Agriculture is one of the most crucial needs of the life since it supports human and animals with food supplies and benefits the human employment and the national economy. Wireless Sensor Network (WSN) has recently applied in precision agriculture to improve the crop yields and apply the agricultural resources at right time and place. In this paper, Greenhouse Smart Management System (GSMS) using WSNs is designed and developed to automatically control, manage and monitor the agricultural parameters and activities inside the greenhouses. The ambient relative humidity and temperature of the greenhouse are measured using sensor nodes. When the sensed parameters exceed threshold values, the irrigation and cooling activities are triggered by activating the fan and water pump devices. GSMS includes also an algorithm to compute the period of irrigation and coolingaccording to the measured agricultural parameters. Hardware and software for the proposed GSMS are developed in this paper. The results show that the GSMS can save the agricultural resources and improve the crop yields, compared with other traditional schemes.
{"title":"Precision Agriculture for Greenhouses Using a Wireless Sensor Network","authors":"Yousef E. M. Hamouda, Basel H. Y. Elhabil","doi":"10.1109/PICICT.2017.20","DOIUrl":"https://doi.org/10.1109/PICICT.2017.20","url":null,"abstract":"Agriculture is one of the most crucial needs of the life since it supports human and animals with food supplies and benefits the human employment and the national economy. Wireless Sensor Network (WSN) has recently applied in precision agriculture to improve the crop yields and apply the agricultural resources at right time and place. In this paper, Greenhouse Smart Management System (GSMS) using WSNs is designed and developed to automatically control, manage and monitor the agricultural parameters and activities inside the greenhouses. The ambient relative humidity and temperature of the greenhouse are measured using sensor nodes. When the sensed parameters exceed threshold values, the irrigation and cooling activities are triggered by activating the fan and water pump devices. GSMS includes also an algorithm to compute the period of irrigation and coolingaccording to the measured agricultural parameters. Hardware and software for the proposed GSMS are developed in this paper. The results show that the GSMS can save the agricultural resources and improve the crop yields, compared with other traditional schemes.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998380","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}
Multi document summarization focuses on extracting the most significant information from a collection of textual documents. Most summarization techniques require the data to be centralized, which may not be feasible in many cases due to computational and storage limitations. The huge increase of data emerging by the progress of technology and the various sources makes automatic text summarization of large scale of data a challenging task. We propose an approach for automatic text summarization of large scale Arabic multiple documents using Genetic algorithm and MapReduce parallel programming model. The approach insures scalability, speed and accuracy in summary generation. It eliminates sentence redundancy and increases readability and cohesion factors between the sentences of summaries. The experiments resulted in acceptable precision and recall scores. This indicates that the system successfully identifies the most important sentences. In Addition to all to that, the approach provided up to 10x speedup score, which is faster than on a single machine. Therefore, it can deal with large-scale datasets successfully. Finally, the efficiency score of the proposed approach indicates that the large data set utilizes the available resources up to 62%.
{"title":"Automatic Arabic Text Summarization for Large Scale Multiple Documents Using Genetic Algorithm and MapReduce","authors":"R. Baraka, Sulaiman N. Al Breem","doi":"10.1109/PICICT.2017.32","DOIUrl":"https://doi.org/10.1109/PICICT.2017.32","url":null,"abstract":"Multi document summarization focuses on extracting the most significant information from a collection of textual documents. Most summarization techniques require the data to be centralized, which may not be feasible in many cases due to computational and storage limitations. The huge increase of data emerging by the progress of technology and the various sources makes automatic text summarization of large scale of data a challenging task. We propose an approach for automatic text summarization of large scale Arabic multiple documents using Genetic algorithm and MapReduce parallel programming model. The approach insures scalability, speed and accuracy in summary generation. It eliminates sentence redundancy and increases readability and cohesion factors between the sentences of summaries. The experiments resulted in acceptable precision and recall scores. This indicates that the system successfully identifies the most important sentences. In Addition to all to that, the approach provided up to 10x speedup score, which is faster than on a single machine. Therefore, it can deal with large-scale datasets successfully. Finally, the efficiency score of the proposed approach indicates that the large data set utilizes the available resources up to 62%.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129212191","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}
Omar E. Elejla, B. Belaton, Mohammed Anbar, Issa M. Smadi
ICMPv6 is vulnerable to a set of attacks that contributes to preventing IPv6 from being trusted for full implementations on today's networks. One of these attacks is Router Advertisement (RA) flooding attack by sending a huge traffic toward a victim to consume its resources and stop its services. To detect these attacks, classification processes are applied based on a set of features used to represent the network traffic. This paper proposes a set of representative features depends on a suitable formation of data using a flow representation of the traffic. The proposed features and representation have achieved an acceptable detection ability of the RA flooding attacks using several classification techniques. Moreover, the achieved detection ability might be further improved by extracting more representative features or selecting a subset of them to represent the traffic.
