Naguib J. Siphocly, El-Sayed M. El-Horbaty, A. M. Salem
Nowadays, computers are extremely beneficial to music composers. Computer music generation tools are developed for aiding composers in producing satisfying musical pieces. The automation of music composition tasks is a challenging research point, specially to the field of Artificial Intelligence. Converting melodies that are played on a major scale to minor (or vice versa) is interesting to both composers and music listeners. Newly converted melodies of famous songs, either from major to minor or the opposite, are becoming blockbusters on the social media. In this paper we propose an intelligent method for automating the conversion between major and minor melodies using Artificial Intelligence techniques. We run our experiments on melodies in the MIDI format which is a standard music format enabling the communication between computers and various musical devices. We also propose a smart method for musical scale detection for the input melodies. Scale detection is a critical step for correctly converting between major and minor melodies. Additionally, this step is also important as a pre-processing step in various other music retrieval or transformation applications.
{"title":"Intelligent Technique for Automating the Conversion between Major and Minor Melodies","authors":"Naguib J. Siphocly, El-Sayed M. El-Horbaty, A. M. Salem","doi":"10.54623/fue.fcij.4.2.2","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.2","url":null,"abstract":"Nowadays, computers are extremely beneficial to music composers. Computer music generation tools are developed for aiding composers in producing satisfying musical pieces. The automation of music composition tasks is a challenging research point, specially to the field of Artificial Intelligence. Converting melodies that are played on a major scale to minor (or vice versa) is interesting to both composers and music listeners. Newly converted melodies of famous songs, either from major to minor or the opposite, are becoming blockbusters on the social media. In this paper we propose an intelligent method for automating the conversion between major and minor melodies using Artificial Intelligence techniques. We run our experiments on melodies in the MIDI format which is a standard music format enabling the communication between computers and various musical devices. We also propose a smart method for musical scale detection for the input melodies. Scale detection is a critical step for correctly converting between major and minor melodies. Additionally, this step is also important as a pre-processing step in various other music retrieval or transformation applications.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83744677","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}
Mervat Ragab Bakry, Mona M. Nasr, Fahad Kamal Al-sheref
Online social networks (OSNs) have become essential ways for users to socially share information and feelings, communicate, and thoughts with others through online social networks. Online social networks such as Twitter and Facebook are some of the most common OSNs among users. Users’ behaviors on social networks aid researchers for detecting and understanding their online behaviors and personality traits. Personality detection is one of the new difficulties in social networks. Machine learning techniques are used to build models for understanding personality, detecting personality traits, and classifying users into different kinds through user generated content based on different features and measures of psychological models such as PEN (Psychoticism, Extraversion, and Neuroticism) model, DISC (Dominance, Influence, Steadiness, and Compliance) model, and the Big-five model (Openness, Extraversion, Consciousness, Agreeableness, and Neurotic) which is the most accepted model of personality. This survey discusses the existing works on psychological personality classification.
在线社交网络(Online social network，简称osn)已经成为用户通过在线社交网络与他人分享信息和感受、交流思想的重要方式。Twitter和Facebook等在线社交网络是用户最常用的osn。用户在社交网络上的行为有助于研究人员发现和理解他们的在线行为和人格特征。人格检测是社交网络的新难点之一。基于PEN (Psychoticism, Extraversion, Neuroticism)模型、DISC (Dominance, Influence, Steadiness, and Compliance)模型、Big-five (Openness, Extraversion, Consciousness, Agreeableness)模型等心理模型的不同特征和度量，利用机器学习技术构建理解人格、检测人格特征的模型，并通过用户生成的内容将用户分类为不同的类型。和神经质)，这是最被接受的人格模型。本文对现有的心理人格分类研究进行了综述。
{"title":"A Survey of Psychological Personality Classification Approaches","authors":"Mervat Ragab Bakry, Mona M. Nasr, Fahad Kamal Al-sheref","doi":"10.54623/fue.fcij.4.2.3","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.3","url":null,"abstract":"Online social networks (OSNs) have become essential ways for users to socially share information and feelings, communicate, and thoughts with others through online social networks. Online social networks such as Twitter and Facebook are some of the most common OSNs among users. Users’ behaviors on social networks aid researchers for detecting and understanding their online behaviors and personality traits. Personality detection is one of the new difficulties in social networks. Machine learning techniques are used to build models for understanding personality, detecting personality traits, and classifying users into different kinds through user generated content based on different features and measures of psychological models such as PEN (Psychoticism, Extraversion, and Neuroticism) model, DISC (Dominance, Influence, Steadiness, and Compliance) model, and the Big-five model (Openness, Extraversion, Consciousness, Agreeableness, and Neurotic) which is the most accepted model of personality. This survey discusses the existing works on psychological personality classification.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"111 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91553841","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}
Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces a review and an analysis related SCG techniques. Moreover, comparisons are presented for: techniques mapping, Natural Language Processing (NLP), knowledgebase, ontology, Specification Configuration Template (SCT) model and deep learning.
