Abstract
Mind-maps have been widely neglected by the information retrieval (IR) community. However, there are an estimated two million active mind-map users, who create 5 million mind-maps every year, of which a total of 300,000 is publicly available. We believe this to be a rich source for information retrieval applications, and present eight ideas on how mind-maps could be utilized by them. For instance, mind-maps could be utilized to generate user models for recommender systems or expert search, or to calculate relatedness of web-pages that are linked in mind-maps. We evaluated the feasibility of the eight ideas, based on estimates of the number of available mind-maps, an analysis of the content of mind-maps, and an evaluation of the users’ acceptance of the ideas. We concluded that user modelling is the most promising application with respect to mind-maps. A user modelling prototype – a recommender system for the users of our mind-mapping software Docear – was implemented, and evaluated. Depending on the applied user modelling approaches, the effectiveness, i.e. click-through rate on recommendations, varied between 0.28% and 6.24%. This indicates that mind-map based user modelling is promising, but not trivial, and that further research is required to increase effectiveness.
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References
Google: Ads in Gmail and your personal data (2012), https://support.google.com/mail/answer/6603
Zubiaga, A., Martinez, R., Fresno, V.: Getting the most out of social annotations for web page classification. In: Proceedings of the 9th ACM Symposium on Document Engineering, pp. 74–83 (2009)
Jacso, P.: Testing the calculation of a realistic h-index in Google Scholar, Scopus, and Web of Science for FW Lancaster. Library Trends 56, 784–815 (2008)
Beel, J., Langer, S., Genzmehr, M., Nürnberger, A.: Introducing Docear’s Research Paper Recommender System. In: Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2013, pp. 459–460. ACM (2013)
Beel, J., Gipp, B., Langer, S., Genzmehr, M.: Docear: An Academic Literature Suite for Searching, Organizing and Creating Academic Literature. In: Proceedings of the 11th International ACM/IEEE Conference on Digital Libraries, pp. 465–466. ACM (2011)
Nesbit, J.C., Adesope, O.O.: Learning with concept and knowledge maps: A meta-analysis. Review of Educational Research 76, 413 (2006)
Brucks, C., Schommer, C.: Assembling Actor-based Mind-Maps from Text Stream. arXiv preprint (abs/0810.4616) (2008).
Mahler, T., Weber, M.: Dimian-Direct Manipulation and Interaction in Pen Based Mind Mapping. In: Proceedings of the 17th World Congress on Ergonomics, IEA 2009 (2009)
Beel, J., Langer, S.: An Exploratory Analysis of Mind Maps. In: Proceedings of the 11th ACM Symposium on Document Engineering, DocEng 2011, pp. 81–84. ACM (2011)
Beel, J., Gipp, B., Stiller, J.-O.: Information Retrieval on Mind Maps - What could it be good for? In: Proceedings of the 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2009, pp. 1–4 (2009)
Gipp, B., Beel, J.: Citation Proximity Analysis (CPA) - A new approach for identifying related work based on Co-Citation Analysis. In: Proceedings of the 12th International Conference on Scientometrics and Informetrics ISSI 2009, pp. 571–575. International Society for Scientometrics and Informetrics, Rio de Janeiro (2009)
Chi, Y., Tseng, B.L., Tatemura, J.: Eigen-trend: trend analysis in the blogosphere based on singular value decompositions. In: Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pp. 68–77. ACM (2006)
Beel, J., Gipp, B., Mueller, C.: SciPlore MindMapping’ - A Tool for Creating Mind Maps Combined with PDF and Reference Management. D-Lib Magazine 15 (2009)
Google: Annual Report (2010), http://investor.google.com/pdf/2010_google_annual_report.pdf
Kiwitobes: Lessons on recommendation systems. Blog (2011), http://blog.kiwitobes.com/?p=58
Rich, E.: User modeling via stereotypes. Cognitive science 3, 329–354 (1979)
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Beel, J., Langer, S., Genzmehr, M., Gipp, B. (2014). Utilizing Mind-Maps for Information Retrieval and User Modelling. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, GJ. (eds) User Modeling, Adaptation, and Personalization. UMAP 2014. Lecture Notes in Computer Science, vol 8538. Springer, Cham. https://doi.org/10.1007/978-3-319-08786-3_26
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DOI: https://doi.org/10.1007/978-3-319-08786-3_26
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