Abstract
The rapid increasing of online information is hard to handle. Summaries such as abstracts help us to reduce this problem. Keywords, which can be regarded as very short summaries, may help even more. Filtering documents by using keywords may save precious time while searching. However, most of the documents do not include keywords. In this paper we present a model that extracts keywords from abstracts and titles. This model has been implemented in a prototype system. We have tested our model on a set of abstracts of Academic papers containing keywords composed by their authors. Results show that keywords extracted from abstracts and titles may be a primary tool for researchers.
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HaCohen-Kerner, Y. (2003). Automatic Extraction of Keywords from Abstracts. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_112
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DOI: https://doi.org/10.1007/978-3-540-45224-9_112
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40803-1
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