Arabic Text Representation using Rich Semantic Graph: A Case Study

نویسندگان

  • SALLY S. ISMAIL
  • MOSTAFA AREF
چکیده

Representing Arabic Text semantically using Rich Semantic Graph (RSG) is one of the recent techniques that facilitate the process of manipulating the Arabic Language in Natural Language Processing (NLP) field. The work presented in this paper is a part of an ongoing research to create an abstractive summary for a single input document in Arabic Language. The abstractive summary is generated through three modules: converting the input Arabic text into a Rich Semantic Graph, then performing Graph Reduction, and finally generating the summarized text from the reduced graph. This is done with the aid of a domain Ontology. In this paper, we are presenting the first module and a detailed case study verifying our work. Key-Words: Arabic Language, Text Representation, Rich Semantic Graph (RSG), Natural Language Processing(NLP), Text Summarization, Ontology.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Joint Semantic Vector Representation Model for Text Clustering and Classification

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...

متن کامل

Towards Supporting Exploratory Search over the Arabic Web Content: The Case of ArabXplore

Due to the huge amount of data published on the Web, the Web search process has become more difficult, and it is sometimes hard to get the expected results, especially when the users are less certain about their information needs. Several efforts have been proposed to support exploratory search on the web by using query expansion, faceted search, or supplementary information extracted from exte...

متن کامل

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...

متن کامل

Abstracts/Journal of the Arabic Language and LiteratureVol.14, No48, autumn 2018

Contents The Representation of Culture in Arabic pedagogy books to non-Arabic languages Danesh Mohammadi, Sakineh Zarenejad....................................................... 1 Critical Study of the‏‏manifestations of Mamluke's life from the novel “Alsaeroun‏‏niyam...

متن کامل

Situation and Text: Representation of Migrants Whilst the Escalation of Refugee Crisis in Great Britain as Compared to Russia

Increasing migration is a vital concern for a globalizing sociocultural environment in today’s world. The UK and developed European countries have become an attractive destination for asylum seekers (labelled as “migrants”) in the past decade. The rapid rise in the number of asylum seekers, which was labelled “migration crisis” (Ruz, 2015), made this topic an integral part of scientific discuss...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013