Neural Computing and Applications, ( ISI ), Volume (23), No (6), Year (2012-9) , Pages (1573-1582)

Title : ( SREC: Discourse-level semantic relation extraction from text )

Authors: Mohammad Hadi Zahedi , mohsen kahani ,

Citation: BibTeX | EndNote

Semantic relation extraction is a significant topic in semantic web and natural language processing with various important applications such as knowledge acquisition, web and text mining, information retrieval and search engine, text classification and summarization. Many approaches such rule base, machine learning and statistical methods have been applied, targeting different types of relation ranging from hyponymy, hypernymy, meronymy, holonymy to domain-specific relation. In this paper, we present a computational method for extraction of explicit and implicit semantic relation from text, by applying statistic and linear algebraic approaches besides syntactic and semantic processing of text.

Keywords

Semantic relation extraction – Semantic role labelling – Singular value
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@article{paperid:1029279,
author = {Zahedi, Mohammad Hadi and Kahani, Mohsen},
title = {SREC: Discourse-level semantic relation extraction from text},
journal = {Neural Computing and Applications},
year = {2012},
volume = {23},
number = {6},
month = {September},
issn = {0941-0643},
pages = {1573--1582},
numpages = {9},
keywords = {Semantic relation extraction – Semantic role labelling – Singular value decomposition},
}

[Download]

%0 Journal Article
%T SREC: Discourse-level semantic relation extraction from text
%A Zahedi, Mohammad Hadi
%A Kahani, Mohsen
%J Neural Computing and Applications
%@ 0941-0643
%D 2012

[Download]