Abstract
Exploratory search (in contrary to the traditional lookup search) is characterized by the search tasks that have exploration, learning, and investigation as their goals. An example of this task in the domain of digital libraries is exploration of a new domain, a task that is typically performed by a researcher novice, such as a master’s or a doctoral student. To support the researcher novices in this task, we proposed an approach of exploratory search and navigation using navigation leads, with which we augment the search results, and which serve as navigation starting points allowing users to follow a specific path by filtering only documents pertinent to the selected lead. In this paper, we present a method of selection of navigation leads considering their navigational value in the form of a corpus relevance. We examined this method by the means of an offline evaluation on the dataset from a bookmarking service Annota. We showed that considering the corpus relevance helps to cover significantly more (relevant) documents when conducting the exploratory search. In addition, our relevance metric combining document and corpus relevance of a lead outperformed the popularity metric based on the frequency of the term in the document corpus.
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References
Bates MJ (1989) The design of browsing and berrypicking techniques for the online search interface. Online Rev 13(5):407–424. https://doi.org/10.1108/eb024320
Belkin N, Oddy R, Brooks H (1982a) ASK for information retrieval: part I. Background and theory. J Doc 38(2):61–71. https://doi.org/10.1108/eb026722
Belkin N, Oddy R, Brooks H (1982b) ASK for information retrieval: part II. Results of a design study. J Doc 38(3):145–164. https://doi.org/10.1108/eb026726
Blei DM, Ng AY, Jordan MI (2003) Latent Dirichlet allocation. J Mach Learn Res 3(4–5):993–1022. https://doi.org/10.1162/jmlr.2003.3.4-5.993
Broder A (2002) A taxonomy of web search. ACM SIGIR Forum 36(2):3–10. https://doi.org/10.1145/792550.792552
Carpineto C, Osiński S, Romano G, Weiss D (2009) A survey of web clustering engines. ACM Comput Surv 41(3):1–38. https://doi.org/10.1145/1541880.1541884
Choi D, Matni Z, Shah C (2015) Switching sources: a study of people’s exploratory search behavior on social media and the web. Proc Assoc Inf Sci Technol 52(1):1–10. https://doi.org/10.1002/pra2.2015.145052010045
Cierniak G, Scheiter K, Gerjets P (2009) Explaining the split-attention effect: is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Comput Hum Behav 25(2):315–324. https://doi.org/10.1016/j.chb.2008.12.020
Cutting DR, Karger DR, Pedersen JO, Tukey JW (1992) Scatter/gather: a cluster-based approach to browsing large document collections. In: SIGIR ’92: Proceedings of the 15th annual international ACM SIGIR conference on research and development in information retrieval, ACM Press, NY, USA, pp 318–329. https://doi.org/10.1145/133160.133214
Dervin B, Foreman-Wernet L, Lauterbach E (2003) Sense-making methodology reader: selected writings of Brenda Dervin. Communication alternatives. Hampton Press, New York
Dimitrov D, Singer P, Helic D, Strohmaier M (2015) The role of structural information for designing navigational user interfaces. In: Proceedings of the 26th ACM conference on hypertext and social media—HT’15, ACM Press, NY, USA, pp 59–68. https://doi.org/10.1145/2700171.2791025
Dimitrov D, Helic D, Strohmaier M (2018) Tag-based navigation and visualization. In: Brusilovsky P, He D (eds) Social information access, vol 10100. Springer, Berlin, pp 181–212. https://doi.org/10.1007/978-3-319-90092-6_6
Golovchinsky G, Diriye A, Dunnigan T (2012) The future is in the past: designing for exploratory search. In: Proceedings of the 4th information interaction in context symposium on—IIIX ’12, ACM Press, NY, USA, pp 52–61. https://doi.org/10.1145/2362724.2362738
