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All Outputs (18)

Robust and cost-effective approach for discovering action rules (2011)
Journal Article
Kalanat, N., Shamsinejad, P., & Saraee, M. (2011). Robust and cost-effective approach for discovering action rules. International journal of machine learning and computing (Online), 1(4), 325-331. https://doi.org/10.7763/IJMLC.2011.V1.48

The main goal of Knowledge Discovery in
Databases is to find interesting and usable patterns, meaningful
in their domain. Actionable Knowledge Discovery came to
existence as a direct respond to the need of finding more usable
patterns called acti... Read More about Robust and cost-effective approach for discovering action rules.

Hybrid rule threshold adjustment system for intrusion detection (2011)
Presentation / Conference
Moghimi, M., & Saraee, M. (2011, September). Hybrid rule threshold adjustment system for intrusion detection. Presented at The 8th International ISC Conference on Information Security and Cryptology (ISCISC 2011), September 14-15, 2011 - Ferdowsi University of Mashhad,, Mashhad, Iran

Generally, multiple IDSs generates huge volume of alerts every minute and to manage these alerts, rule-based alert management systems are very important. It is critical to keep the rules inside these systems updated, based on the ever changing networ... Read More about Hybrid rule threshold adjustment system for intrusion detection.

Modeling batch annealing process using data mining techniques for cold rolled steel sheets (2011)
Presentation / Conference
Saraee, M., Moghimi, M., & Bagheri, A. (2011, August). Modeling batch annealing process using data mining techniques for cold rolled steel sheets. Presented at The 17th Annual ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego

The annealing process is one of the important operations in production of cold rolled steel sheets, which significantly influences the final product quality of cold rolling mills. In this process, cold rolled coils are heated slowly to a desired temp... Read More about Modeling batch annealing process using data mining techniques for cold rolled steel sheets.

Examination of the online reputation systems problems and provide solution (2011)
Presentation / Conference
Ehghaghi Kakoli, Z., Nematbakhsh, M., & Saraee, M. (2011, August). Examination of the online reputation systems problems and provide solution. Presented at 13th IEEE Joint International Computer Science and Information Technology Conference (JICSIT 2011), Chongqing, China

Electronic commerce communities are considered to
be communities that provide opportunities for the sellers on
the one hand and include threats for the purchasers on the
other hand. One of the ways to reduce such threats in these
open communities... Read More about Examination of the online reputation systems problems and provide solution.

A new unsupervised feature selection method for text clustering based on genetic algorithms (2011)
Journal Article
Shamsinejadbabki, P., & Saraee, M. (2012). A new unsupervised feature selection method for text clustering based on genetic algorithms. Journal of Intelligent Information Systems, 38(3), 669-684. https://doi.org/10.1007/s10844-011-0172-5

Nowadays a vast amount of textual information is collected and stored in various databases around the world, including the Internet as the largest database of all. This rapidly increasing growth of published text means that even the most avid reader... Read More about A new unsupervised feature selection method for text clustering based on genetic algorithms.

Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model (2011)
Presentation / Conference
Shayegh, F., Amirfattahi, R., Sadri, S., Ansari-Asl, K., & Saraee, M. (2011, July). Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model. Presented at Intelligent Systems and Control / 742 : Computational Bioscience (ISC 2011), Cambridge, UK

There are various methods to measure the value of synchronization of signals. These methods usually do not consider the sources of the signals. Therefore, these methods usually underestimate the coupling phenomena of the sources of the system that ge... Read More about Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model.

Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model (2011)
Presentation / Conference
Shayegh, F., Amirfattahi, R., Sadri, S., Ansari-Asl, K., & Saraee, M. (2011, July). Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model. Presented at Intelligent Systems and Control / 742: Computational Bioscience (ISC 2011), Cambridge, United Kingdom

There are various methods to measure the value of synchronization of signals. These methods usually do not consider the sources of the signals. Therefore, these methods usually underestimate the coupling phenomena of the sources of the system that ge... Read More about Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model.

A new framework for online rule threshold adjustment in intrusion detection (2011)
Presentation / Conference
Moghimi, M., & Saraee, M. (2011, June). A new framework for online rule threshold adjustment in intrusion detection. Presented at 2011 CSI International Symposium on Computer Science and Software Engineering (CSSE), Tehran

Generally, rule-based systems work to make sense of a large volume of alerts generated by the intrusion detection systems (IDSs) every minute. Hence, it is very significant to verify that these systems are error-free and that the rules are suitable f... Read More about A new framework for online rule threshold adjustment in intrusion detection.