{"title":"A New Set of Features for Detecting Router Advertisement Flooding Attacks","authors":"Omar E. Elejla, B. Belaton, Mohammed Anbar, Issa M. Smadi","doi":"10.1109/PICICT.2017.19","DOIUrl":"https://doi.org/10.1109/PICICT.2017.19","url":null,"abstract":"ICMPv6 is vulnerable to a set of attacks that contributes to preventing IPv6 from being trusted for full implementations on today's networks. One of these attacks is Router Advertisement (RA) flooding attack by sending a huge traffic toward a victim to consume its resources and stop its services. To detect these attacks, classification processes are applied based on a set of features used to represent the network traffic. This paper proposes a set of representative features depends on a suitable formation of data using a flow representation of the traffic. The proposed features and representation have achieved an acceptable detection ability of the RA flooding attacks using several classification techniques. Moreover, the achieved detection ability might be further improved by extracting more representative features or selecting a subset of them to represent the traffic.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123855994","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}
Haider Dhia Zubaydi, Mohammed Anbar, Chong Yung Wey
The evolution of information and communication technologies has brought new challenges in managing the Internet. Software-Defined Networking (SDN) aims to provide easily configured and remotely controlled networks based on centralized control. Since SDN will be the next disruption in networking, SDN security has become a hot research topic because of its importance in communication systems. A centralized controller can become a focal point of attack, thus preventing attack in controller will be a priority. The whole network will be affected if attacker gain access to the controller. One of the attacks that affect SDN controller is DDoS attacks. This paper reviews different detection techniques that are available to prevent DDoS attacks, characteristics of these techniques and issues that may arise using these techniques.
{"title":"Review on Detection Techniques against DDoS Attacks on a Software-Defined Networking Controller","authors":"Haider Dhia Zubaydi, Mohammed Anbar, Chong Yung Wey","doi":"10.1109/PICICT.2017.26","DOIUrl":"https://doi.org/10.1109/PICICT.2017.26","url":null,"abstract":"The evolution of information and communication technologies has brought new challenges in managing the Internet. Software-Defined Networking (SDN) aims to provide easily configured and remotely controlled networks based on centralized control. Since SDN will be the next disruption in networking, SDN security has become a hot research topic because of its importance in communication systems. A centralized controller can become a focal point of attack, thus preventing attack in controller will be a priority. The whole network will be affected if attacker gain access to the controller. One of the attacks that affect SDN controller is DDoS attacks. This paper reviews different detection techniques that are available to prevent DDoS attacks, characteristics of these techniques and issues that may arise using these techniques.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129453733","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}
Nowadays, many people express their opinions using user generated contains such as social media, forums and reviews. Opinion mining is a field of study that extracts sentiments from user generated contents. Because of the complexity of the Arabic language, extracting those opinions are challenging. Better representation of reviews can help to improve extraction of opinions. The traditional way of representing opinion documents is using Bag-of-Words where the word is presented in fixed-length. The problem of this presentation is that it loses the order of the word and it ignores grammatical structure and lexicon-dependent. To overcome these limitations, distributed representations can be employed. It is based on learning vector representations of words, which also called "word embeddings". It can make the performance of natural language processing tasks have better performance with the help of learning algorithms. This representation uses neural networks and makes the learned vectors explicitly encode many linguistic patterns. In this study, we used distributed representations for Arabic opinion mining and compare it with Bag of Words (BOW) representation. We applied them on four benchmark datasets. Then, we used four machine learning methods which are Support Vector Machine, Logistic Regression and Random Forest. Using f-measure metric, we found that, in all datasets and all methods we used in our experiment, the distributed representations have better performance than bag-of-words representation.
{"title":"Arabic Opinion Mining Using Distributed Representations of Documents","authors":"A. El-Halees","doi":"10.1109/PICICT.2017.15","DOIUrl":"https://doi.org/10.1109/PICICT.2017.15","url":null,"abstract":"Nowadays, many people express their opinions using user generated contains such as social media, forums and reviews. Opinion mining is a field of study that extracts sentiments from user generated contents. Because of the complexity of the Arabic language, extracting those opinions are challenging. Better representation of reviews can help to improve extraction of opinions. The traditional way of representing opinion documents is using Bag-of-Words where the word is presented in fixed-length. The problem of this presentation is that it loses the order of the word and it ignores grammatical structure and lexicon-dependent. To overcome these limitations, distributed representations can be employed. It is based on learning vector representations of words, which also called \"word embeddings\". It can make the performance of natural language processing tasks have better performance with the help of learning algorithms. This representation uses neural networks and makes the learned vectors explicitly encode many linguistic patterns. In this study, we used distributed representations for Arabic opinion mining and compare it with Bag of Words (BOW) representation. We applied them on four benchmark datasets. Then, we used four machine learning methods which are Support Vector Machine, Logistic Regression and Random Forest. Using f-measure metric, we found that, in all datasets and all methods we used in our experiment, the distributed representations have better performance than bag-of-words representation.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132002904","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}
Wikipedia encyclopedia is an attractive source for comparable corpora in many languages. Most researchers develop their own script to perform document alignment task, which requires efforts and time. In this paper, we present WikiDocsAligner, an off-the-shelf Wikipedia Articles alignment handy tool. The implementation of WikiDocsAligner does not require the researchers to import/export of interlanguage links databases. The user just need to download Wikipedia dumps (interlanguage links and articles), then provide them to the tool, which performs the alignment. This software can be used easily to align Wikipedia documents in any language pair. Finally, we use WikiDocsAligner to align comparable documents from Arabic Wikipedia and Egyptian Wikipedia. So we shed the light on Wikipedia as a source of Arabic dialects language resources. The produced resources is interesting and useful as the demand on Arabic/dialects language resources increased in the last decade.
