Arabic verb pattern extraction

Saad, E. M.; Awadalla, Medhat; Alajmi, A. F.

doi:10.1109/isspa.2010.5605427

Cited by 2 publications

(3 citation statements)

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“…A variety of algorithms have been developed to perform morphological analysis of verbs based on an input word, such as, sliding window algorithms (El-Affindi, 1998), word decomposition using algebraic algorithms (El-Affindi, 1991), and literals generation using permutations of the input word letters (Al-Shalabi and Evens, 1998). Other analyzers attempt to extract the root of a verb by manipulating infixes and prefixes (Hamandi et al, 2002(Hamandi et al, , 2006Khoja, 2017;Khoja and Garside, 1999;Larkey and Connell, 2006;Saad et al, 2010;Larkey et al, 2002;Asaad and Abbod, 2014;Boudlal et al, 2011;Hegaz and Elsharkawi, 1986;Hlal, 1987;Abu Shquier and Alhawiti, 2015;Sembok and Ata, 2013;Abu-Errub et al, 2014;Al-Bawab and Al-Tayyan, 1998). The extracted stems are then validated against a list of standard Arabic roots.…”

Section: Related Workmentioning

confidence: 99%

Parallel hardware for faster morphological analysis

Damaj

Imdoukh

Zantout

2018

Journal of King Saud University - Computer and Information Scie

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Hardware design FPGAs a b s t r a c tMorphological analysis of Arabic language is computationally intensive, has numerous forms and rules, and intrinsically parallel. The investigation presented in this paper confirms that the effective development of parallel algorithms and the derivation of corresponding processors in hardware enable implementations with appealing performance characteristics. The presented developments of parallel hardware comprise the application of a variety of algorithm modelling techniques, strategies for concurrent processing, and the creation of pioneering hardware implementations that target modern programmable devices. The investigation includes the creation of a linguistic-based stemmer for Arabic verb root extraction with extended infix processing to attain high-levels of accuracy. The implementations comprise three versions, namely, software, non-pipelined processor, and pipelined processor with high throughput. The targeted systems are high-performance multi-core processors for software implementations and high-end Field Programmable Gate Array systems for hardware implementations. The investigation includes a thorough evaluation of the methodology, and performance and accuracy analyses of the developed software and hardware implementations. The developed processors achieved significant speedups over the software implementation. The developed stemmer for verb root extraction with infix processing attained accuracies of 87% and 90.7% for analyzing the texts of the Holy Quran and its Chapter 29 -Surat Al-Ankabut. Ó 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Section: Related Workmentioning

confidence: 99%

Parallel hardware for faster morphological analysis

Damaj

Imdoukh

Zantout

2018

Journal of King Saud University - Computer and Information Scie

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“…Saad et al [21] used a pattern-based approach for extracting verb patterns. Their method first generates a list of all possible Arabic verb patterns and then reduces the list based on Arabic morphological rules.…”

Section: 1mentioning

confidence: 99%

“…Major works in Arabic include the extraction of rhetorical relations [15] [16] and general semantic relations explicitly stated in a text [17], Wikipedia relations [18], synonyms [19], relations between named entities [20], verbs [21], spatial relations [22], grammatical relations [23], and ontological relations [24] [25]. The only study in our review that explicitly mentions antonymy as one of the extracted relations is [19], which uses morpho-lexical patterns applied on a set of Wikipedia articles as a corpus to enrich WordNet, but the results obtained for antonyms were 0%.…”

Section: Introductionmentioning

confidence: 99%

Ontological Lexicon Enrichment: The Badea System For Semi-Automated Extraction Of Antonymy Relations From Arabic Language Corpora

Al-Yahya

Al-Malak

Aldhubayi

2016

MJCS

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Ontological lexicons are considered a rich source of knowledge for the development of various natural language processing tools and applications; however, they are expensive to build, maintain, and extend. In this paper, we present the Badea system for the semi-automated extraction of lexical relations, specifically antonyms using a pattern-based approach to support the task of ontological lexicon enrichment. The approach is based on an ontology of "seed" pairs of antonyms in the Arabic language; we identify patterns in which the pairs occur and then use the patterns identified to find new antonym pairs in an Arabic textual corpora. Experiments are conducted on Badea using texts from three Arabic textual corpuses: KSUCCA, KACSTAC, and CAC. The system is evaluated and the patterns' reliability and system performance is measured. The results from our experiments on the three Arabic corpora show that the pattern-based approach can be useful in the ontological enrichment task, as the evaluation of the system resulted in the ontology being updated with over 300 new antonym pairs, thereby enriching the lexicon and increasing its size by over 400%. Moreover, the results show important findings on the reliability of patterns in extracting antonyms for Arabic. The Badea system will facilitate the enrichment of ontological lexicons that can be very useful in any Arabic natural language processing system that requires semantic relation extraction.Keywords: Antonym Extraction, Ontology, Arabic Lexicon, Semantic Relation, Arabic NLP INTRODUCTIONA lexicon is defined as "the knowledge that a native speaker has about a language. This includes information about the form and meanings of words and phrases, lexical categorization, the appropriate usage of words and phrases, relationships between words and phrases, and categories of words and phrases" [1]. Lexicon is an essential element for natural language processing (NLP) applications. For some applications, such as machine translation, lexicon is a critical resource [2]. An important aspect of such lexicons that renders them effective, reusable, and sharable within the community is building them upon standards such as semantic Web standards in the form of ontologies. An ontological lexicon is a lexicon designed using an ontological model and developed as an ontology. Ontological lexicons play a vital role in NLP applications such as language analysis, semantic annotation, summarization, machine translation, sense disambiguation, generation of lexical-competence questions used in standard language tests, and other applications that rely on implicit information in the text.Although ontological lexicons provide a rich source of knowledge for NLP applications, like other types of computational lexicons, they are expensive to build, maintain, and extend [2] [3] [4]. Moreover, the task of relation extraction is essential in any ontological lexicon development. Relation extraction focuses on the extraction of structured relations from unstructured sources such as Web documents ...

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Arabic verb pattern extraction

Cited by 2 publications

References 10 publications

Parallel hardware for faster morphological analysis

Parallel hardware for faster morphological analysis

Ontological Lexicon Enrichment: The Badea System For Semi-Automated Extraction Of Antonymy Relations From Arabic Language Corpora

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