RESEARCH ARTICLE
A study of visually linked keywords to support exploratory browsing in academic search
Orland Hoeber,
Soumya Shukla,
Corresponding Author
Orland Hoeber
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Correspondence
Orland Hoeber, Department of Computer Science, University of Regina, Regina, SK S4S 0A2, Canada.
Email: [email protected]
Search for more papers by this authorSoumya Shukla
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Search for more papers by this authorOrland Hoeber,
Soumya Shukla,
Corresponding Author
Orland Hoeber
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Correspondence
Orland Hoeber, Department of Computer Science, University of Regina, Regina, SK S4S 0A2, Canada.
Email: [email protected]
Search for more papers by this authorSoumya Shukla
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Search for more papers by this authorFunding information: Natural Sciences and Engineering Research Council of Canada, Grant/Award Number: RGPIN-2017-06446
Abstract
While the search interfaces used by common academic digital libraries provide easy access to a wealth of peer-reviewed literature, their interfaces provide little support for exploratory browsing. When faced with a complex search task (such as one that requires knowledge discovery), exploratory browsing is an important first step in an exploratory search process. To more effectively support exploratory browsing, we have designed and implemented a novel academic digital library search interface (KLink Search) with two new features: visually linked keywords and an interactive workspace. To study the potential value of these features, we have conducted a controlled laboratory study with 32 participants, comparing KLink Search to a baseline digital library search interface modeled after that used by IEEE Xplore. Based on subjective opinions, objective performance, and behavioral data, we show the value of adding lightweight visual and interactive features to academic digital library search interfaces to support exploratory browsing.
REFERENCES
- Ahn, J.-W., Brusilovsky, P., Grady, J., He, D., & Florian, R. (2010). Semantic annotation based exploratory search for information analysts. Information Processing & Management, 46(4), 383–402. https://doi.org/10.1016/j.ipm.2010.02.001
- Belkin, N. (2015). People, interacting with information. SIGIR Forum, 49(2), 13–27. https://doi.org/10.1145/2888422.2888424
10.1145/2888422.2888424 Google Scholar
- Belkin, N., Cool, C., Stein, A., & Thiel, U. (1995). Cases, scripts, and information-seeking strategies: On the design of interactive information retrieval systems. Expert Systems with Applications, 9(3), 379–395. https://doi.org/10.1016/0957-4174(95)00011-W
- Belkin, N., Dumais, S., Scholtz, J., & Wilkinson, R. (2004). Evaluating interactive information retrieval systems: Opportunities and challenges. In Extended Abstracts on Human Factors in Computing Systems (pp. 1594–1595). Association for Computing Machinery. https://doi.org/10.1145/985921.986162
10.1145/985921.986162 Google Scholar
- Bernard, J., Daberkow, D., Fellner, D., Fischer, K., Koepler, O., Kohlhammer, J., Runnwerth, M., Ruppert, T., Schreck, T., & Sens, I. (2015). VisInfo: A digital library system for time series research data based on exploratory search-a user-centered design approach. International Journal on Digital Libraries, 16(1), 37–59. https://doi.org/10.1007/s00799-014-0134-y
10.1007/s00799-014-0134-y Google Scholar
- Bertin, J. (1983). Semiology of graphics: Diagrams, networks, maps. University of Wisconsin Press.
- Borlund, P. (2003). The IIR evaluation model: A framework for evaluation of interactive information retrieval systems. Information Research, 8(2), 3–8.
