2022 20th International Conference on Language Engineering (ESOLEC)最新文献_第3页

Towards a Psycholinguistic Database of Arabic 建立阿拉伯语心理语言学数据库

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009144

N. Fathy, S. Alansary

引用次数: 0

Deep Learning in Arabic Text Summarization: Approaches, Datasets, and Evaluation Metrics 阿拉伯语文本摘要中的深度学习:方法，数据集和评估指标

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009528

Yasmin Einieh, Amal Almansour

引用次数: 0

Arabic Sentences Semantic Similarity Based on Word Embedding 基于词嵌入的阿拉伯语句子语义相似度研究

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009099

Badrya Dahy, M. Farouk, Khaled Fathy

{"title":"Arabic Sentences Semantic Similarity Based on Word Embedding","authors":"Badrya Dahy, M. Farouk, Khaled Fathy","doi":"10.1109/ESOLEC54569.2022.10009099","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009099","url":null,"abstract":"Natural language processing pays significant attention to semantic textual similarity. It's useful in a variety of NLP-applications, including information retrieval, plagiarism detection, data extraction, and machine translation. Sentence similarity in the Arabic language has not been investigated deeply because of the lack of Arabic language resources. Moreover, it's critical to calculate the degree of similarity between Arabic sentences accurately. The method for determining the semantic similarity of Arabic sentences is suggested in this research. The strategy suggested uses word embedding to measure the similarity between words. Moreover, more than one similarity measure is combined to calculate the final similarity. Furthermore, due to the lack of Arabic resources, a new dataset for evaluating similarity techniques has been constructed. The new dataset is available for public use. An experiment have been conducted to show the efficiency of the strategy suggested. Two datasets are used to compare other approaches. Experiments reveal that the proposed methods outperform alternative approaches to measuring sentence similarity in the Arabic language.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116849632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new framework for an eKYC system 一个新的eKYC系统框架

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009253

Abdallah Gomaa, Omar Rashed, Abdelkarim Refaey, Abdel-rahman Mohamed, M. Sayed, M. Rashwan

引用次数: 0

Recommender Diagnosis System with Fuzzy Logic in Cloud Environment 云环境下模糊逻辑推荐诊断系统

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009214

Maie Aboghazalah, Rasha Elnemr, Nedaa Elsayed, Ayman El-Sayed, Passant El-Kafrawy

{"title":"Recommender Diagnosis System with Fuzzy Logic in Cloud Environment","authors":"Maie Aboghazalah, Rasha Elnemr, Nedaa Elsayed, Ayman El-Sayed, Passant El-Kafrawy","doi":"10.1109/ESOLEC54569.2022.10009214","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009214","url":null,"abstract":"Recommendation systems are now used in a wide range in many fields. In the medical field, recommendation systems have a great stature to both doctors and patients for its accurate prediction. It can reduce the time and efforts spent by doctors and patients. The present work introduces a simple and effective methodology for medical recommendation system based on fuzzy logic. Fuzzy logic is an important method to be used based on fuzzy input data. The input data for each patient are not the same, on which recommendation can differ. This work aims to develop techniques for handling the patient data to urge accurate lifestyle recommendations to the patient. Fuzzy logic is utilized to form different recommendations for the patient like lifestyle recommendations, medicine recommendations, and sports recommendations based on different patient factors like age, gender and patient diseases. After evaluating the system its efficiency reached 94%. This Experiment is the final module in a four modules recommendation system. The first one is responsible for diagnosing chest diseases using ECG signals. The second one makes diagnosis using X-ray images. The third is utilizing the security of the whole system through encryption when sending user data over the cloud.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127782064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Implementation of a Dockerized, Cross Platform, Multi-Purpose Cryptography as a Service Framework Featuring Scalability, Extendibility and Ease of Integration Dockerized, Cross - Platform, Multi-Purpose Cryptography as a Service Framework的设计与实现，具有可扩展性，可扩展性和易于集成的特点

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009317

A. Merdan, H. Aslan, Nashwa Abdelbaki

{"title":"Design and Implementation of a Dockerized, Cross Platform, Multi-Purpose Cryptography as a Service Framework Featuring Scalability, Extendibility and Ease of Integration","authors":"A. Merdan, H. Aslan, Nashwa Abdelbaki","doi":"10.1109/ESOLEC54569.2022.10009317","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009317","url":null,"abstract":"Following cybersecurity standards nowadays is becoming one of the highest priorities to the digital specialists. Due to the global direction to apply digital transformation, data security is a concern. It becomes crucial to ensure data confidentiality, integrity, and availability whether while transmitting, at rest or even while processing it. The difficulty being faced by organizations, is the challenge of applying the needed security measures. Also, implementing, and maintaining the cryptographic algorithms that ensure the wellness of the data encryption. Having a crypto library or a server that can fit multiple use-cases is either too costly to implement, or expensive to buy (including licensing options, per user/server/year…etc.). The goal of our work is to identify the data protection challenges, by implementing a solution that could match a theoretical hypothesis of having cryptography as a service framework. The term “as a service” has been promoted lately due to its capabilities to provide a ready-made solution by the vendors to satisfy their customer base. In this paper, we are proposing a framework that works cross-platform with ease. It is a scalable, extendible solution with multiple hosting options, from an on-premises hosting to cloud hosting. The proposed framework is implemented and evaluated. The results show that the proposed framework can efficiently process enormous amounts of data. In addition, it could be easily accessed by standard HTTPS requests using JSON format. Also, proving the used deployment technique, we were able to evaluate it on-premises and on cloud with the same allocated resources, getting matching results.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134263651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Knowledge Graph Embeddings in Embedding Based Recommender Systems 知识图嵌入在基于嵌入的推荐系统中的应用

