Title
Semantic Role Labeling Of English Tweets
Abstract
Semantic role labeling (SRL) is a task of defining the conceptual role to the arguments of predicate in a sentence. This is an important task for a wide range of tweet related applications associated with semantic information extraction. SRL is a challenging task due to the difficulties regarding general semantic roles for all predicates. It is more challenging for Social Media Text (SMT) where the nature of text is more casual. This paper presents an automatic SRL system for English tweets based on Sequential Minimal Optimization (SMO) algorithm. Proposed system is evaluated through experiments and reports comparable performance with the prior state-of-the art SRL system.
Year
DOI
Venue
2018
10.13053/CyS-22-3-3035
COMPUTACION Y SISTEMAS
Keywords
Field
DocType
Social media text, tweet stream, semantic role labeling, tweet summarization
Social media,Computer science,Semantic information,Natural language processing,Artificial intelligence,Predicate (grammar),Casual,Sequential minimal optimization,Sentence,Semantic role labeling
Journal
Volume
Issue
ISSN
22
3
1405-5546
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Dwijen Rudrapal132.74
Amitava Das219842.49