{"title":"WikiDocsAligner: An Off-the-Shelf Wikipedia Documents Alignment Tool","authors":"Motaz Saad, B. Alijla","doi":"10.1109/PICICT.2017.27","DOIUrl":"https://doi.org/10.1109/PICICT.2017.27","url":null,"abstract":"Wikipedia encyclopedia is an attractive source for comparable corpora in many languages. Most researchers develop their own script to perform document alignment task, which requires efforts and time. In this paper, we present WikiDocsAligner, an off-the-shelf Wikipedia Articles alignment handy tool. The implementation of WikiDocsAligner does not require the researchers to import/export of interlanguage links databases. The user just need to download Wikipedia dumps (interlanguage links and articles), then provide them to the tool, which performs the alignment. This software can be used easily to align Wikipedia documents in any language pair. Finally, we use WikiDocsAligner to align comparable documents from Arabic Wikipedia and Egyptian Wikipedia. So we shed the light on Wikipedia as a source of Arabic dialects language resources. The produced resources is interesting and useful as the demand on Arabic/dialects language resources increased in the last decade.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663997","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}
Imad A. Shaheen, A. Zekry, F. Newagy, Reem Ibrahim
Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC/OQAM) may be one of the best waveform used in the next generation wireless communication system (5G system). Moreover, The FBMC/OQAM system supports high data rate, low impulse noise and high bandwidth efficiency. However, Similar to Orthogonal frequency-division multiplexing OFDM system, the FBMC/OQAM system are the type of multicarrier modulation system (MCM) which suffers from high peak to average power ratio (PAPR) problem cases reduced power efficiency. In this paper, We propose a nonlinear companding scheme called 'Absolute Exponential Companding' (AEXC) to reduced PAPR in FBMC/OQAM system. However, the FBMC/OQAM system is employed with prototype filter bank using square root raised cosine (SRRC) filter. The simulation results show that, The proposed schemes highly effectively reduces the PAPR in the system by compressing the peak signals and expanding the small signals.
{"title":"Absolute Exponential Companding to Reduced PAPR for FBMC/OQAM","authors":"Imad A. Shaheen, A. Zekry, F. Newagy, Reem Ibrahim","doi":"10.1109/PICICT.2017.17","DOIUrl":"https://doi.org/10.1109/PICICT.2017.17","url":null,"abstract":"Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC/OQAM) may be one of the best waveform used in the next generation wireless communication system (5G system). Moreover, The FBMC/OQAM system supports high data rate, low impulse noise and high bandwidth efficiency. However, Similar to Orthogonal frequency-division multiplexing OFDM system, the FBMC/OQAM system are the type of multicarrier modulation system (MCM) which suffers from high peak to average power ratio (PAPR) problem cases reduced power efficiency. In this paper, We propose a nonlinear companding scheme called 'Absolute Exponential Companding' (AEXC) to reduced PAPR in FBMC/OQAM system. However, the FBMC/OQAM system is employed with prototype filter bank using square root raised cosine (SRRC) filter. The simulation results show that, The proposed schemes highly effectively reduces the PAPR in the system by compressing the peak signals and expanding the small signals.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128720666","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}
A. Haron, S. Sahibuddin, Haizan Yusoff, M. H. Osman
Best practices in developing Requirements Engineering are not new. They are easily comprehended by experts familiar to Requirements Engineering. However, for IT Personnel that are new to this field, understanding the process may pose major challenges. Thus, a Requirements Engineering Best Practices Work Flow was developed as a tool to assist in the development of Requirements Engineering. The work flow consists of four phases: Exploratory, Development, Measurement and Experts panel review. Hopefully, this Requirements Engineering Best Practices Work Flow will be a practical and helpful tool to any IT Personnel in developing Requirements Engineering in the organization.