Helic D, Trattner C, Strohmaier M, Andrews K (2011) Are tag clouds useful for navigation? A network-theoretic analysis. Int J Soc Comput Cyber Phys Syst 1(1):33–55. https://doi.org/10.1504/IJSCCPS.2011.043603
Helic D, Strohmaier M, Granitzer M, Scherer R (2013) Models of human navigation in information networks based on decentralized search. In: Proceedings of the 24th ACM conference on hypertext and social media—HT ’13, ACM Press, New York, USA, pp 89–98. https://doi.org/10.1145/2481492.2481502
Holub M, Moro R, Sevcech J, Liptak M, Bielikova M (2014) Annota: towards enriching scientific publications with semantics and user annotations. D-Lib Mag. https://doi.org/10.1045/november14-holub
Ingwersen P, Järvelin K (2005) The turn: integration of information seeking and retrieval in context. Springer, Dordrecht
Jiang D, Leung KWT, Yang L, Ng W (2015) Query suggestion with diversification and personalization. Knowl Based Syst 89:553–568. https://doi.org/10.1016/j.knosys.2015.09.003
Jin X, Sloan M, Wang J (2013) Interactive exploratory search for multi page search results. In: Proceedings of the 22nd international conference on world wide web—WWW ’13, IW3C2, Geneva, Switzerland, pp 655–665
Klein G, Moon B, Hoffman R (2006) Making sense of sensemaking 2: a macrocognitive model. Intell Syst 21:88–92
Kong W, Allan J (2014) Extending faceted search to the general web. In: Proceedings of the 23rd ACM international conference on information and knowledge management—CIKM ’14, ACM Press, NY, USA, pp 839–848. https://doi.org/10.1145/2661829.2661964
Kramár T, Barla M, Bieliková M (2013) Personalizing search using socially enhanced interest model, built from the stream of user’s activity. J Web Eng 12(1–2):65–92
Kuhlthau CC (2009) Information search process. J Financ Serv Mark. https://doi.org/10.1057/fsm.2010.5
Kules B, Capra R, Banta M, Sierra T (2009) What do exploratory searchers look at in a faceted search interface? In: Proceedings of the 9th ACM/IEEE-CS joint conference on digital libraries—JCDL’09, ACM Press, NY, USA, pp 313–322. https://doi.org/10.1145/1555400.1555452
Maglio PP, Matlock T (1999) The conceptual structure of information space. In: Munro AJ, Höök K, Benyon D (eds) Social navigation of information space. Springer, London, pp 155–173. https://doi.org/10.1007/978-1-4471-0837-5_9
Makri S, Blandford A (2012a) Coming across information serendipitously: part 2—a classification framework. J Doc 68(5):706–724
Makri S, Blandford A (2012b) Coming across information serendipitously—part 1: a process model. J Doc 68(5):684–705. https://doi.org/10.1108/00220411211256030
Marchionini G (2006) Exploratory search: from finding to understanding. Commun ACM 49(4):41–46. https://doi.org/10.1145/1121949.1121979
Moro R, Bielikova M (2015) Navigation leads selection considering navigational value of keywords. In: WWW ’15 Companion: proceedings of the 24th international conference on world wide web companion, 18–22 May, 2015, Florence, Italy, IW3C2, Geneva, pp 79–80. https://doi.org/10.1145/2740908.2742764
Moro R, Vangel M, Bielikova M (2016) Identification of navigation lead candidates using citation and co-citation analysis. In: Proceedings of the 42nd international conference on current trends in theory and practice of computer science—SOFSEM ’16, LNCS 9587, Springer, Berlin, pp 556–568
Návrat P (2012) Cognitive traveling in digital space: from keyword search through exploratory information seeking. Cent Eur J Comput Sci 2(3):170–182. https://doi.org/10.2478/s13537-012-0024-6
Niu X, Hemminger B (2015) Analyzing the Interaction Patterns in a Faceted Search Interface. J Assoc Inf Sci Technol 66(5):1030–1047. https://doi.org/10.1002/asi
Olston C, Chi EH (2003) ScentTrails: integrating browsing and searching on the web. ACM Trans Comput Hum Interact 10(3):177–197
