Abstract
The web has become a major source of information to learn about a topic. With the continuous growth of information and its high connectivity, it is hard to follow only the links that are relevant and not to get lost in hyperspace. Our aim is to support people who read documents in a highly connected information space, helping them remain on focus. Our contextually-aware in-browser text summarisation tool, IBES, does this by capturing users’ current interests and providing users with contextualised summaries of linked documents, to help them decide whether the link is worth following.
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References
Mani, I.: Automatic Summarization. John Benjamins Publishing Company, Amsterdam/Philadelphia (2001)
Salton, G., McGill, M.J.: Introduction to modern information retrieval. McGraw-Hill, New York (1983)
Firmin, T., Chrzanowski, M.J.: An Evaluation of Automatic Text Summarization Systems. In: Manni, I., Maybury, M.T. (eds.) Advances in Automatic Text Summarization, pp. 325–336. MIT Press, Cambridge (1999)
Berkovsky, S., Baldwin, T., Zukerman, I.: Aspect-Based Personalized Text Summarization. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) AH 2008. LNCS, vol. 5149, pp. 267–270. Springer, Heidelberg (2008)
Amitay, E., Paris, C.: Automatically summarising web sites: is there a way around it? In: 9th Int’l Conf. on Information and Knowledge Management (2000)
Teufel, S., Moens, M.: Summarizing scientific articles: experiments with relevance and rhetorical status. Computational Linguistics 28, 409–445 (2002)
Mani, I., Bloedorn, E.: Summarizing similarities and differences among related documents. Information Retrieval 1 (2000)
Sia, K.C., Zhu, S., Chi, Y., Hino, K., Tsen, B.: Capturing User Interests by Both Exploitation and Exploration. In: Conati, C., McCoy, K., Paliouras, G. (eds.) UM 2007. LNCS, vol. 4511, pp. 334–339. Springer, Heidelberg (2007)
Zhang, H., Song, Y., Song, H.: Construction of Ontology-Based User Model for Web Personalisation. In: The 2007 International Conference on User Modelling, pp. 67–76 (2007)
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Paris, C., Wan, S. (2009). Capturing the User’s Reading Context for Tailoring Summaries. In: Houben, GJ., McCalla, G., Pianesi, F., Zancanaro, M. (eds) User Modeling, Adaptation, and Personalization. UMAP 2009. Lecture Notes in Computer Science, vol 5535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02247-0_33
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DOI: https://doi.org/10.1007/978-3-642-02247-0_33
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