{"title":"Systematic Approach Based on Best Practices to Develop Requirements Engineering (RE) Guideline in an Organization","authors":"A. Haron, S. Sahibuddin, Haizan Yusoff, M. H. Osman","doi":"10.1109/PICICT.2017.31","DOIUrl":"https://doi.org/10.1109/PICICT.2017.31","url":null,"abstract":"Best practices in developing Requirements Engineering are not new. They are easily comprehended by experts familiar to Requirements Engineering. However, for IT Personnel that are new to this field, understanding the process may pose major challenges. Thus, a Requirements Engineering Best Practices Work Flow was developed as a tool to assist in the development of Requirements Engineering. The work flow consists of four phases: Exploratory, Development, Measurement and Experts panel review. Hopefully, this Requirements Engineering Best Practices Work Flow will be a practical and helpful tool to any IT Personnel in developing Requirements Engineering in the organization.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114268717","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}
The ability to check the location of people or mobile devices (MD) in indoor environment has a large number of application. Indoor Positioning System (IPS) utilizes many existing technologies such as radio frequencies, magnetic fields, acoustic signals, thermal, optical or other sensors. WLAN IPS become one of the most favorite solutions because it is already widely exist and provide good accuracy. Fingerprint is one of the methods in WLAN IPS. The performance of this method is greatly affected by received signal strength indicator (RSSI). In fact RSSI value is very dynamic and influenced by environmental conditions inside the room such as walls, ceiling and also human presence. This paper presented an experiment to explore the effect of many people around MD to the RSSI and position error of IPS. People around MD at certain distance and position will be barrier for WLAN signal, therefore the RSSI will decrease. The average of position error because of that effect is 11.34 meter.
{"title":"Effect of People around User to WLAN Indoor Positioning System Accuracy","authors":"Firdaus, Noor Azurati Ahmad, S. Sahibuddin","doi":"10.1109/PICICT.2017.21","DOIUrl":"https://doi.org/10.1109/PICICT.2017.21","url":null,"abstract":"The ability to check the location of people or mobile devices (MD) in indoor environment has a large number of application. Indoor Positioning System (IPS) utilizes many existing technologies such as radio frequencies, magnetic fields, acoustic signals, thermal, optical or other sensors. WLAN IPS become one of the most favorite solutions because it is already widely exist and provide good accuracy. Fingerprint is one of the methods in WLAN IPS. The performance of this method is greatly affected by received signal strength indicator (RSSI). In fact RSSI value is very dynamic and influenced by environmental conditions inside the room such as walls, ceiling and also human presence. This paper presented an experiment to explore the effect of many people around MD to the RSSI and position error of IPS. People around MD at certain distance and position will be barrier for WLAN signal, therefore the RSSI will decrease. The average of position error because of that effect is 11.34 meter.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130776751","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}
The information systems are widely spread in most official institutions, and become certified in all areas of our life such as education, health and entertainment. Usability is one of the most important factors, which encourages users to deal with these systems or refuse it. Data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. In this paper we analyze the stored data in database of Palestinian Government decisions system in order to study the relationship between some attributes. Accordingly, we can find patterns that help us to make the system more user-friendly by offering suggestions to the users during data entry process. Naive Bayes, Rule Induction, K-NN, and Decision Tree methods are applied to the stored data in order to produce a prediction model that predicts entries to the user during the entry process, which can make the entry system more user-friendly. The experiment result shows the Naïve Bayes is the best model among the other techniques by achieving the highest accuracy of 68.41%. Future efforts can apply this model in the Government decisions system of Palestinian Ministers Council in Gaza.
{"title":"Predicting User Entries by Using Data Mining Algorithms","authors":"Basel A. Alhaj, Ashraf Y. A. Maghari","doi":"10.1109/PICICT.2017.24","DOIUrl":"https://doi.org/10.1109/PICICT.2017.24","url":null,"abstract":"The information systems are widely spread in most official institutions, and become certified in all areas of our life such as education, health and entertainment. Usability is one of the most important factors, which encourages users to deal with these systems or refuse it. Data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. In this paper we analyze the stored data in database of Palestinian Government decisions system in order to study the relationship between some attributes. Accordingly, we can find patterns that help us to make the system more user-friendly by offering suggestions to the users during data entry process. Naive Bayes, Rule Induction, K-NN, and Decision Tree methods are applied to the stored data in order to produce a prediction model that predicts entries to the user during the entry process, which can make the entry system more user-friendly. The experiment result shows the Naïve Bayes is the best model among the other techniques by achieving the highest accuracy of 68.41%. Future efforts can apply this model in the Government decisions system of Palestinian Ministers Council in Gaza.","PeriodicalId":259869,"journal":{"name":"2017 Palestinian International Conference on Information and Communication Technology (PICICT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129507423","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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