scholarly journals Multi-Word Term Extraction Based on New Hybrid Approach for Arabic Language

2014 ◽  
Author(s):  
Meryeme Hadni ◽  
Abdelmonaime Lachkar ◽  
Said Alaoui Ouatik
Keyword(s):  
Hybrid Approach ◽  
Arabic Language ◽  
Term Extraction

A New Semantic Relations-Based Hybrid Approach for Implicit Aspect Identification in Sentiment Analysis

2020 ◽  
Vol 19 (03) ◽  
pp. 2050019
Author(s):  
Hajar El Hannach ◽  
Mohammed Benkhalifa
Keyword(s):  
Sentiment Analysis ◽  
Hybrid Model ◽  
Opinion Mining ◽  
Short Term Memory ◽  
Hybrid Approach ◽  
Active Phase ◽  
Semantic Relations ◽  
Term Extraction ◽  
Supervised Classifiers ◽  
Restaurant Reviews

Within the next few years, sentiment analysis or opinion mining is set to become an important component of real-world applications for product manufacturers, e-commerce companies, and potential customers. Sentiment analysis deals with the computational assessment of people’s opinions apparent or hidden within the text according to three levels: document, sentence and aspect levels. The aspect-level is increasingly becoming an active phase of sentiment analysis. At this level, the aim is to determine the hidden target of opinion represented in datasets, known as aspect term identification. This paper proposes an original hybrid model combining semantic relations and frequency-based approach with supervised classifiers for implicit aspect identification (IAI). The proposed approach is directed towards improving the F1-performances for traditional supervised classifiers commonly used in this field based on eager and lazy learning, and deep learning technique using long short-term memory whit attention mechanism applied for IAI. Particularly, this work addresses aspect term extraction and aggregation, the two sub-tasks of IAI, involving adjectives and verbs. The effects of this approach are empirically examined on multiple datasets of electronic products and restaurant reviews with multiple aspect granularity levels. Comparing this method with similar approaches clearly shows the benefits of this method: (i) the use of an appropriately selected WordNet semantic relations of adjectives and verbs that significantly helps classifiers for IAI. (ii) Using the hybrid model helps classifiers better handle these selected WordNet semantic relations and therefore deal better with IAI.

Expatriate managers decision-making practices within the UAE: a qualitative study

2016 ◽  
Vol 24 (5) ◽  
pp. 856-882 ◽  
Author(s):  
Hanan AlMazrouei ◽  
Robert Zacca ◽  
Chris Bilney ◽  
Giselle Antoine
Keyword(s):  
Decision Making ◽  
Hybrid Approach ◽  
Arabic Language ◽  
Management Style ◽  
Business Success ◽  
Content Type ◽  
Local Staff ◽  
Local Decision ◽  
Expatriate Managers ◽  
Contextual Environment

Purpose Managing across cultures is vital for international business success. Leaders need to make decisions in a way that suits the new culture in which they are placed. This paper aims to explore how expatriate managers in the UAE make decisions in respect to their contextual environment. Additionally, the study investigates the approaches expatriate managers use to adjust their decision-making and how they manage local staff in contrast to home country staff. Finally, the study investigates the factors that contribute to the situation-specific environment of the expatriate leaders’ experience. Design/methodology/approach Structured personal interviews of expatriates drawn from stratified sampling were used to discover the styles of decision-making that were effective in the UAE. Findings The consultative management style of management enhanced by a hybrid approach of melding the strongest aspects of the expatriates’ decision-making style with the strongest aspects of the local decision-making style met with much success managing in the UAE. Additionally, the expatriate managers’ expression of appreciation towards local staff provided motivation and encouraged cooperation. Moreover, it was found that expatriates can face difficulties in expressing their wishes and requirements accurately to local staff because of their unfamiliarity with the Arabic language. Practical implications This research provides practical guidance for expatriate managers charged with successfully leading organizations in UAE. It also offers guidance for employers seeking to recruit or employ appropriate management talent to UAE. Originality/value The paper concentrates on expatriate managers’ decision-making practices within the UAE.

scholarly journals HAMLET

Terminology ◽  
2021 ◽  
Author(s):  
Ayla Rigouts Terryn ◽  
Véronique Hoste ◽  
Els Lefever
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Hybrid Approach ◽  
Substantial Effect ◽  
Training Data ◽  
Supervised Machine Learning ◽  
Learning Approach ◽  
Term Extraction ◽  
Machine Learning Approach ◽  
Different Types

Abstract Automatic term extraction (ATE) is an important task within natural language processing, both separately, and as a preprocessing step for other tasks. In recent years, research has moved far beyond the traditional hybrid approach where candidate terms are extracted based on part-of-speech patterns and filtered and sorted with statistical termhood and unithood measures. While there has been an explosion of different types of features and algorithms, including machine learning methodologies, some of the fundamental problems remain unsolved, such as the ambiguous nature of the concept “term”. This has been a hurdle in the creation of data for ATE, meaning that datasets for both training and testing are scarce, and system evaluations are often limited and rarely cover multiple languages and domains. The ACTER Annotated Corpora for Term Extraction Research contain manual term annotations in four domains and three languages and have been used to investigate a supervised machine learning approach for ATE, using a binary random forest classifier with multiple types of features. The resulting system (HAMLET Hybrid Adaptable Machine Learning approach to Extract Terminology) provides detailed insights into its strengths and weaknesses. It highlights a certain unpredictability as an important drawback of machine learning methodologies, but also shows how the system appears to have learnt a robust definition of terms, producing results that are state-of-the-art, and contain few errors that are not (part of) terms in any way. Both the amount and the relevance of the training data have a substantial effect on results, and by varying the training data, it appears to be possible to adapt the system to various desired outputs, e.g., different types of terms. While certain issues remain difficult – such as the extraction of rare terms and multiword terms – this study shows how supervised machine learning is a promising methodology for ATE.

