International Journal of Intelligent Computing and Information Sciences最新文献_第2页

Arabic Negation and Speculation Scope Detection: a Transformer-based Approach. 阿拉伯语否定和推测范围检测:一种基于变压器的方法。

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-07 DOI: 10.21608/ijicis.2023.176628.1232

Ahmed Mahany, Heba Khaled, S. Ghoniemy

{"title":"Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.","authors":"Ahmed Mahany, Heba Khaled, S. Ghoniemy","doi":"10.21608/ijicis.2023.176628.1232","DOIUrl":"https://doi.org/10.21608/ijicis.2023.176628.1232","url":null,"abstract":": Detecting the negation and speculation linguistic phenomena is vital for the performance of Arabic Natural Language Processing (ANLP) tasks. The negation and speculation scope detection problems have been addressed in a number of studies where most of them focused on the English and Spanish languages. This is due to the lack of corpora annotated for negation and speculation. In this work, the ArNeg corpus, annotated with negation, is extended by annotating it for the speculation to build the ArNegSpec corpus. In addition, we propose a transformer-based learning approach for detecting both the negation and speculation in Arabic texts. The AraBERT models with a Bidirectional Long Short-Term Memory and a Conditional Random Field (BiLSTM-CRF) as a sequence classification layer to achieve this goal. The results reached an F1 measure of 98% for cue identification for both negation and speculation. The proposed approach enhanced the evaluation results of the negation scope detection by 6% in terms of the F1 measure compared to the previous study. Furthermore, it achieved a 95% F1 measure for the speculation scope detection and a PCS value of 96% for both the negation and speculation scope. This approach shows the feasibility of transformer-based learning models in the sequence classification tasks as the detection of the negation and speculation in Arabic.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133615777","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

TUNICATE SWARM BASED CLUSTERING AND ROUTING ALGORITHM FOR INTERNET OF THINGS 物联网中基于束状虫群的聚类与路由算法

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.175550.1228

Aya Saad Mohammed Mohammed, I. Hegazy, El-Sayed M. El-Horabty

引用次数: 0

CONVOLUTIONAL NEURAL NETWORK MODELS FOR CANCER TREATMENT RESPONSE PREDICTION 用于癌症治疗反应预测的卷积神经网络模型

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.180508.1239

Hanan Ahmed, Howida A. Shedeed, S. Hamad, A. Saad

引用次数: 0

A RULE LEARNING APPROACH FOR BUILDING AN EXPERT SYSTEM TO DETECT NETWORK INTRUSIONS 基于规则学习的网络入侵检测专家系统构建方法

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.167424.1223

O. Galal, A. Nasr, L. Rizkallah

引用次数: 2

Long-Form Open-Domain Question-Answering System Architecture 长格式开放域问答系统架构

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.185241.1245

Moataz Seliem, Salsabil Amin, M. Aref

引用次数: 0

AN EFFICIENT HIDING METHOD FOR PRIVACY PRESERVING UTILITY MINING 一种有效的保护隐私的效用挖掘隐藏方法

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2022.142694.1191

Mohamed Ali, S. Rady, T. Abdelkader, Tarek G Gharib

引用次数: 1

Prediction Of O-Glycosylation Site Using Pre-Trained Language Model And Machine Learning 使用预训练语言模型和机器学习预测o -糖基化位点

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.160986.1218

Alhasan Alkuhlani, Walaa K. Gad, Mohamed Roushdy, Abdel-Badeeh M. Salem

引用次数: 1

CLASSIFICATION OF DERMATOLOGIC MANIFESTATIONS OF CARDIOVASCULAR DISEASE USING EFFICIENTNETV2 CNN MODEL 应用efficientnetv2 CNN模型对心血管疾病皮肤病表现进行分类

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-03-01 DOI: 10.21608/ijicis.2023.184311.1242

A. Evwiekpaefe, Oghenegueke F. Amrevuawho

引用次数: 0

WEIGHTED ENTITY-LINKING AND INTEGRATION ALGORITHM FOR MEDICAL KNOWLEDGE GRAPH GENERATION 医学知识图谱生成的加权实体链接与集成算法

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-02-26 DOI: 10.21608/ijicis.2023.179031.1236

Noura E. Maghawry, Samy S. A. Ghoniemy, Eman Shaaban, Karim Emara

{"title":"WEIGHTED ENTITY-LINKING AND INTEGRATION ALGORITHM FOR MEDICAL KNOWLEDGE GRAPH GENERATION","authors":"Noura E. Maghawry, Samy S. A. Ghoniemy, Eman Shaaban, Karim Emara","doi":"10.21608/ijicis.2023.179031.1236","DOIUrl":"https://doi.org/10.21608/ijicis.2023.179031.1236","url":null,"abstract":": Semantic data integration is the process of interrelating information from multiple heterogeneous resources. There is a need for representing data concepts and their relationships to eliminate heterogeneity among different data sources in healthcare management systems. Standardized medical ontologies provide predefined medical vocabulary serving as a stable interface for concepts related to medical data sources. However, different ontologies have different concepts although these concepts have logical relations between them such as the Human Disease Ontology and the Symptoms ontology. There aroused a need for a knowledge graph providing a reliable knowledge base for any intelligent healthcare expert advisor disease prediction system. The knowledge graph provides a model for linking and integrating different concepts having logical relationships such as diseases and their symptoms. Medical online website and encyclopedia provides a reliable source for building such a knowledge graph. The knowledge graph is enriched with social networks data where information extracted reflects a major source of data based on user experiences. The paper proposes a framework for constructing a disease-symptom entity linked knowledge graph based on online medical encyclopedia and social networks user experiences. Entity linking such an integrated knowledge graph with standardized medical ontologies makes it a reliable knowledge base for a standard system that could be used by social networks user and the professional staff.","PeriodicalId":244591,"journal":{"name":"International Journal of Intelligent Computing and Information Sciences","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124999433","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

ARCHITECTURE FOR PERSONALITY DETECTION USING ENNEAGRAM KNOWLEDGE: CASE STUDY 使用九型人格知识的人格检测架构:案例研究

International Journal of Intelligent Computing and Information Sciences Pub Date : 2023-02-26 DOI: 10.21608/ijicis.2023.137912.1181

Esraa Abdelhamid, S. Ismail, M. Aref

引用次数: 1