Title: Concept Extraction from Arabic Text Based On Semantic Analysis

Year of Publication: 2015
Page Numbers: 32-38
Authors: Hassan Najadat, Ahmad Rawashdeh
Conference Name: The International Technology Management Conference (ITMC2015)
- Turkey

Abstract:


Concept extraction can help in building ontologies, which are the main component of the semantic Web. Ontologies are not only used in the semantic Web, but also in other fields such as Information Retrieval to improve the retrieval. In this work, an Automatic Concept Extractor, which processes Arabic text, is presented. The algorithm of the Automatic Concept Extractor tags the words in the text, finds the pattern of each noun, and outputs only those nouns whose patterns match one of the concepts patterns in the concepts extraction rules. The result of each rule was evaluated individually to find the rules with the highest precision. Two datasets were crawled from the Web and converted to XML. Each rule was tested twice with each dataset as the input. The average precision of the rules showed that the rules with the patterns "Tafe'el" “ليعفت” and Fe'aleh “ةلاعف” achieved a high precision.