Abstract
This paper describes how a system currently developed can be used to connect readers of enhanced e-books both to each other, to web resources and to real world locations and events. A set of Natural Language Processing resources are used to annotate relevant e-books and a framework is developed using the original text and the annotated metadata to detect and display semantic connections within the text and from text to relevant web data. This system can be further enhanced to detect connections between users using common reading interests and habits, their location in relation to locations found in text, and their reading and real world localisation history. Users could also be able to share collected data (text and web references, video and audio recordings, other interested readers) improving an individual reader experience and helping to establish a community around a particular e-book or a real life location with literary significance.
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References
Aggarwal, C.: Text mining in social networks. In: Aggarwal, C. (ed.) Social Network Data Analytics, 2nd edn, pp. 353–374. Springer, Heidelberg (2011)
Irfana, R., Kinga, C.K., Gragesa D., Ewena S., Khana, S.U., Madania, S.A., Kolodzieja, J., Wanga, L., Chena, D,, Rayesa, A, Tziritasa, N., Xua, C., Zomayaa, A.Y., Alzahrania, A.S., and L, H.: A Survey on Text Mining in Social Networks. The Knowledge Engineering Review. Cambridge University Press, Cambridge, pp. 1–24 (2015)
Romero, C., Ventura, S.: Data mining in education. Wiley Interdisc. Rev. Data Min. Knowl. Disc. 3(1), 12–27 (2013)
Hung, J.L., Zhang, K.: Examining mobile learning trends 2003–2008: a categorical meta-trend analysis using text mining techniques. J. Comput. High. Educ. 24(1), 1–17 (2012)
Cambria, E., Schuller, B., Xia, Y., Havasi, C.: New avenues in opinion mining and sentiment analysis. IEEE Intell. Syst. 2, 15–21 (2013)
Netzer, O., Feldman, R., Goldenberg, J., Fresko, M.: Mine your own business: market-structure surveillance through text mining. Mark. Sci. 31(3), 521–543 (2012)
Kraak, M.-J., Rico, V.D.: Principles of hypermaps. Comput. Geosci. 23(4), 457–464 (1997)
Simionescu, R.: UAIC Romanian Part of Speech Tagger, resource on nlptools.info.uaic.ro, “Alexandru Ioan Cuza” University of Iași (2011)
Simionescu, R.: Romanian deep noun phrase chunking using graphical grammar studio. In: Moruz, M.A., Cristea, D., Tufiș, D., Iftene, A., Teodorescu, H.N. (eds.) Proceedings of the 8th International Conference Linguistic Resources and Tools for Processing of the Romanian Language, pp. 135–143 (2012)
Gîfu, D., Vasilache, G.: A language independent named entity recognition system. In: Colhon, M., Iftene, A., Barbu Mititelu, V., Cristea, D., Tufiş, D. (eds.) Proceedings of ConsILR-2014, pp. 181–188, “Alexandru Ioan Cuza” University Publishing House, Iaşi (2014)
Ignat, E.: RARE-UAIC (Robust Anaphora Resolution Engine), open-resource on META-SHARE, “Alexandru Ioan Cuza” University of Iași (2011)
Cristea, D., Postolache, O.: Anaphora resolution: framework, creation of resources, and evaluation. In: Proceedings of the Fifth International Conference Formal Approaches to South Slavic and Balkan Languages, FASSBL-2006, 18–20 October, Sofia, Bulgaria (2006)
Cristea, D., Gîfu, D., Pistol, I., Sfirnaciuc, D., Niculita, M.: A mixed approach in recognising geographical entities in texts. In: Trandabat, D., Gîfu, D. (eds.) EUROLAN 2015. CCIS, vol. 588, pp. 49–63. Springer, Heidelberg (2016). doi:10.1007/978-3-319-32942-0_4
Gîfu, D., Pistol, I., Cristea, D.: Annotation conventions for geographical relations. In: Proceedings of the 11th International Conference Linguistic Resources and Tools for Processing the Romanian Language, ConsILR-2015, pp. 67–78 (2015)
Waterman, D.A., Hayes-Roth, F. (eds.): Pattern-Directed Inference Systems. Academic press, New York (2014)
Acknowledgements
The work reported in this paper was achieved with the support of the PN-II-PT-PCCA-2013-4-1878 Partnership PCCA 2013 grant “MappingBooks - Intră în carte!”, having as partners UAIC, SIVECO and „Ștefan Cel Mare” University of Suceava. We address our thanks to Vivi Năstase for relevant ideas and realisation of Figs. 2 and 3.
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Cristea, D., Pistol, I., Gîfu, D., Anechitei, D. (2016). Networking Readers: Using Semantic and Geographical Links to Enhance e-Books Reading Experience. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_6
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DOI: https://doi.org/10.1007/978-3-319-45246-3_6
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