Unsupervised Affix Identification Approach using Probabilistic Dependence

Abeer Alsheddi; Ahmed Khorsi

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Unsupervised Affix Identification Approach using Probabilistic Dependence

Abeer Alsheddi and Ahmed Khorsi

The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.1

01/01/2018

Abstract

Computer security

Dependence

Conference Title: 2018 1st International Conference on Computer Applications & Information Security (ICCAIS) Conference Start Date: 2018, April 4 Conference End Date: 2018, April 6 Conference Location: Riyadh, Saudi Arabia It is difficult to identify an affix letter from a root letter in a given word in many NLP applications. This challenge is even harder in morphologically complex languages, such as Arabic. This paper investigates to identify affix letters using probabilistic dependence concept with an unsupervised method. A relationship is shown when 90% of the negative dependence points appeared at the affix letters.

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Title: Unsupervised Affix Identification Approach using Probabilistic Dependence
Creators - without role: Abeer Alsheddi
Ahmed Khorsi
Publication Details: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.1
Publisher: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Identifiers: 9916702708331
Academic Unit: Imam Mohammad Ibn Saud Islamic University (IMSIU)
Language: English
Resource Type: Conference proceeding