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Information Finding with Robust Entity Detection: The Case of an Online News Reader

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Human-Computer Interaction: The Agency Perspective

Part of the book series: Studies in Computational Intelligence ((SCI,volume 396))

Abstract

Journalists and editors work under tight deadlines and are forced to gather as much background and details as they can about a particular situation or event. They have to keep track of useful sources and they have to be able to record what aspects and what portions of the source provided useful information.

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References

  1. Budzik, J., Hammond, K.J., Birnbaum, L.: Information access in context. Knowledge-Based Systems 14(1-2), 37–53 (2001), http://dx.doi.org/10.1016/S0950-70510000105-2

    Article  Google Scholar 

  2. Downey, D., Broadhead, M., Etzioni, O.: Locating complex named entities in web text. In: Proc. of IJCAI (2007), http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.6523

  3. Etzioni, O., Cafarella, M., Downey, D., Popescu, A.M., Shaked, T., Soderland, S., Weld, D.S., Yates, A.: Unsupervised named-entity extraction from the web: an experimental study. Artif. Intell. 165(1), 91–134 (2005), http://dx.doi.org/10.1016/j.artint.2005.03.001 ; doi:10.1016/j.artint.2005.03.001

    Article  Google Scholar 

  4. Fredkin, E.: Trie memory. Commun. ACM 3(9), 490–499 (1960), http://dx.doi.org/10.1145/367390.367400 ; doi:10.1145/367390.367400

    Article  Google Scholar 

  5. Gabrilovich, E., Dumais, S., Horvitz, E.: Newsjunkie: providing personalized newsfeeds via analysis of information novelty. In: WWW 2004: Proceedings of the 13th International Conference on World Wide Web, pp. 482–490. ACM Press, New York (2004); doi:10.1145/988672.988738

    Google Scholar 

  6. Iacobelli, F., Birnbaum, L., Hammond, K.J.: Tell me more, not just ”more of the same”. In: IUI 2010: Proceeding of the 14th International Conference on Intelligent User Interfaces, pp. 81–90. ACM, New York (2010), http://dx.doi.org/10.1145/1719970.1719982 ; doi:10.1145/1719970.1719982

    Google Scholar 

  7. Käki, M.: Findex: search result categories help users when document ranking fails. In: CHI 2005: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 131–140. ACM, New York (2005)

    Google Scholar 

  8. Lafferty, J., McCallum, A., Pereira, F.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Proc. 18th International Conf. on Machine Learning, pp. 282–289. Morgan Kaufmann, San Francisco (2001); http://citeseer.ist.psu.edu/lafferty01conditional.html

    Google Scholar 

  9. Li, W., McCallum, A.: Semi-supervised sequence modeling with syntactic topic models. In: AAAI-2005, The Twentieth National Conference on Artificial Intelligence (2005), http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.152.3819

  10. Milne, D., Witten, I.H.: Learning to link with wikipedia. In: CIKM 2008: Proceeding of the 17th ACM Conference on Information and Knowledge Management, pp. 509–518. ACM, New York (2008), http://dx.doi.org/10.1145/1458082.1458150 ; doi:10.1145/1458082.1458150

    Google Scholar 

  11. Park, S., Lee, S., Song, J.: Aspect-level news browsing: Understanding news events from multiple viewpoints. In: Intelligent User Interfaces (IUI 2010), pp. 41–50 (2010)

    Google Scholar 

  12. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. In: Information Processing and Management, pp. 513–523 (1988)

    Google Scholar 

  13. Schiffman, B.: Learning to identify new information. Ph.D. thesis, Columbia University (2005)

    Google Scholar 

  14. Schiffman, B., Mckeown, K.R.: Columbia university in the novelty track at trec 2004. In: Proceedings of the TREC 2004 (2004)

    Google Scholar 

  15. Soboroff, I., Harman, D.: Overview of the TREC 2003 novelty track. In: Proceedings of TREC-2003, Citeseer (2003)

    Google Scholar 

  16. Sweeney, S., Crestani, F., Losada, D.: ’show me more’: Incremental length summarisation using novelty detection. Information Processing & Management 44(2), 663–686 (2008); doi:10.1016/j.ipm.2007.03.012

    Article  Google Scholar 

  17. Wagner, E.J., Liu, J., Birnbaum, L., Forbus, K.D.: Rich interfaces for reading news on the web. In: IUI 2009: Proceedings of the 13th International Conference on Intelligent User Interfaces, pp. 27–36. ACM, New York (2009), http://dx.doi.org/10.1145/1502650.1502658 ; doi:10.1145/1502650.1502658

    Google Scholar 

  18. Yerva, S.R., Miklós, Z., Aberer, K.: Towards better entity resolution techniques for web document collections. In: Proceedings of 1st International Workshop on Data Engineering meets the Semantic Web, Co-located with ICDE 2010 (2010), http://lsirpeople.epfl.ch/yerva/papers/desweb2010.pdf

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Iacobelli, F., Nichols, N., Birnbaum, L., Hammond, K. (2012). Information Finding with Robust Entity Detection: The Case of an Online News Reader. In: Zacarias, M., de Oliveira, J.V. (eds) Human-Computer Interaction: The Agency Perspective. Studies in Computational Intelligence, vol 396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25691-2_16

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  • DOI: https://doi.org/10.1007/978-3-642-25691-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25690-5

  • Online ISBN: 978-3-642-25691-2

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