- Borlund, P., & Ingwersen, P. (1997). The development of a method for the evaluation of interactive information retrieval systems. Journal of Documentation, 3(1–2), 225–250. https://doi.org/10.1561/1500000012
10.1561/1500000012 Google Scholar
- Bostock, M. (2020). Data-driven documents. Retrieved from https://d3js.org/
- Bozzon, A., Brambilla, M., Ceri, S., & Fraternali, P. (2010). Liquid query: Multi-domain exploratory search on the web. In Proceedings of the International Conference on the World Wide Web (pp. 161–170). Association for Computing Machinery. https://doi.org/10.1145/1772690.1772708
10.1145/1772690.1772708 Google Scholar
- Capra, R., Marchionini, G., Velasco-Martin, J., & Muller, K. (2010). Tools-at-hand and learning in multi-session, collaborative search. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (pp. 951–960). Association for Computing Machinery. https://doi.org/10.1145/1753326.1753468
10.1145/1753326.1753468 Google Scholar
- Carpendale, S. (2008). Evaluating information visualizations. In A. Kerren, J. T. Stasko, J.-D. Fekete, & C. North (Eds.), Information visualization: Human-centered issues and perspectives (pp. 19–45). Springer. https://doi.org/10.1007/978-3-540-70956-5
10.1007/978-3-540-70956-5_2 Google Scholar
- Chang, J. C., Hahn, N., Perer, A., & Kittur, A. (2019). SearchLens: Composing and capturing complex user interests for exploratory search. In Proceedings of the International Conference on Intelligent User Interfaces (pp. 498–509). Association for Computing Machinery. https://doi.org/10.1145/3301275.3302321
10.1145/3301275.3302321 Google Scholar
- Choi, B., Arguello, J., Capra, R., & Ward, A. R. (2021). OrgBox: A knowledge representation tool to support complex search tasks. In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 219–228). Association for Computing Machinery. https://doi.org/10.1145/3406522.3446029
10.1145/3406522.3446029 Google Scholar
- Clarkson, E., Desai, K., & Foley, J. (2009). ResultMaps: Visualization for search interfaces. IEEE Transactions on Visualization and Computer Graphics, 15(6), 64–1057. https://doi.org/10.1109/TVCG.2009.176
- Dattolo, A., & Corbatto, M. (2018). VisualBib: Narrative views for customized bibliographies. In Proceedings of International Conference Information Visualisation (pp. 133–138). IEEE. https://doi.org/10.1109/iV.2018.00033
10.1109/iV.2018.00033 Google Scholar
- di Sciascio, C., Brusilovsky, P., & Veas, E. (2018). A study on user-controllable social exploratory search. In Proceedings of the International Conference on Intelligent User Interfaces (pp. 353–364). Association for Computing Machinery. https://doi.org/10.1145/3172944.3172986
10.1145/3172944.3172986 Google Scholar
- di Sciascio, C., Sabol, V., & Veas, E. (2017). Supporting exploratory search with a visual user-driven approach. ACM Transactions on Interactive Intelligent Systems, 7(4), 1–35. https://doi.org/10.1145/3009976
- Dörk, M., Carpendale, S., Collins, C., & Williamson, C. (2008). VisGets: Coordinated visualizations for web-based information exploration and discovery. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1205–1212. https://doi.org/10.1109/TVCG.2008.175
- Federico, P., Heimerl, F., Koch, S., & Miksch, S. (2017). A survey on visual approaches for analyzing scientific literature and patents. IEEE Transactions on Visualization and Computer Graphics, 23(9), 2179–2198. https://doi.org/10.1109/TVCG.2016.2610422
- Furnas, G. W., & Rauch, S. J. (1998). Considerations for information environments and the NaviQue workspace. In Proceedings of the Third ACM Conference on Digital Libraries (pp. 79–88). Association for Computing Machinery. https://doi.org/10.1145/276675.276684
10.1145/276675.276684 Google Scholar
- He, J., Ping, Q., Lou, W., & Chen, C. (2019). PaperPoles: Facilitating adaptive visual exploration of scientific publications by citation links. Journal of the Association for Information Science and Technology, 70(8), 843–857. https://doi.org/10.1002/asi.24171
- Hearst, M. A. (2009). Search user interfaces. Cambridge University Press.