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009491

Ahmed Hussein Ragab, Passant El-Kafrawy

{"title":"Using Knowledge Graph Embeddings in Embedding Based Recommender Systems","authors":"Ahmed Hussein Ragab, Passant El-Kafrawy","doi":"10.1109/ESOLEC54569.2022.10009491","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009491","url":null,"abstract":"This paper proposes using entity2rec [1] which utilizes knowledge graph-based embeddings (node2vec) instead of traditional embedding layers in embedding based recommender systems. This opens the door to increasing the accuracy of some of the most implemented recommender systems running in production in many companies by just replacing the traditional embedding layer with node2vec graph embedding without the risk of completely migrating to newer SOTA systems and risking unexpected performance issues. Also, Graph embeddings will be able to incorporate user and item features which can help in solving the well-known Cold start problem in recommender systems. Both embedding methods are compared on the movie-Lens 100-K dataset in an item-item collaborative filtering recommender and we show that the suggested replacement improves the representation learning of the embedding layer by adding a semantic layer that can increase the overall performance of the normal embedding based recommenders. First, normal Recommender systems are introduced, and a brief explanation of both traditional and graph-based embeddings is presented. Then, the proposed approach is presented along with related work. Finally, results are presented along with future work.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133733125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Gold Price Prediction using Sentiment Analysis 利用情绪分析预测黄金价格

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009529

Mariam Abdou, Menna Shaltout, Alaa Godah, Karim Sobh, Yomna Eid, Walaa Medhat

{"title":"Gold Price Prediction using Sentiment Analysis","authors":"Mariam Abdou, Menna Shaltout, Alaa Godah, Karim Sobh, Yomna Eid, Walaa Medhat","doi":"10.1109/ESOLEC54569.2022.10009529","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009529","url":null,"abstract":"Gold is one of the valuable materials that is used for funding trading purchases. Nowadays, more investors are interested in gold investments due to the sudden increase in gold prices. However, transactions involving gold are risky, the price of gold fluctuates wildly due to the unpredictability of the gold market. Hence, there is a need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper analyzes the correlation between gold price movements and sentiments of Arabic tweets in Egypt. After performing sentiment analysis on these tweets, three supervised machine learning algorithms were used for predicting the gold price. The algorithms include Multiple linear regression, Ridge regression, and Lasso regression. The result of this work shows that the Lasso regression model performs better than the other two models. However, it is concluded that there is a weak correlation between gold prices and Twitter data. Therefore, gold prices cannot be accurately predicted using Twitter data alone.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126514827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fine-tuning Arabic Pre-Trained Transformer Models for Egyptian-Arabic Dialect Offensive Language and Hate Speech Detection and Classification 微调阿拉伯语预训练变压器模型，用于埃及-阿拉伯方言攻击性语言和仇恨言论的检测和分类

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009167

Ibrahim Ahmed, Mostafa Abbas, Rany Hatem, Andrew Ihab, Mohamed Waleed Fahkr

{"title":"Fine-tuning Arabic Pre-Trained Transformer Models for Egyptian-Arabic Dialect Offensive Language and Hate Speech Detection and Classification","authors":"Ibrahim Ahmed, Mostafa Abbas, Rany Hatem, Andrew Ihab, Mohamed Waleed Fahkr","doi":"10.1109/ESOLEC54569.2022.10009167","DOIUrl":"https://doi.org/10.1109/ESOLEC54569.2022.10009167","url":null,"abstract":"Offensive language and Hate Speech are rampant on social media platforms (Facebook, Twitter, etc.) in Egypt for quite a while now, appearing in Tweets, Facebook posts and comments, etc., It is an increasingly outreaching problem that needs immediate attention. This paper focuses on the problem of detecting and classifying both offensive language and Hate Speech using State-of-the-art techniques in text classification. Pre-trained transformer models have gained a reputation of astounding general language understanding that could be fine-tuned for language-specific tasks like Text classification, We collected an Egyptian-Arabic dialect Custom dataset of about 8,000 text samples manually labelled into 5 distinct classes: (Neutral, Offensive, Sexism, Religious Discrimination, Racism), It was used to fine-tune and evaluate multiple different Arabic pre-trained transformer models based on different transformer architectures and pre-training approaches for the Natural Language Processing downstream task of text classification. We achieved an average accuracy of about 96% across all fine-tuned transformer models.","PeriodicalId":179850,"journal":{"name":"2022 20th International Conference on Language Engineering (ESOLEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124073685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Networks for Bilingual Machine Translation Model 基于神经网络的双语机器翻译模型

2022 20th International Conference on Language Engineering (ESOLEC) Pub Date : 2022-10-12 DOI: 10.1109/ESOLEC54569.2022.10009266

Hassanin M. Al-Barhamtoshy, Ashraf Said Qutb Metwalli

引用次数: 0