{"title":"Ontological Engineering For Source Code Generation","authors":"Anas Alokla, Walaa K. Gad, M. Aref, A. M. Salem","doi":"10.54623/fue.fcij.4.2.1","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.1","url":null,"abstract":"Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces a review and an analysis related SCG techniques. Moreover, comparisons are presented for: techniques mapping, Natural Language Processing (NLP), knowledgebase, ontology, Specification Configuration Template (SCT) model and deep learning.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73271355","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}
Colon cancer is also referred to as colorectal cancer, a kind of cancer that starts with colon damage to the large intestine in the last section of the digestive tract. Elderly people typically suffer from colon cancer, but this may occur at any age.It normally starts as little, noncancerous (benign) mass of cells named polyps that structure within the colon. After a period of time these polyps can turn into advanced malignant tumors that attack the human body and some of these polyps can become colon cancers. So far, no concrete causes have been identified and the complete cancer treatment is very difficult to be detected by doctors in the medical field. Colon cancer often has no symptoms in early stage so detecting it at this stage is curable but colorectal cancer diagnosis in the final stages (stage IV), gives it the opportunity to spread to different pieces of the body, difficult to treat successfully, and the person's chances of survival are much lower. False diagnosis of colorectal cancer which mean wrong treatment for patients with long-term infections and they are suffering from colon cancer this causing the death for these patients. Also, the cancer treatment needs more time and a lot of money. This paper provides a comparative study for methodologies and algorithms used in colon cancer diagnoses and detection this can help for proposing a prediction for risk levels of colon cancer disease using CNN algorithm of the deep learning (Convolutional Neural Networks Algorithm).
{"title":"A Comparative Study for Methodologies and Algorithms Used In Colon Cancer Diagnoses and Detection","authors":"Mona Nasr, Laila Abdelhamid, NaglaaSaeed Shehata","doi":"10.54623/fue.fcij.4.2.6","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.6","url":null,"abstract":"Colon cancer is also referred to as colorectal cancer, a kind of cancer that starts with colon damage to the large intestine in the last section of the digestive tract. Elderly people typically suffer from colon cancer, but this may occur at any age.It normally starts as little, noncancerous (benign) mass of cells named polyps that structure within the colon. After a period of time these polyps can turn into advanced malignant tumors that attack the human body and some of these polyps can become colon cancers. So far, no concrete causes have been identified and the complete cancer treatment is very difficult to be detected by doctors in the medical field. Colon cancer often has no symptoms in early stage so detecting it at this stage is curable but colorectal cancer diagnosis in the final stages (stage IV), gives it the opportunity to spread to different pieces of the body, difficult to treat successfully, and the person's chances of survival are much lower. False diagnosis of colorectal cancer which mean wrong treatment for patients with long-term infections and they are suffering from colon cancer this causing the death for these patients. Also, the cancer treatment needs more time and a lot of money. This paper provides a comparative study for methodologies and algorithms used in colon cancer diagnoses and detection this can help for proposing a prediction for risk levels of colon cancer disease using CNN algorithm of the deep learning (Convolutional Neural Networks Algorithm).","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73621675","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}
Dalia Rizk, Hoda Hosny Prof. Dr., El-Sayed M. El-Horbaty Prof. Dr., Abdel-Badeeh M. Salem Prof. Dr.