10.1017/CBO9781139644082 Google Scholar
- Hearst, M. A. (2011). User interfaces for search. In R. Baeza-Yates & B. Ribeiro-Neto (Eds.), Modern information retrieval: The concepts and technology behind search engines (pp. 21–56). Cambridge University Press. https://doi.org/10.5555/1796408
- Heimerl, F., John, M., Han, Q., Koch, S., & Ertl, T. (2016). DocuCompass: Effective exploration of document landscapes. In Proceedings of the IEEE Conference on Visual Analytics Science and Technology (pp. 11–20). IEEE. https://doi.org/10.1109/VAST.2016.7883507
10.1109/VAST.2016.7883507 Google Scholar
- Hoeber, O. (2008). Web information retrieval support systems: The future of web search. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (pp. 29–32). Association for Computing Machinery. https://doi.org/10.1109/WIIAT.2008.151
10.1109/WIIAT.2008.151 Google Scholar
- Hoeber, O. (2018). Information visualization for interactive information retrieval. In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 371–374). Association for Computing Machinery. https://doi.org/10.1145/3176349.3176898
10.1145/3176349.3176898 Google Scholar
- Hoeber, O., Hoeber, L., El Meseery, M., Odoh, K., & Gopi, R. (2016). Visual Twitter analytics (Vista): Temporally changing sentiment and the discovery of emergent themes within sport event tweets. Online Information Review, 40(1), 25–41. https://doi.org/10.1108/OIR-02-2015-0067
- Hoeber, O., Patel, D., & Storie, D. (2019). A study of academic search scenarios and information seeking behaviour. In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 231–235). Association for Computing Machinery. https://doi.org/10.1145/3295750.3298943
10.1145/3295750.3298943 Google Scholar
- Hoeber, O., & Yang, X. D. (2008). Evaluating WordBars in exploratory web search scenarios. Information Processing & Management, 44(2), 485–510. https://doi.org/10.1016/j.ipm.2007.07.003
- Hoeber, O., & Yang, X. D. (2009). HotMap: Supporting visual exploration of web search results. Journal of the American Society for Information Science and Technology, 60(1), 90–110. https://doi.org/10.1002/asi.20957
- IEEE. (2019a). IEEE Xplore. Retrieved from https://ieeexplore.ieee.org/Xplore/home.jsp
- IEEE. (2019b). IEEE Xplore API. Retrieved from https://developer.ieee.org/
- Jackson, A., Lin, J., Milligan, I., & Ruest, N. (2016). Desiderata for exploratory search interfaces to web archives in support of scholarly activities. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (pp. 103–106). Association for Computing Machinery. https://doi.org/10.1145/2910896.2910912
10.1145/2910896.2910912 Google Scholar
- Jhaveri, N., & Räihä, K.-J. (2005). The advantages of a cross-session web workspace. In Extended Abstracts on Human Factors in Computing Systems (pp. 1949–1952). Association for Computing Machinery. https://doi.org/10.1145/1056808.1057064
10.1145/1056808.1057064 Google Scholar
- Jiang, T. (2014). Exploratory search: A critical analysis of the theoretical foundations, system features, and research trends. In C. Chen & R. Larsen (Eds.), Library and information sciences: Trends and research (pp. 79–103). Springer. https://doi.org/10.1007/978-3-642-54812-3_7
10.1007/978-3-642-54812-3_7 Google Scholar
- Kang, H., Plaisant, C., Lee, B., & Bederson, B. B. (2006). NetLens: Interative exploration of content-actor network data. In Proceedings of the IEEE Conference on Visual Analytics Science and Technology (pp. 91–98). IEEE. https://doi.org/10.1109/VAST.2006.261426
10.1109/VAST.2006.261426 Google Scholar
- Kangasrääsiö, A., Glowacka, D., & Kaski, S. (2015). Improving controllability and predictability interactive recommendation interfaces for exploratory search. In Proceedings of the International Conference on Intelligent User Interfaces (pp. 247–251). Association for Computing Machinery. https://doi.org/10.1145/2678025.2701371
10.1145/2678025.2701371 Google Scholar
- Kelly, D. (2009). Methods for evaluating interactive information retrieval systems with users. Foundations and Trends in Information Retrieval, 3(1–2), 1–224. https://doi.org/10.1561/1500000012
- Khazaei, T., & Hoeber, O. (2017). Supporting academic search tasks through citation visualization and exploration. International Journal on Digital Libraries, 18(1), 59–72. https://doi.org/10.1007/s00799-016-0170-x
- Koffka, K. (1935). Principles of gestalt psychology. Routledge.
