Paper Info
Title
f: Phrase Relatedness Function Using Overlapping Bi-gram Context.
Abstract
We present an unsupervised phrase relatedness function f that has been applied in a Semantic Textual Similarity system TrWP of SemEval-2015. The best run of TrWP was ranked 33 among 73 runs. f finds the relatedness strength between two phrases using overlapping bi-gram context extracted from the Google-n-gram corpus. The relatedness strength is the strength of association capturing how similar or dissimilar two phrases are. In order to find the relatedness strength, f applies a sum-ratio SR technique based on the statistics of the overlapping n-grams associated with two input phrases. The experimental result from f demonstrates improvement over existing phrase relatedness methods on two standard datasets of 216 phrase-pairs. f does not require any human annotated resource and is independent of the syntactic structure of phrases.
Year
DOI
Venue
2016
10.1007/978-3-319-34111-8_19
Canadian Conference on AI
Keywords
Field
DocType
Phrase relatedness,Google-n-gram,Unsupervised,Overlapping bi-gram context
Ranking,Pattern recognition,Computer science,Phrase,Speech recognition,Natural language processing,Artificial intelligence,Gram,Syntactic structure
Conference
Volume
ISSN
Citations 
9673
0302-9743
0
PageRank 
References 
Authors
0.34
19
3
Name
Order
Citations
PageRank
Md. Rashadul Hasan Rakib110.70
Aminul Islam232831.16
Evangelos E. Milios329041.22