Smart healthcare is of great interest to researchers and governments due to the increasing development of new smart cities. However, there is no current standard practice to format the cloud computing infrastructure and to assist the healthcare system architect in designing a comprehensive solution for the basic services that are required by the healthcare users while taking into consideration a balanced approach towards their specific functional and non-functional needs such as openness, scalability, concurrency, interoperability and security factors. The integration of smart healthcare services with cloud computing needs a concrete framework. The main objective of this paper is to analyze the different frameworks that discuss smart healthcare services and reach to a conclusion of the common factors to arrive at a unified and smart framework
{"title":"Proposed Framework for Smart Healthcare Services","authors":"Dalia Rizk, Hoda Hosny Prof. Dr., El-Sayed M. El-Horbaty Prof. Dr., Abdel-Badeeh M. Salem Prof. Dr.","doi":"10.54623/fue.fcij.4.2.4","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.4","url":null,"abstract":"Smart healthcare is of great interest to researchers and governments due to the increasing development of new smart cities. However, there is no current standard practice to format the cloud computing infrastructure and to assist the healthcare system architect in designing a comprehensive solution for the basic services that are required by the healthcare users while taking into consideration a balanced approach towards their specific functional and non-functional needs such as openness, scalability, concurrency, interoperability and security factors. The integration of smart healthcare services with cloud computing needs a concrete framework. The main objective of this paper is to analyze the different frameworks that discuss smart healthcare services and reach to a conclusion of the common factors to arrive at a unified and smart framework","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81563127","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}
Hossam Eldin Mohammed Abd El-Hamid Ahmed Abdou, W. Khalifa, Mohamed Roushdy, A. Salem
The term “fraud”, it always concerned about credit card fraud in our minds. And after the significant increase in the transactions of credit card, the fraud of credit card increased extremely in last years. So the fraud detection should include surveillance of the spending attitude for the person/customer to the determination, avoidance, and detection of unwanted behavior. Because the credit card is the most payment predominant way for the online and regular purchasing, the credit card fraud raises highly. The Fraud detection is not only concerned with capturing of the fraudulent practices, but also, discover it as fast as they can, because the fraud costs millions of dollar business loss and it is rising over time, and that affects greatly the worldwide economy. . In this paper we introduce 14 different techniques of how data mining techniques can be successfully combined to obtain a high fraud coverage with a high or low false rate, the Advantage and The Disadvantages of every technique, and The Data Sets used in the researches by researcher
{"title":"Machine Learning Techniques for Credit Card Fraud Detection","authors":"Hossam Eldin Mohammed Abd El-Hamid Ahmed Abdou, W. Khalifa, Mohamed Roushdy, A. Salem","doi":"10.54623/fue.fcij.4.2.5","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.2.5","url":null,"abstract":"The term “fraud”, it always concerned about credit card fraud in our minds. And after the significant increase in the transactions of credit card, the fraud of credit card increased extremely in last years. So the fraud detection should include surveillance of the spending attitude for the person/customer to the determination, avoidance, and detection of unwanted behavior. Because the credit card is the most payment predominant way for the online and regular purchasing, the credit card fraud raises highly. The Fraud detection is not only concerned with capturing of the fraudulent practices, but also, discover it as fast as they can, because the fraud costs millions of dollar business loss and it is rising over time, and that affects greatly the worldwide economy. . In this paper we introduce 14 different techniques of how data mining techniques can be successfully combined to obtain a high fraud coverage with a high or low false rate, the Advantage and The Disadvantages of every technique, and The Data Sets used in the researches by researcher","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75302258","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}
E-learning has become a prominent and effective role in recent years. The factor of place and time became ineffective in the educational process. So that anyone can learn anywhere in the world. The educational services that benefit the learner during the educational process as well as the factors of assistance are important elements that help in the success of the educational process in the environment of e-learning. The more these services, the greater the benefit from e-learning. But its way of reviewing electronic content is still ineffective. Therefore it was necessary to create a suitable environment for the learner is similar to the real reality. Through which the learner feels the integration and concentration in the academic content as if it were realistic. So, the trend was to take advantage of the virtual reality technology that have become effective in all fields. The use of this technology will help the learner gain more realism and make full use of the electronic content. This study reviews the effect of the use of virtual reality technology in the review of the learner's electronic content, as well as the attitudes and opinions of the students of the Business Information Systems program at the Faculty of Commerce, Helwan University, Cairo, Egypt, about the use of this technology and to what extent will effect on change and effectiveness in the quality of educational process
{"title":"A General Approach Students’ Attitude towards to Virtual Reality Technology in Distance Education Environment","authors":"M. Abdelsalam","doi":"10.54623/fue.fcij.4.1.2","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.1.2","url":null,"abstract":"E-learning has become a prominent and effective role in recent years. The factor of place and time became ineffective in the educational process. So that anyone can learn anywhere in the world. The educational services that benefit the learner during the educational process as well as the factors of assistance are important elements that help in the success of the educational process in the environment of e-learning. The more these services, the greater the benefit from e-learning. But its way of reviewing electronic content is still ineffective. Therefore it was necessary to create a suitable environment for the learner is similar to the real reality. Through which the learner feels the integration and concentration in the academic content as if it were realistic. So, the trend was to take advantage of the virtual reality technology that have become effective in all fields. The use of this technology will help the learner gain more realism and make full use of the electronic content. This study reviews the effect of the use of virtual reality technology in the review of the learner's electronic content, as well as the attitudes and opinions of the students of the Business Information Systems program at the Faculty of Commerce, Helwan University, Cairo, Egypt, about the use of this technology and to what extent will effect on change and effectiveness in the quality of educational process","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78483378","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}
Now a days, have a great dependence on computer and network and the security of computer related to the whole world and everybody. Cryptography is the art and science of achieving security by encoding message to make them non readable, to secure data information transmits over the network, In this paper introduced modified RSA approach based on multi keys and Chinese remainder theorem (CRT), which RSA algorithm is asymmetric key encryption technique. The objective of this Technique is to provide secure transmission of data between any networks. Which is the Network security is an activity which is designed to provide the usage protection and integrity of the Network and data. So that only the user allowed can read and process it, the objective of this paper Enhancement the performance of RSA and increase the security. In proposed model RSA will be implemented using java.