Ozertem U, Chapelle O, Donmez P, Velipasaoglu E (2012) Learning to suggest: a machine learning framework for ranking query suggestions. In: Proceedings of the 35th international ACM SIGIR conference on research and development in information retrieval—SIGIR ’12, ACM Press, NY, USA, pp 25 –34. https://doi.org/10.1145/2348283.2348290
Pääkkönen T, Kekäläinen J, Keskustalo H, Azzopardi L, Maxwell D, Järvelin K (2017) Validating simulated interaction for retrieval evaluation. Inf Retr J 20(4):338–362. https://doi.org/10.1007/s10791-017-9301-2
Pandit S, Olston C (2007) Navigation-aided retrieval. In: Proceedings of the 16th international conference on world wide web—WWW’07, ACM Press, NY, USA, pp 391–400. https://doi.org/10.1145/1242572.1242626
Panigrahi D, Das Sarma A, Aggarwal G, Tomkins A (2012) Online selection of diverse results. In: Proceedings of the 5th ACM international conference on web search and data mining—WSDM ’12, ACM Press, NY, USA, pp 263–272. https://doi.org/10.1145/2124295.2124329
Pirolli P, Card SK (1999) Information foraging. Psychol Rev 106:643–675
Ren P, Chen Z, Ma J, Wang S, Zhang Z, Ren Z, Ma T (2018) User session level diverse reranking of search results. Neurocomputing 274:66–79. https://doi.org/10.1016/j.neucom.2016.05.087
Russell DM, Stefik MJ, Pirolli P, Card SK (1993) The cost structure of sensemaking. In: Proceedings of the SIGCHI conference on Human factors in computing systems—CHI ’93, ACM Press, New York, USA, pp 269–276. https://doi.org/10.1145/169059.169209
Sacco GM, Tzitzikas Y (2009) Dynamic taxonomies and faceted search: theory, practice, and experience, the information retrieval series, vol 25. Springer, Berlin. https://doi.org/10.1007/978-3-642-02359-0
Santos RLT, Macdonald C, Ounis I (2012) Learning to rank query suggestions for adhoc and diversity search. Inf Retr 16(4):429–451. https://doi.org/10.1007/s10791-012-9211-2
Ševcech J, Bieliková M (2014) User’s interest detection through eye tracking for related documents retrieval. In: Proceedings of the 9th international workshop on semantic and social media adaptation and personalization—Sofsem ’14, IEEE, pp 9–13. https://doi.org/10.1109/SMAP.2014.20
Ševcech J, Móro R, Holub M, Bieliková M (2014) User annotations as a context for related document search on the web and digital libraries. Informatica (Slovenia) 38(1):21
Shah C, González-Ibáñez R (2011) Evaluating the synergic effect of collaboration in information seeking. In: Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval—SIGIR’11, pp 913–922. https://doi.org/10.1145/2009916.2010038
Shah C, Hendahewa C, González-Ibáñez R (2015) Two’s company, but three’s no crowd. Aslib J Inf Manag 67(6):636–662. https://doi.org/10.1108/AJIM-05-2015-0082
Singer P, Helic D, Taraghi B, Strohmaier M (2014) Detecting memory and structure in human navigation patterns using Markov chain models of varying order. PLoS ONE. https://doi.org/10.1371/journal.pone.0102070
Singer P, Helic D, Hotho A, Strohmaier M (2017) A Bayesian method for comparing hypotheses about human trails. ACM Trans Web 11(3):1–29. https://doi.org/10.1145/3054950
Skoutas D, Alrifai M (2011) Tag clouds revisited. In: Proceedings of the 20th ACM international conference on information and knowledge management—CIKM’11, ACM Press, NY, USA, pp 221–230. https://doi.org/10.1145/2063576.2063613
Stolz A, Hepp M (2015) Adaptive faceted search for product comparison on the web of data. In: Proceedings of the 15th international conference on web engineering—ICWE’15, LNCS 9114, Springer, pp 420–429. https://doi.org/10.1007/978-3-319-19890-3_27
Sun H, Jiang C, Ding Z, Wang P, Zhou M (2016) Topic-oriented exploratory search based on an indexing network. IEEE Trans Syst Man Cybern Syst 46(2):234–247. https://doi.org/10.1109/TSMC.2015.2421484
