All Outputs (45)

ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences (2014)
Journal Article
Bagheri, A., Saraee, M., & de Jong, F. (2014). ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences. Journal of Information Science, 40(5), 621-636. https://doi.org/10.1177/0165551514538744

Probabilistic topic models are statistical methods whose aim is to discover the latent structure in a large collection of documents. The intuition behind topic models is that, by generating documents by latent topics, the word distribution for each t... Read More about ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences.

Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews (2013)
Journal Article
Bagheri, A., Saraee, M., & de Jong, F. (2013). Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews. Knowledge-Based Systems, 52(2013), 201-213. https://doi.org/10.1016/j.knosys.2013.08.011

With the rapid growth of user-generated content on the internet, automatic sentiment analysis of online customer reviews has become a hot research topic recently, but due to variety and wide range of products and services being reviewed on the intern... Read More about Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews.

Causality-based cost-effective action mining (2013)
Journal Article
Shamsinejadbabki, P., Saraee, M., & Blockeel, H. (2013). Causality-based cost-effective action mining. Intelligent Data Analysis, 17(6), 1075-1091. https://doi.org/10.3233/IDA-130621

In many business contexts, the ultimate goal of knowledge discovery is not the knowledge itself, but putting it to use. Models or patterns found by data mining methods often require further post-processing to bring this about. For instance, in churn... Read More about Causality-based cost-effective action mining.

Protein contact map prediction using committee machine approach (2013)
Journal Article
Habibi, N., Saraee, M., & Korbekandi, H. (2013). Protein contact map prediction using committee machine approach. International Journal of Data Mining and Bioinformatics, 7(4), 397-415. https://doi.org/10.1504/IJDMB.2013.054226

A protein contact map is a simplified representation of the protein's spatial structure. In recent years, contact map prediction has received a great deal of attention in Bioinformatics. Committee Machine is a machine learning method which shares t... Read More about Protein contact map prediction using committee machine approach.

An unsupervised aspect detection model for sentiment analysis of reviews (2013)
Journal Article
Bagheri, A., Saraee, M., & Jong, F. (2013). An unsupervised aspect detection model for sentiment analysis of reviews. Lecture notes in computer science, 7934, 140-151. https://doi.org/10.1007/978-3-642-38824-8_12

With the rapid growth of user-generated content on the internet, sentiment analysis of online reviews has become a hot research topic recently, but due to variety and wide range of products and services, the supervised and domain-specific models are... Read More about An unsupervised aspect detection model for sentiment analysis of reviews.

Feature selection methods in Persian sentiment analysis (2013)
Journal Article
Saraee, M., & Bagheri, A. (2013). Feature selection methods in Persian sentiment analysis. Lecture notes in computer science, 7934, 303-308. https://doi.org/10.1007/978-3-642-38824-8_29

With the enormous growth of digital content in internet, various types of online reviews such as product and movie reviews present a wealth of subjective information that can be very helpful for potential users. Sentiment analysis aims to use automat... Read More about Feature selection methods in Persian sentiment analysis.

A new method for compressing massive RFID data to achieve efficient mining (2012)
Journal Article
Hafezi, L., Saraee, M., & Montazeri, M. (2012). A new method for compressing massive RFID data to achieve efficient mining. International journal of computer theory and engineering (Print), 4(5), 694-696. https://doi.org/10.7763/IJCTE.2012.V4.559

Radio Frequency Identification (RFID) technology has been used for many purposes and has had effective results. This technology eases and accelerates many applications, but it has proposed a challenge, and that is the production of such a volume of d... Read More about A new method for compressing massive RFID data to achieve efficient mining.

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.

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.

A survey on utilization of data mining approaches for dermatological (skin) diseases prediction (2011)
Journal Article
Barati, E., Saraee, M., Mohammadi, A., & Adibi, N. (2011). A survey on utilization of data mining approaches for dermatological (skin) diseases prediction. #Journal not on list,

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.

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.

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.

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.

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.

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.

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.

Social networking approach for building trust in e-commerce (2010)
Journal Article
Saraee, M., Shahghlian, A., & Mazrooei, P. (2010). Social networking approach for building trust in e-commerce. Journal of communication and computer, 7(6), 49-53

E-commerce has played a major role for most business functions in today's competitive enterprises. In general, E-commerce has enabled online transactions while the most important factor in a transaction between two individuals is the degree of trust... Read More about Social networking approach for building trust in e-commerce.

Finding shortest path with learning algorithms (2008)
Journal Article
Bagheri, A., Akbarzadeh, M., & Saraee, M. (2008). Finding shortest path with learning algorithms. International Journal of Artificial Intelligence, 1(A08),

This paper presents an approach to the shortest path routing problem that uses one of the most popular learning algorithms. The Genetic Algorithm (GA) is one of the most powerful and successful method in stochastic search and optimization techniques... Read More about Finding shortest path with learning algorithms.

Genome-wide efficient attribute selection for purely epistatic models via Shannon entropy (2008)
Journal Article
Manzourolajdad, A., Saraee, M., Mirlohi, A., & Javan, A. (2008). Genome-wide efficient attribute selection for purely epistatic models via Shannon entropy. International Journal of Business Intelligence and Data Mining, 3(4), 390. https://doi.org/10.1504/IJBIDM.2008.022736

Epistasis plays an important role in the genetic architecture of common human diseases. Most complex diseases are believed to have multiple contributing loci that often have subtle patterns which make them fairly difficult to find in large data sets.... Read More about Genome-wide efficient attribute selection for purely epistatic models via Shannon entropy.