Abstract
Keyphrase extraction is a task with many applications in information retrieval, text mining, and natural language processing. In this paper, a keyphrase extraction approach based on neural network is proposed. To determine whether a phrase is a keyphrase, the following features of a phrase in a given document are adopted: its term frequency and inverted document frequency, whether to appear in the title or headings (subheadings) of the given document, and its frequency appearing in the paragraphs of the given document. The algorithm is evaluated by the standard information retrieval metrics of precision and recall, and human assessment.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Wang, J., Peng, H., Hu, Js. (2006). Automatic Keyphrases Extraction from Document Using Neural Network. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_66
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DOI: https://doi.org/10.1007/11739685_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
Online ISBN: 978-3-540-33585-6
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