- Krestel, R., Demartini, G., & Herder, E. (2011). Visual interfaces for stimulating exploratory search. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (pp. 393–394). Association for Computing Machinery. https://doi.org/10.1145/1998076.1998151
10.1145/1998076.1998151 Google Scholar
- Kules, B., & Capra, R. (2009). Designing exploratory search tasks for user studies of information seeking support systems. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (pp. 419–420). Association for Computing Machinery. https://doi.org/10.1145/1555400.1555492
10.1145/1555400.1555492 Google Scholar
- Lantz, B. (2013). Equidistance of Likert-type scales and validation of inferential methods using experiments and simulations. Electronic Journal of Business Research Methods, 11(1), 16–28.
- Li, Y., Capra, R., & Zhang, Y. (2020). Everyday cross-session search: How and why do people search across multiple sessions? In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 163–172). Association for Computing Machinery. https://doi.org/10.1145/3343413.3377970
10.1145/3343413.3377970 Google Scholar
- Lin, Y., Ahn, J.-W., Brusilovsky, P., He, D., & Real, W. (2010). ImageSieve: Exploratory search of museum archives with named entity-based faceted browsing. Proceedings of the American Society for Information Science and Technology, 47(1), 1–10. https://doi.org/10.1002/meet.14504701217
10.1002/meet.14504701217 Google Scholar
- Marchionini, G. (2006). Exploratory search: From finding to understanding. Communications of the ACM, 49(4), 41–46. https://doi.org/10.1145/1121949.1121979
- Matejka, J., Grossman, T., & Fitzmaurice, G. (2012). Citeology: Visualizing paper genealogy. In Extended Abstracts on Human Factors in Computing Systems (pp. 181–190). Association for Computing Machinery. https://doi.org/10.1145/2212776.2212796
10.1145/2212776.2212796 Google Scholar
- Medlar, A., Ilves, K., Wang, P., Buntine, W., & Glowacka, D. (2016). PULP: A system for exploratory search of scientific literature. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1133–1136). Association for Computing Machinery. https://doi.org/10.1145/2911451.2911455
10.1145/2911451.2911455 Google Scholar
- Medlar, A., Li, J., & Głowacka, D. (2021). Query suggestions as summarization in exploratory search. In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 119–128). Association for Computing Machinery. https://doi.org/10.1145/3406522.3446020
10.1145/3406522.3446020 Google Scholar
- Nedumov, Y., Babichev, A., Mashonsky, I., & Semina, N. (2019). Scinoon: Exploratory search system for scientific groups. In Joint Proceedings of the ACM IUI 2019 Workshops (pp. 23–27). Association for Computing Machinery.
- OpenJS Foundation. (2020a). About Node JS. Retrieved from https://nodejs.org/en/about/
- OpenJS Foundation. (2020b). Express Node.js web application framework. Retrieved from https://expressjs.com/
- Oracle. (2020). MySQL. Retrieved from https://www.mysql.com/
- Park, H., Myaeng, S. H., Choi, J.-W., Jo, S., & Roh, H.-C. (2008). An interactive information seeking interface for exploratory search. In Proceedings of the International Conference on Enterprise Information Systems (pp. 276–285). Science and Technology Publications. https://doi.org/10.5220/0001711302760285
- Peltonen, J., Belorustceva, K., & Ruotsalo, T. (2017). Topic-relevance map: Visualization for improving search result comprehension. In Proceedings of the International Conference on Intelligent User Interfaces (pp. 611–622). Association for Computing Machinery. https://doi.org/10.1145/3025171.3025223
10.1145/3025171.3025223 Google Scholar
- Peltonen, J., Strahl, J., & Floréen, P. (2017). Negative relevance feedback for exploratory search with visual interactive intent modeling. In Proceedings of the International Conference on Intelligent User Interfaces (pp. 149–159). Association for Computing Machinery. https://doi.org/10.1145/3025171.3025222
10.1145/3025171.3025222 Google Scholar