Tague-Sutcliffe J (1995) Measuring information: an information services perspective. Library and information science. Academic Press, Amsterdam
Trattner C, Helic D, Singer P, Strohmaier M (2012) Exploring the differences and similarities between hierarchical decentralized search and human navigation in information networks. In: Proceedings of the 12th international conference on knowledge management and knowledge technologies—i-KNOW ’12, ACM Press, New York, USA, p 8. https://doi.org/10.1145/2362456.2362474
Tvarožek M, Bieliková M (2010) Generating exploratory search interfaces for the semantic web. In: Human–computer interaction, IFIP advances in information and communication technology, vol 332, pp 175–186
Umemoto K, Yamamoto T, Tanaka K (2016) ScentBar: a query suggestion interface visualizing the amount of missed relevant information for intrinsically diverse search. In: Proceedings of the 39th international ACM SIGIR conference on research and development in information retrieval—SIGIR ’16, ACM Press, New York, New York, USA, pp 405–414. https://doi.org/10.1145/2911451.2911546
Verberne S, Sappelli M, Järvelin K, Kraaij W (2015) User simulations for interactive search: evaluating personalized query suggestion. In: Proceedings of the 37th European conference on IR research—ECIR 2015, LNCS 9022, Springer International Publishing, pp 678–690. https://doi.org/10.1007/978-3-319-16354-3_75
Vnenk L, Bielikova M (2014) Searcher’s activity in standalone and web applications as a source for search query expansion. In: Proceedings—2014 European network intelligence conference, ENIC 2014, pp 75–80. https://doi.org/10.1109/ENIC.2014.19
White RW, Roth RA (2009) Exploratory search: beyond the query–response paradigm, vol 1. Morgan & Claypool, San Rafael. https://doi.org/10.2200/S00174ED1V01Y200901ICR003
Wilson T (1999) Models in information behaviour research. J Doc 55(3):249–270
Yu HT, Jatowt A, Blanco R, Joho H, Jose JM, Chen L, Yuan F (2018) Revisiting the cluster-based paradigm for implicit search result diversification. Inf Process Manag 54(4):507–528. https://doi.org/10.1016/j.ipm.2018.03.003
Yuan X, White R (2012) Building the trail best traveled: effects of domain knowledge on web search trailblazing. In: Proceedings of the 2012 ACM annual conference on human factors in computing systems—CHI ’12, ACM Press, New York, USA, pp 1795–1804. https://doi.org/10.1145/2207676.2208312
Yue Z, Han S, He D (2014) Modeling search processes using hidden states in collaborative exploratory web search. In: Proceedings of the 17th ACM conference on computer supported cooperative work and social computing—-CSCW’14, ACM Press, NY, USA, pp 820–830. https://doi.org/10.1145/2531602.2531658
Zhang P, Soergel D, Klavans JL, Oard DW (2009) Extending sense-making models with ideas from cognition and learning theories. Proc Am Soc Inf Sci Technol 45(1):23–23. https://doi.org/10.1002/meet.2008.1450450219
Acknowledgements
This work was partially supported by the Scientific Grant Agency of the Slovak Republic, Grant Nos. VG 1/0667/18 and VG 1/0725/19, Slovak Research and Development Agency under the Contract No. APVV-15-0508, European Regional Development Fund, Grant Nos. ITMS 26240120039 and ITMS 26240220084. The authors also wish to thank our colleagues that contributed to the development of Annota and its dataset, which was used for evaluation of this work, namely Michal Holub, Jakub Sevcech, Martin Liptak, and Juraj Kostolansky.
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Moro, R., Bielikova, M. Navigation leads for exploratory search and navigation in digital libraries. Knowl Inf Syst 62, 2739–2764 (2020). https://doi.org/10.1007/s10115-019-01434-2
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DOI: https://doi.org/10.1007/s10115-019-01434-2