A Method for Chinese Noun Phrase Recognition Base on Word Co-Occurrence Directed Graph

Abstract:

This paper proposes a recognition method for Chinese Noun Phrase based on word co-occurrence directed graph. An input document is firstly scanned in which noun word string is retrieved. Atomic word table and word co-occurrence directed graph is then generated according to the word strings. A search is performed on the graph to find the longest paths with priority weight satisfying certain criteria. The word strings corresponding to the paths are considered as noun phrases. As dimensionality reduction is applied, the scale of the word co-occurrence directed graph is reduced significantly, and thus the efficiency of the algorithm is improved. Experimental results demonstrate that the precision of noun phrase recognition reaches 95.4%.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 4412-4418
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.4412
• Online since: September 2013
• Authors: Xing Lin Liu
• Keywords: Atomic Word, Knowledge Acquisition, Natural Language Processing, Noun Phrase, Word Co-Occurrence Directed Graph

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