Abstract
In this paper we present ScienScan – a browsing and visualization tool for academic search. The tool operates in real time by post-processing the query results returned by an academic search engine. ScienScan discovers topics in the search results and summarizes them in the form of a concise hierarchical topic map. The produced topical summary informatively represents the results in a visual way and provides an additional filtering control. We demonstrate the operation of ScienScan deploying it on top of the search API of Microsoft Academic Search.
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Gansner, E.R., North, S.C.: An open graph visualization system and its applications to software engineering. Software – Practice & Experience 30(11) (2000)
He, Q., Chen, B., Pei, J., Qiu, B., Mitra, P., Giles, L.: Detecting topic evolution in scientific literature: how can citations help? In: CIKM, pp. 957–966. ACM (2009)
Milne, D., Witten, I.H.: An open-source toolkit for mining wikipedia. Artificial Intelligence 194, 222–239 (2013)
Mirylenka, D., Passerini, A.: Learning to grow structured visual summaries for document collections. In: ICML Workshop on Structured Learning (2013)
Scaiella, U., Ferragina, P., Marino, A., Ciaramita, M.: Topical clustering of search results. In: WSDM, pp. 223–232. ACM (2012)
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Mirylenka, D., Passerini, A. (2013). ScienScan – An Efficient Visualization and Browsing Tool for Academic Search. In: Blockeel, H., Kersting, K., Nijssen, S., Železný, F. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2013. Lecture Notes in Computer Science(), vol 8190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40994-3_51
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DOI: https://doi.org/10.1007/978-3-642-40994-3_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40993-6
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