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Prof Mo Saraee's Outputs (181)

EasyMiner: data mining in medical databases (1998)
Presentation / Conference
Saraee, M., Koundourakis, G., & Theodoulidis, B. (1998, October). EasyMiner: data mining in medical databases. Presented at IEE Colloquium on Intelligent Methods in Healthcare and Medical Applications, York, UK

Data mining techniques have rarely been applied to medical domain. The University of Manchester Institute of Science and Technology (UMIST) is currently in the process of experimenting with a data mining project using an extensive clinical database o... Read More about EasyMiner: data mining in medical databases.

Data mining in temporal databases (1998)
Presentation / Conference
Saraee, M., & Theodoulidis, B. (1998, October). Data mining in temporal databases. Presented at Panhellenic Conference on New Information Technology Athens, Hellas, Athens, Greece

Knowledge discovery in temporal databases (1995)
Presentation / Conference
Saraee, M., & Theodoulidis, B. (1995, February). Knowledge discovery in temporal databases. Presented at IEE Colloquium on Knowledge Discovery in Databases, London, UK

Knowledge discovery in databases is the process of applying statistical, machine learning and other techniques to conventional database systems. Our survey in knowledge discovery systems has indicated that up to date there is no knowledge discovery s... Read More about Knowledge discovery in temporal databases.

Applying NLP to build a cold reading chatbot
Presentation / Conference
Tracey, P., Saraee, M., & Hughes, C. Applying NLP to build a cold reading chatbot. Presented at ISEEIE 2021: 2021 International Symposium on Electrical, Electronics and Information Engineering, Seoul, Republic of Korea

Chatbots are computer programs designed to simulate conversation by interacting with a human user. In this paper we present a chatbot framework designed specifically to aid prolonged grief disorder (PGD) sufferers by replicating the techniques perfor... Read More about Applying NLP to build a cold reading chatbot.

Data science in public mental health : a new analytic framework
Presentation / Conference
Silva, H., Saraee, M., & Saraee, M. Data science in public mental health : a new analytic framework. Presented at IEEE Symposium on Computers and Communications June 30 - July 3, 2019 – Barcelona, Spain

Understanding public mental health issues and finding solutions can be complex and requires advanced techniques, compared to conventional data analysis projects. It is important to have a comprehensive project management process to ensure that... Read More about Data science in public mental health : a new analytic framework.

Latent dirichlet markov allocation for sentiment analysis
Presentation / Conference
Bagheri, A., Saraee, M., & de Jong, F. Latent dirichlet markov allocation for sentiment analysis. Presented at The Fifth European Conference on Intelligent Management Systems in Operations (IMSIO 5), Thinklab, University of Salford

In recent years probabilistic topic models have gained tremendous attention in data mining and natural language processing research areas. In the field of information retrieval for text mining, a variety of probabilistic topic models have been used t... Read More about Latent dirichlet markov allocation for sentiment analysis.

A state of the art survey on semantic web mining
Journal Article
Quboa, Q., & Saraee, M. A state of the art survey on semantic web mining. Intelligent Information Management, 05(01), 10-17. https://doi.org/10.4236/iim.2013.51002

The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many researchers to apply Data Mining t... Read More about A state of the art survey on semantic web mining.

A novel method in scam detection and prevention using data mining approaches
Presentation / Conference
Mokhtari, M., Saraee, M., & Haghshenas, A. A novel method in scam detection and prevention using data mining approaches. Presented at IDMC2008, Amir Kabir University, Tehran Iran

‘Scam’ is a fraudulence message by criminal intent sent to internet user mailboxes. Many approaches have been proposed to filter out unsolicited messages known as ‘spam’ from legitimate messages known as ‘ham’. However up to this date no suitable app... Read More about A novel method in scam detection and prevention using data mining approaches.

Mining GPS logs to augment location models
Presentation / Conference
Saraee, M., & Yamaner, S. Mining GPS logs to augment location models. Presented at The Sixth International Conference on Data Mining, Text Mining and their Business Applications May 25 – 27, 2005, Skiathos, Greece., 2005, Skiathos, Greece

The availability of mobile computing and satellite technologies make it possible to develop applications that are aware of user location.However, as the amount of collected data grows quickly, coming up with techniques that ease interpretation of suc... Read More about Mining GPS logs to augment location models.

Improving genetic algorithm with the help of novel twin removal method
Presentation / Conference
Imani, M., Pakizeh, E., & Saraee, M. Improving genetic algorithm with the help of novel twin removal method. Presented at 10th IASTED International Conference on Artificial Intelligence and Applications, held February 15-17, 2010 in Innsbruck, Austria., Innsbruck, Austria

Evolutionary Algorithms is one of the fastest growing areas of computer science. The simple Genetic Algorithm is fairly representative of other EAs. As they all use the same steps, significant researches in this area focus on Genetic Algorithm (GA).... Read More about Improving genetic algorithm with the help of novel twin removal method.

Iris disease classifying using neuro-fuzzy medical diagnosis machine
Book Chapter
Moein, S., Saraee, M., & Moein, M. Iris disease classifying using neuro-fuzzy medical diagnosis machine. In The Sixth International Symposium on Neural Networks (ISNN 2009) (359-368). Springer Berlin / Heidelberg,. https://doi.org/10.1007/978-3-642-01216-7_38

Disease diagnosis is an essential task in the medical world. The use of computers in the practice of medicine is becoming more and more crucial. In this paper, we propose an intelligent system to help us diagnose the Iris disease. This system is base... Read More about Iris disease classifying using neuro-fuzzy medical diagnosis machine.

Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques
Thesis
Shaukat, S. (in press). Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques. (Dissertation). University of Salford

Application of machine learning in the field of malware analysis is not a new concept, there have been lots of researches done on the classification of malware in android and windows environments. However, when it comes to malware analysis in the int... Read More about Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques.

Classifying advanced malware into families based on instruction link analysis
Thesis
Tabatabaei, S. (in press). Classifying advanced malware into families based on instruction link analysis. (Dissertation). University of Salford

With the ever-increasing growth of network resources, a great number of organizations are extremely dependent on the internet for operational activities as such, exposing their sensitive and confidential information to intrusion or invasion by sabote... Read More about Classifying advanced malware into families based on instruction link analysis.