Title :
Sentence Similarity Measurement Based on Shallow Parsing
Author :
Li, Lin ; Zhou, Yiming ; Yuan, Boqiu ; Wang, Jun ; Hu, Xia
Author_Institution :
Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
Abstract :
The paper proposes a novel method to determine sentence similarities. First two compared sentences are parsed by shallow-parsing and all noun phrases, verb phrases and preposition phrases of each sentence are extracted. Then the similarity between each kind of phrases is calculated based on a semantic vector method. The overall sentence similarity is defined as a combination of semantic similarities of the three kinds of phrases. Experiments show that the proposed method has a high performance in F-measure (81.6%) and Recall (97.4%).
Keywords :
formal languages; grammars; compared sentences; noun phrase; preposition phrase; semantic vector method; sentence similarity measurement; shallow parsing; verb phrase; Computer science; Data mining; Fuzzy systems; Knowledge engineering; Knowledge representation; Robustness; Speech analysis; Testing; Text mining; Time measurement; Semantic similarity; Semantic vector; Sentence similarity; Shallow parsing;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.657