DocumentCode
2767939
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
Volume
7
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
487
Lastpage
491
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.657
Filename
5360058
Link To Document