Title :
Identifying Text Objects Based on Expansion
Author :
Ohkubo, Kohta ; Miura, Takao
Author_Institution :
Hosei Univ., Tokyo
Abstract :
In this investigation, we propose a sophisticated approach to identify items in several dictionaries for the purpose of integration. To identity synonymous words efficiently, we discuss IR approach based on vector space modeling to sentences in item explanations, without any knowledge of grammatical analysis or any other NLP analysis. We show the usefulness by some experimental results.
Keywords :
dictionaries; natural language processing; text analysis; dictionaries; grammatical analysis; item explanation; sentences; synonymous words; text object identification; vector space modeling; Character generation; Dictionaries; Frequency; Functional analysis; Humans; Internet; Natural languages; Scalability; Speech; Thesauri; Dictionary; Expansion; Object Identification;
Conference_Titel :
Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1189-4
Electronic_ISBN :
1-4244-1190-4
DOI :
10.1109/PACRIM.2007.4313223
