Paper Info
Title
Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining.
Abstract
This paper deals with the extraction of semantic relations from scientific texts. Pattern-based representations are compared to word embeddings in unsupervised clustering experiments, according to their potential to discover new types of semantic relations and recognize their instances. The results indicate that sequential pattern mining can significantly improve pattern-based representations, even in a completely unsupervised setting.
Year
DOI
Venue
2016
10.1007/978-3-319-46349-0_21
ADVANCES IN INTELLIGENT DATA ANALYSIS XV
Field
DocType
Volume
Parse tree,Pattern recognition,Computer science,Semantic relation,Artificial intelligence,Cluster analysis,Sequential Pattern Mining,Relationship extraction
Conference
9897
ISSN
Citations 
PageRank 
0302-9743
2
0.38
References 
Authors
28
5
Name
Order
Citations
PageRank
Kata Gábor1124.13
Haïfa Zargayouna27611.85
isabelle tellier38420.31
Davide Buscaldi443654.12
thierry charnois59817.21