Automatic Subject-Object-Verb relation extraction

Author

Temizer, Merve ; Diri, Banu

Author_Institution

Software Dev., Gobito Enterprise Solutions, İstanbul, Turkey

fYear

2012

fDate

2-4 July 2012

Firstpage

1

Lastpage

4

Abstract

Artificial Intelligence is one of the key concepts of today´s technology. As it is known, AI´s aim is to developing technology that can learn by itself. Also, Natural Language Processing is another key concept as a significant contributor to AI in the field of natural languages. Considering the AI and NLP together brings us to teach computers to learn on their own about the natural languages and human derived words with their relationship. This paper aims to transfer a considerable amount of information to computers´ world by presenting a way to extract Subject-Object-Verb relation extraction from Turkish documents automatically. Through three main steps the goal is achieved: (1) morphological analysis, (2) dependency analysis, (3) triplet extraction. As a result, an independent triplets graph can be generated for each text input, and verbs-nouns relation can be viewed.

Keywords

artificial intelligence; natural language processing; Turkish documents; artificial intelligence; automatic subject-object-verb relation extraction; dependency analysis; developing technology; independent triplets graph; morphological analysis; natural language processing; triplet extraction; verbs-nouns relation; Algorithm design and analysis; Artificial intelligence; Computers; Data mining; Feature extraction; Java; Support vector machines; dependency analysis; subject-object-verb relation extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on

Conference_Location

Trabzon

Print_ISBN

978-1-4673-1446-6

Type

conf

DOI

10.1109/INISTA.2012.6246943

Filename

6246943