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Title:Domain-independent term extraction & term network for scientific publications
Author(s):Chen, Zheng; Yan, Erjia
Subject(s):Term extraction
Term network
Domain independent
Publication analysis
Abstract:Term extraction is an essential tool for content-based publication analysis, and has a long history dating back to 1970s. However, previous methods are either domain-specific, or need complex model training, or relies on external resources like Wikipedia. Recent rise of cross-domain publication content analyses has put forward the demand for simple and efficient domain-independent extraction method. This paper proposes a new rule-based method that adapts C-value method to publication analysis, extends it with two types of frequency lists and sigmoid functions, and develops a prototype term extraction system. Our experiment shows a remarkable reduction of “error” with better or competitive “keyword recall” against C-Value method and a complex term extraction method provided by Translated.net. We then construct a term network by connecting adjacent terms in a paragraph and demonstrate that rich and meaningful analysis can be done on such network through a case study on an HCI abstract corpus.
Issue Date:2017
Citation Info:Chen, Z., & Yan, E. (2017). Domain-Independent Term Extraction & Term Network for Scientific Publications. In iConference 2017 Proceedings (pp. 171–189). https://doi.org/10.9776/17020
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper/Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/96671
DOI:https://doi.org/10.9776/17020
Rights Information:Copyright 2017 Zheng Chen and Erija Yan
Date Available in IDEALS:2017-07-27


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