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An Academic Search and Analysis Prototype for Specific Domain

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7234))

Abstract

There exist several powerful and popular academic search engines, such as Microsoft Academic Search, Google Scholar and CiteSeerX, etc. However, query answering is now being required by users in addition to existed keyword and semantic search. Academic search and analysis is based on techniques of keyword and semantic search, and implements part of the query answering functions. It can provide but not limited to the following services: ranking researchers, mining university and company relationships, finding research groups in an affiliation, evaluating importance of research communities, recommending similar researchers, and so on. This paper introduces an academic search and analysis prototype All4One for specific domains of information science, computer science and telecommunication science. It is focused on solving the two major difficulties of affiliation name and researcher name disambiguation, as well as domain specific large scale ontology construction.

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References

  1. Gao, Z.Q., Zhu, W.Y., Qu, Y.Z., Huang, Z.S.: Analyzing Distribution and Evolution of Research Interests by Term Extraction and Ontology Learning. In: Proceedings of the 9th International Conference on Web-Age Information Management (2008)

    Google Scholar 

  2. Speretta, M., Gauch, S., Lakkaraju, P.: Using CiteSeer to Analyze Trends in the ACM’s Computing Classificatin System. In: Conference on Human System Interaction (HSI), Poland, pp. 571–577 (2010)

    Google Scholar 

  3. Dolby, J., Fokoue, A., Kalyanpur, A., Schonberg, E., Srinivas, K.: Extracting Enterprise Vocabularies Using Linked Open Data. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 779–794. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  4. Navigli, R., Velardi, P.: Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites. Comput. Linguist. 30(2), 151–179 (2004)

    Article  MATH  Google Scholar 

  5. Smeaton, A.F., Keogh, G., Gurrin, C., McDonald, K., Sodring, T.: Analysis of Papers from Twenty-Five Years of SIGIR Conferences: What Have We Been Doing for the Last Quarter of a Century? SIGIR Forum 36(2), 39–43 (2002)

    Article  Google Scholar 

  6. Frantzi, K.T., Ananiadou, S., Mima, H.: Automatic recognition of multi-word terms: the C-value/NC-value method. Int. J. on Digital Libraries (JODL) 3(2), 115–130 (2000)

    Article  Google Scholar 

  7. Kageura, K., Umino, B.: Methods of Automatic Term Recognition: A Review. Terminology 3(2), 259–289 (1996)

    Article  Google Scholar 

  8. Etzioni, O., Cafarella, M., Downey, D., Kok, S., Popescu, A., Shaked, T., Soderland, S., Weld, D.S., Yates, A.: Web-Scale Information Extraction in KnowItAll. In: Proceeding of 13th World Wide Web Conference (2004)

    Google Scholar 

  9. Cimiano, P., Handschun, S., Staab, S.: Towards the Self-Annotating Web. In: Proceedings of the 13th World Wide Web Conference (2004)

    Google Scholar 

  10. Cimiano, P., Ladwig, G., Staab, S.: Gimme’ The Context: Context-driven Automatic Semantic Annotation with C-PANKOW. In: Proceedings of the 14th World Wide Web Conference (2005)

    Google Scholar 

  11. Guha, R., Mccool, R., Miller, E.: Semantic Search. In: Proceeding of the 12th World Wide Web Conference, New York, NY, USA (2003)

    Google Scholar 

  12. Cimiano, P., Staab, S.: Learning Conception Hierarchies form Text with a Guided Agglomerative Clustering Algorithm. In: Proceedings of Workshop on Learning and Extracting Lexical Ontologies with Machine Learning Methods, Bonn, Germany

    Google Scholar 

  13. Maedche, A., Staab, S.: Discovering Conceptual Relations from Text. In: Proceedings of the 8th International Conference on Conceptual Structures, Darmstadt, Germany (2000)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Gao, Z., Gui, Y., Zhu, M., Huang, Z. (2012). An Academic Search and Analysis Prototype for Specific Domain. In: Wang, H., et al. Web Technologies and Applications. APWeb 2012. Lecture Notes in Computer Science, vol 7234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29426-6_21

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  • DOI: https://doi.org/10.1007/978-3-642-29426-6_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29425-9

  • Online ISBN: 978-3-642-29426-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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