عنوان

A computational lexicon and representational model for Arabic multiword expressions

شماره

TLets766461

عنوان اصلي

A computational lexicon and representational model for Arabic multiword expressions

نام عام مواد

[Thesis]

نام نخستين پديدآور

Alghamdi, Ayman Ahmad O.

نام ساير پديدآوران

Atwell, Eric

نام ناشر، پخش کننده و غيره

University of Leeds

تاریخ نشرو بخش و غیره

2018

جزئيات پايان نامه و نوع درجه آن

Thesis (Ph.D.)

امتياز متن

2018

متن يادداشت

The phenomenon of multiword expressions (MWEs) is increasingly recognised as a serious and challenging issue that has attracted the attention of researchers in various language-related disciplines. Research in these many areas has emphasised the primary role of MWEs in the process of analysing and understanding language, particularly in the computational treatment of natural languages. Ignoring MWE knowledge in any NLP system reduces the possibility of achieving high precision outputs. However, despite the enormous wealth of MWE research and language resources available for English and some other languages, research on Arabic MWEs (AMWEs) still faces multiple challenges, particularly in key computational tasks such as extraction, identification, evaluation, language resource building, and lexical representations. This research aims to remedy this deficiency by extending knowledge of AMWEs and making noteworthy contributions to the existing literature in three related research areas on the way towards building a computational lexicon of AMWEs. First, this study develops a general understanding of AMWEs by establishing a detailed conceptual framework that includes a description of an adopted AMWE concept and its distinctive properties at multiple linguistic levels. Second, in the use of AMWE extraction and discovery tasks, the study employs a hybrid approach that combines knowledge-based and data-driven computational methods for discovering multiple types of AMWEs. Third, this thesis presents a representative system for AMWEs which consists of multilayer encoding of extensive linguistic descriptions. This project also paves the way for further in-depth AMWE-aware studies in NLP and linguistics to gain new insights into this complicated phenomenon in standard Arabic. The implications of this research are related to the vital role of the AMWE lexicon, as a new lexical resource, in the improvement of various ANLP tasks and the potential opportunities this lexicon provides for linguists to analyse and explore AMWE phenomena.

مستند نام اشخاص تاييد نشده

Alghamdi, Ayman Ahmad O.

مستند نام اشخاص تاييد نشده

Atwell, Eric

مستند نام تنالگان تاييد نشده

University of Leeds

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y