Toward a functional ontology of reputation for e-commerce (2011)
Presentation / Conference
Ehghaghi Kakoli, Z., Nematbakhsh, M., & Saraee, M. (2011, March). Toward a functional ontology of reputation for e-commerce. Presented at e-Society 2011, 9th International Conference IADIS, Avila, Spain

In recent years, the expansion of the internet has influenced all aspect of our lives. Trust is an important factor making business transactions possible. In a conventional setting this trust is based on all involved parties knowing each other. Howev... Read More about Toward a functional ontology of reputation for e-commerce.

A survey on utilization of data mining approaches for dermatological (skin) diseases prediction (2011)
Journal Article
Barati, E., Saraee, M., Mohammadi, A., Adibi, N., & Ahmadzadeh, M. (2011). A survey on utilization of data mining approaches for dermatological (skin) diseases prediction

Due to recent technology advances, large volumes of medical data is obtained. These data contain valuable information. Therefore data mining techniques can be used to extract useful patterns. This paper is intended to introduce data mining and its va... Read More about A survey on utilization of data mining approaches for dermatological (skin) diseases prediction.

A hybrid recommender system for dynamic web users (2011)
Journal Article
Nadi, S., Saraee, M., & Bagheri, A. (2011). A hybrid recommender system for dynamic web users. International Journal of Multimedia and Image Processing, 1(1), 3-8

Nowadays, providing tools that eases the interaction of users with websites is a big challenge in e-commerce. Recommender systems are useful tools which adapts the environment of websites compatible with users needs. In this paper, applying a hybrid... Read More about A hybrid recommender system for dynamic web users.

Identification of disease-causing genes using microarray data mining and gene ontology (2011)
Journal Article
Mohammadi, A., Saraee, M., & Salehi, M. (2011). Identification of disease-causing genes using microarray data mining and gene ontology. BMC Medical Genomics, 4(12), 1-9. https://doi.org/10.1186/1755-8794-4-12

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small... Read More about Identification of disease-causing genes using microarray data mining and gene ontology.

Disordered metabolic evaluation in renal stone recurrence : a data mining approach (2011)
Journal Article
Saraee, M., Givchi, A., Taghi Adl, S., & Eshraghi, A. (2011). Disordered metabolic evaluation in renal stone recurrence : a data mining approach. Journal of Applied Computer Science & Mathematics (Suceava. Online), 5(11), 64-68

Nephrolithiasis is a disease with a high and even rising incidence. It has a high morbidity, generates high costs and has a high recurrence rate. Metabolic evaluation in renal stone formers allows the identification and quantification of risk factors... Read More about Disordered metabolic evaluation in renal stone recurrence : a data mining approach.

A Bayesian network approach for causal action rule mining (2011)
Journal Article
Shamsinejad, P., & Saraee, M. (2011). A Bayesian network approach for causal action rule mining. International journal of machine learning and computing (Online), 1(5), 528-533

Actionable Knowledge Discovery has attracted much interest lately. It is almost a new paradigm shift toward mining more usable and more applicable knowledge in each specific domain. Action Rule is a new tool in this research area that suggests some a... Read More about A Bayesian network approach for causal action rule mining.

FARS: Fuzzy Ant based Recommender System for Web Users (2011)
Journal Article
Nadi, S., Saraee, M., Bagheri, A., & Davarpanh Jazi, M. (2011). FARS: Fuzzy Ant based Recommender System for Web Users. International Journal of Computer Science Issues, 8(1), 203-209

Recommender systems are useful tools which provide an
adaptive web environment for web users. Nowadays, having a
user friendly website is a big challenge in e-commerce
technology. In this paper, applying the benefits of both
collaborative and... Read More about FARS: Fuzzy Ant based Recommender System for Web Users.

Application of Self Organizing Map (SOM) to model a machining process (2011)
Journal Article
Saraee, M., Moosavi, S., & Rezapour, S. (2011). Application of Self Organizing Map (SOM) to model a machining process. Journal of Manufacturing Technology Management, 22(6), 818-830. https://doi.org/10.1108/17410381111149666

Purpose: This paper aims to present a practical application of Self Organizing Map (SOM) and decision tree algorithms to model a multi-response machining process and to provide a set of control rules for this process.
Design/methodology/approach: S... Read More about Application of Self Organizing Map (SOM) to model a machining process.