A new hybrid approach for speech synthesis: application to the Arabic language

2018 ◽  
Vol 22 (3) ◽  
pp. 629-637
Author(s):  
Hanane Tebbi ◽  
Maamar Hamadouche ◽  
Hamid Azzoune
Keyword(s):  
Speech Synthesis ◽  
Hybrid Approach ◽  
Arabic Language

scholarly journals Automatic Key Term Extraction from Research Article using Hybrid Approach

2017 ◽  
Vol 166 (6) ◽  
pp. 17-21
Author(s):  
Selvani Deepthi ◽  
B. Rajesh ◽  
N. Vyshnavi ◽  
K. Moni
Keyword(s):  
Hybrid Approach ◽  
Term Extraction ◽  
Research Article

Narrative Language Markers of Arabic Language Development and Impairment

2020 ◽  
Vol 63 (10) ◽  
pp. 3472-3487
Author(s):  
Natalia V. Rakhlin ◽  
Nan Li ◽  
Abdullah Aljughaiman ◽  
Elena L. Grigorenko
Keyword(s):  
Language Development ◽  
Standardized Test ◽  
Language Disorder ◽  
Arabic Language ◽  
Developmental Language Disorder ◽  
Standardized Measures ◽  
Verb Agreement ◽  
Language Groups ◽  
Specificity And Sensitivity ◽  
Omission Errors

Purpose We examined indices of narrative microstructure as metrics of language development and impairment in Arabic-speaking children. We examined their age sensitivity, correlations with standardized measures, and ability to differentiate children with average language and language impairment. Method We collected story narratives from 177 children (54.2% boys) between 3.08 and 10.92 years old ( M = 6.25, SD = 1.67) divided into six age bands. Each child also received standardized measures of spoken language (Receptive and Expressive Vocabulary, Sentence Imitation, and Pseudoword Repetition). Several narrative indices of microstructure were examined in each age band. Children were divided into (suspected) developmental language disorder and typical language groups using the standardized test scores and compared on the narrative indicators. Sensitivity and specificity of the narrative indicators that showed group differences were calculated. Results The measures that showed age sensitivity included subject omission error rate, number of object clitics, correct use of subject–verb agreement, and mean length of utterance in words. The developmental language disorder group scored higher on subject omission errors (Cohen's d = 0.55) and lower on correct use of subject–verb agreement (Cohen's d = 0.48) than the typical language group. The threshold for impaired performance with the highest combination of specificity and sensitivity was 35th percentile. Conclusions Several indices of narrative microstructure appear to be valid metrics for documenting language development in children acquiring Gulf Arabic. Subject omission errors and correct use of subject–verb agreement differentiate children with typical and atypical levels of language development.

Surgical and endovascular hybrid approach in peripheral arterial disease of the lower limbs

VASA ◽  
2016 ◽  
Vol 45 (5) ◽  
pp. 417-422 ◽  
Author(s):  
Anouk Grandjean ◽  
Katia Iglesias ◽  
Céline Dubuis ◽  
Sébastien Déglise ◽  
Jean-Marc Corpataux ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Peripheral Arterial Disease ◽  
Limb Salvage ◽  
Hybrid Approach ◽  
Arterial Disease ◽  
Early Mortality ◽  
Secondary Patency ◽  
Limb Salvage Rate ◽  
Peripheral Arterial ◽  
Salvage Rate

Abstract. Background: Multilevel peripheral arterial disease is frequently observed in patients with intermittent claudication or critical limb ischemia. This report evaluates the efficacy of one-stage hybrid revascularization in patients with multilevel arterial peripheral disease. Patients and methods: A retrospective analysis of a prospective database included all consecutive patients treated by a hybrid approach for a multilevel arterial peripheral disease. The primary outcome was the patency rate at 6 months and 1 year. Secondary outcomes were early and midterm complication rate, limb salvage and mortality rate. Statistical analysis, including a Kaplan-Meier estimate and univariate and multivariate Cox regression analyses were carried out with the primary, primary assisted and secondary patency, comparing the impact of various risk factors in pre- and post-operative treatments. Results: 64 patients were included in the study, with a mean follow-up time of 428 days (range: 4 − 1140). The technical success rate was 100 %. The primary, primary assisted and secondary patency rates at 1 year were 39 %, 66 % and 81 %, respectively. The limb-salvage rate was 94 %. The early mortality rate was 3.1 %. Early and midterm complication rates were 15.4 % and 6.4 %, respectively. The early mortality rate was 3.1 %. Conclusions: The hybrid approach is a major alternative in the treatment of peripheral arterial disease in multilevel disease and comorbid patients, with low complication and mortality rates and a high limb-salvage rate.

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