010-0361-5

    Article  Google Scholar 

  40. Seifert I (2011) A pool of queries: interactive multidimensional query visualization for information seeking in digital libraries. Inf Vis 10(2):97–106. doi:10.1057/ivs.2011.1

    Article  MathSciNet  Google Scholar 

  41. Serola S, Vakkari P (2005) The anticipated and assessed contribution of information types in references retrieved for preparing a research proposal. J Am Soc Inf Sci Technol 56(4):373–381

    Article  Google Scholar 

  42. Shi Y, Li Z (2011) COID: a cluster-outlier iterative detection approach to multi-dimensional data analysis. Knowl Inf Syst 28(3):709–733. doi:10.1007/s10115-010-0323-y

    Article  Google Scholar 

  43. Smeulders AWM, Worring M, Santini S, Gupta A, Jain R (2000) Content-based image retrieval at the end of the early years. IEEE Trans PAMI 22(12):1349–1379

    Article  Google Scholar 

  44. Smith JR, Chang S-F (1996) Visualseek: a fully automated content-based image query system. In: Proceedings of the 4th ACM international conference on multimedia, MM’96, pp 87–98. doi:10.1145/244130.244151

  45. Taylor RS (1968) Question, negotiation and information seeking in libraries. Coll Res Libr 29:178–194

    Google Scholar 

  46. Vakkari P, Hakala N (2000) Changes in relevance criteria and problem stages in task performance. J Doc 56(5):540–562

    Article  Google Scholar 

  47. Vakkari P, Pennanen M, Serola S (2003) Changes of search terms and tactics while writing a research proposal: a longitudinal case study. Inf Process Manag 39(3):445–463

    Article  Google Scholar 

  48. Vilar P, Zumer M (2011) Information searching behaviour of young Slovenian researchers. Program Electron Libr Inf Syst 45(3):279–293. doi:10.1108/00330331111151593

  49. Wang D, Tse QCK, Zhou Y (2011) A decentralized search engine for dynamic web communities. Knowl Inf Syst 26(1):105–125. doi:10.1007/s10115-009-0270-7

    Article  Google Scholar 

  50. Wang P, Soergel D (1998) A cognitive model of document use during a research project. Study 1. Document selection. J Am Soc Inf Sci 49(2):115–133

    Article  Google Scholar 

  51. Wang Y, Wang C, Lee T, Ma K (2011) Feature-preserving volume data reduction and focus + context visualization. IEEE Trans Vis Comput Graph 17(2):171–181

    Google Scholar 

  52. Wu I (2011) Toward supporting information-seeking and retrieval activities based on evolving topic-needs. J Doc 67(3):525–561. doi:10.1108/00220411111124578

    Article  Google Scholar 

  53. Zeng Y, Zhong N, Wang Y, Qin Y, Huang Z, Zhou H, Yao Y, Harmelen F (2011) User-centric query refinement and processing using granularity-based strategies. Knowl Inf Syst 27(3):419–450. doi:10.1007/s10115-010-0298-8

  54. Zhang J, Marchionini G (2005) Evaluation and evolution of a browse and search interface: relation browser++. In: Proceedings of the 2005 national conference on digital government research, pp 179–188

  55. Zhang M, Hurley N (2010) Niche product retrieval in top-N recommendation. In: 2010 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (WI-IAT), pp 74–81

  56. Zhang R, Tran T (2011) An information gain-based approach for recommending useful product reviews. Knowl Inf Syst 26(3):419–434. doi:10.1007/s10115-010-0287-y

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported in part by Grant-in-Aid for Scientific Research No.19860069 from the Ministry of Education, Culture, Sports, Science and Technology of Japan, Waseda University Grant for Special Research Projects No.2009B-288, and Foundation for the Fusion of Science and Technology of Japan. We greatly appreciate the help of the participants in the usability testing.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tomoko Kajiyama.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kajiyama, T., Satoh, S. An interaction model between human and system for intuitive graphical search interface. Knowl Inf Syst 39, 41–60 (2014). https://doi.org/10.1007/s10115-012-0611-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-012-0611-9

Keywords

Navigation