- Peterson, D. K., & Pitz, G. F. (1988). Confidence, uncertainty, and the use of information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 85–92. https://doi.org/10.1037/0278-7393.14.1.85
- Rotgans, J. I., & Schmidt, H. G. (2017). The relation between individual interest and knowledge acquisition. British Educational Research Journal, 43(2), 350–371. https://doi.org/10.1002/berj.3268
- Ruotsalo, T., Peltonen, J., Eugster, M. J. A., Głowacka, D., Floréen, P., Myllymäki, P., Jacucci, G., & Kaski, S. (2018). Interactive intent modeling for exploratory search. ACM Transactions on Information Systems, 36(4), 44. https://doi.org/10.1145/3231593
- Ruthven, I. (2008). Interactive information retrieval. Annual Review of Information Science and Technology, 42(1), 43–91. https://doi.org/10.1002/aris.2008.1440420109
10.1002/aris.2008.1440420109 Google Scholar
- Sarrafzadeh, B., & Lank, E. (2017). Improving exploratory search experience through hierarchical knowledge graphs. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 145–154). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080829
10.1145/3077136.3080829 Google Scholar
- Scholer, F., & Turpin, A. (2009). Metric and relevance mismatch in retrieval evaluation. In Proceedings of the Asia Information Retrieval Symposium (pp. 50–62).Springer. https://doi.org/10.1007/978-3-642-04769-5_5
10.1007/978-3-642-04769-5_5 Google Scholar
- Shah, C., & González-Ibáñez, R. (2010). Exploring information seeking processes in collaborative search tasks. Proceedings of the American Society for Information Science and Technology, 47(1), 1–7. https://doi.org/10.1002/meet.4504701211
10.1002/meet.4504701211 Google Scholar
- Shukla, S., & Hoeber, O. (2021). Visually linked keywords to support exploratory browsing. In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 273–277). Association for Computing Machinery. https://doi.org/10.1145/3406522.3446037
10.1145/3406522.3446037 Google Scholar
- Spindler, M., & Dachselt, R. (2009). PaperLens: Advanced magic lens interaction above the tabletop. In Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces (pp. 69–76). Association for Computing Machinery. https://doi.org/10.1145/1731903.1731920
10.1145/1731903.1731920 Google Scholar
- Tunkelang, D. (2009). Faceted search. Morgan & Claypool. https://doi.org/10.2200/S00190ED1V01Y200904ICR005
- Vakkari, P. (2003). Task-based information searching. Annual Review of Information Science and Technology, 37(1), 413–464. https://doi.org/10.1002/aris.1440370110
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.5555/2786232.2786234
- Ward, A. R., & Capra, R. (2021). OrgBox: Supporting cognitive metacognitive activities during exploratory search. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2570–2574). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462790
10.1145/3404835.3462790 Google Scholar
- Ward, M. O., Grinstein, G., & Keim, D. (2015). Interactive data visualization: Foundations, techniques, and applications ( 2nd ed.). CRC Press.
10.1201/b18379 Google Scholar
- Ware, C. (2012). Information visualization: Perception for design ( 2nd ed.). Elsevier.
- White, R. W., Kules, B., & Bederson, B. (2005). Exploratory search interfaces: Categorization, clustering and beyond. SIGIR Forum, 39(2), 52–56. https://doi.org/10.1145/1113343.1113356
10.1145/1113343.1113356 Google Scholar
- White, R. W., & Roth, R. A. (2009). Exploratory search: Beyond the query-response paradigm. Morgan & Claypool. https://doi.org/10.2200/S00174ED1V01Y200901ICR003
10.1007/978-3-031-02260-9 Google Scholar
- Wilson, M. (2012). Search user interface design. Morgan & Claypool. https://doi.org/10.2200/S00371ED1V01Y201111ICR020
10.1007/978-3-031-02277-7 Google Scholar
- Yue, Z., Han, S., & He, D. (2014). Modeling search processes using hidden states in collaborative exploratory web search. In Proceedings of the ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 820–830). Association for Computing Machinery. https://doi.org/10.1145/2531602.2531658
10.1145/2531602.2531658 Google Scholar
