A co-occurrence based approach of automatic keyword expansion using mass diffusion

Xicheng Yin, Hongwei Wang (), Pei Yin, Hengmin Zhu and Zhenyu Zhang
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Xicheng Yin: Tongji University
Hongwei Wang: Tongji University
Pei Yin: University of Shanghai for Science and Technology
Hengmin Zhu: Nanjing University of Posts and Telecommunications
Zhenyu Zhang: Tongji University

Scientometrics, 2020, vol. 124, issue 3, No 9, 1885-1905

Abstract: Abstract The performance of keyword expansion in prior methods is often enhanced by adopting external knowledge. Given a set of initial keywords, this paper is motivated to propose a novel method to expand semantically or conceptually related keywords from domain corpus by employing mass diffusion. A bipartite word network is thus constructed based on co-occurrence relations between initial keywords and candidate words. The expanded keywords are identified via two-step mass diffusion which is carried out in the bipartite network. Experimental results prove that the proposed method outperforms both the typical statistical-based approach and graph-based approach. Our research is expected to complement the theoretical framework of keyword expansion and is applicable to the scenarios of query expansion, thesaurus construction, and text clustering.

Keywords: Expansion; Word co-occurrence; Mass diffusion; Bipartite network (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11192-020-03601-7

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