{"title":"Improved RSA security using Chinese Remainder Theorem and Multiple Keys","authors":"Hatem Abdulkader, Rasha Samir, Reda M. Hussien","doi":"10.54623/fue.fcij.4.1.1","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.1.1","url":null,"abstract":"Now a days, have a great dependence on computer and network and the security of computer related to the whole world and everybody. Cryptography is the art and science of achieving security by encoding message to make them non readable, to secure data information transmits over the network, In this paper introduced modified RSA approach based on multi keys and Chinese remainder theorem (CRT), which RSA algorithm is asymmetric key encryption technique. The objective of this Technique is to provide secure transmission of data between any networks. Which is the Network security is an activity which is designed to provide the usage protection and integrity of the Network and data. So that only the user allowed can read and process it, the objective of this paper Enhancement the performance of RSA and increase the security. In proposed model RSA will be implemented using java.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"14 Dermatol Sect 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82955596","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}
Requirements validation is one of the most significant and critical parts of the requirements engineering. This activity ensures that the set of requirements is accurate, right, complete, and consistent. Requirements validation is considered as the key activity because mistakes found in a software requirements document can lead to extensive rework costs when they are discovered either during development or after the system is in service. There are some commonly used bases to validate user requirements such as: Natural language, Design description languages, Graphical notations and Mathematical specification languages. Whereas the graphical notations are the most suitable means to be used in software requirements validation because it is easy to understand, and it can be easily created by analyst and time took. Therefore, this paper adopts the map concept which is a graphical technique for discovering the hidden flaws in software requirements in the early phases of software development lifecycle.
{"title":"Adaptive Concept Map Approach for Software Requirements Validation","authors":"Ahmed A. Ahmed, Ayman E. Khedr, S. Kholeif","doi":"10.54623/fue.fcij.4.1.4","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.1.4","url":null,"abstract":"Requirements validation is one of the most significant and critical parts of the requirements engineering. This activity ensures that the set of requirements is accurate, right, complete, and consistent. Requirements validation is considered as the key activity because mistakes found in a software requirements document can lead to extensive rework costs when they are discovered either during development or after the system is in service. There are some commonly used bases to validate user requirements such as: Natural language, Design description languages, Graphical notations and Mathematical specification languages. Whereas the graphical notations are the most suitable means to be used in software requirements validation because it is easy to understand, and it can be easily created by analyst and time took. Therefore, this paper adopts the map concept which is a graphical technique for discovering the hidden flaws in software requirements in the early phases of software development lifecycle.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"157 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77762133","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}
Mohamed H. Haggag, Marwa M. A. ELFattah, Ahmed Mohammed Ahmed
Measuring Text similarity problem still one of opened fields for research area in natural language processing and text related research such as text mining, Web page retrieval, information retrieval and textual entailment. Several measures have been developed for measuring similarity between two texts: such as Wu and Palmer, Leacock and Chodorow measure and others . But these measures do not take into consideration the contextual information of the text .This paper introduces new model for measuring semantic similarity between two text segments. This model is based on building new contextual structure for extracting semantic similarity. This approach can contribute in solving many NLP problems such as te xt entailment and information retrieval fields.
{"title":"Similarity Evaluation Based on Contextual Modelling","authors":"Mohamed H. Haggag, Marwa M. A. ELFattah, Ahmed Mohammed Ahmed","doi":"10.54623/fue.fcij.4.1.5","DOIUrl":"https://doi.org/10.54623/fue.fcij.4.1.5","url":null,"abstract":"Measuring Text similarity problem still one of opened fields for research area in natural language processing and text related research such as text mining, Web page retrieval, information retrieval and textual entailment. Several measures have been developed for measuring similarity between two texts: such as Wu and Palmer, Leacock and Chodorow measure and others . But these measures do not take into consideration the contextual information of the text .This paper introduces new model for measuring semantic similarity between two text segments. This model is based on building new contextual structure for extracting semantic similarity. This approach can contribute in solving many NLP problems such as te xt entailment and information retrieval fields.","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83497533","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}
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