All Outputs (161)

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments (2016)
Journal Article
Al-Nawashi, M., Al-Hazaimeh, O., & Saraee, M. (2016). A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments. Neural Computing and Applications, 27(4), https://doi.org/10.1007/s00521-016-2363-z

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system thatcan perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic re... Read More about A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings (2016)
Book
(2016). E. Metais, F. Meziane, M. Saraee, V. Sugumaran, S. Vadera, E. Métais, …S. Vadera (Eds.), Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings. Springer. https://doi.org/10.1007/978-3-319-41754-7

This volume of the lecture notes in computer science (LNCS) contains the papers presented at the 21st International Conference on application of Natural Language to Information Systems, held at MediacityUK, University of Salford on the 22-24 June 201... Read More about Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings.

Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification (2016)
Journal Article
Sartakhti, J., Afrabandpey, H., & Saraee, M. (2017). Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification. Soft Computing, 21(15), 4361-4373. https://doi.org/10.1007/s00500-016-2067-4

Least squares twin support vector machine (LSTSVM) is a relatively new version of support vector machine (SVM) based on non-parallel twin hyperplanes. Although, LSTSVM is an extremely efficient and fast algorithm for binary classification, its p... Read More about Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification.

Time-sensitive influence maximization in social networks (2015)
Journal Article
Mohammadi, A., Saraee, M., & Mirzaei, A. (2015). Time-sensitive influence maximization in social networks. Journal of Information Science, 41(6), 765-778. https://doi.org/10.1177/0165551515602808

One of the fundamental issues in social networks is the influence maximization problem, where the goal is to identify a small subset of individuals such that they can trigger the largest number of members in the network. In real-world social networks... Read More about Time-sensitive influence maximization in social networks.

Mars image segmentation with most relevant features among wavelet and color features (2015)
Presentation / Conference
Rashno, A., Saraee, M., & Sadri, S. (2015, April). Mars image segmentation with most relevant features among wavelet and color features. Presented at AI & Robotics (IRANOPEN), 2015

Mars rover is a robot which explores the Mars surface, is equipped to front-line Panoramic Camera (Pancam). Automatic processing and segmentation of images taken by Pancam is one of the most important and most significant tasks of Mars rover since th... Read More about Mars image segmentation with most relevant features among wavelet and color features.

PSA : a hybrid feature selection approach for Persian text classification (2015)
Journal Article
Bagheri, A., Saraee, M., & Nadi, S. (2015). PSA : a hybrid feature selection approach for Persian text classification. Journal of computing and security (Online), 1(4), 261-272

In recent decades, as enormous amount of data being accumulated, the number of text documents is increasing vastly. E-mails, web pages, texts, news and articles are only part of this grow. Thus the need for text mining techniques, including automatic... Read More about PSA : a hybrid feature selection approach for Persian text classification.

A novel feature selection method for text classification using association rules and clustering (2014)
Journal Article
Sheydaei, N., Saraee, M., & Shahgholian, A. (2015). A novel feature selection method for text classification using association rules and clustering. Journal of Information Science, 41(1), 3-15. https://doi.org/10.1177/0165551514550143

Readability and accuracy are two important features of a good classifier. For reasons such as acceptable accuracy, rapid training and high interpretability, associative classifiers have been recently used in many categorization tasks. These features... Read More about A novel feature selection method for text classification using association rules and clustering.

Persian sentiment analyzer : a framework based on a novel feature selection method (2014)
Journal Article
feature selection method. International Journal of Artificial Intelligence, 12(2), 115-129

In the recent decade, with the enormous growth of digital content in internet and databases, sentiment analysis has received more and more attention between information retrieval and natural language processing researchers. Sentiment analysis aims... Read More about Persian sentiment analyzer : a framework based on a novel feature selection method.

MRAR : mining multi-relation association rules (2014)
Journal Article
Ramezani, R., Saraee, M., & Nematbakhsh, M. (2014). MRAR : mining multi-relation association rules. Journal of computing and security (Online), 1(2), 133-158

In this paper, we introduce a new class of association rules (ARs) named “Multi-Relation Association Rules” which in contrast to primitive ARs (that are usually extracted from multi-relational databases), each rule item consists of one entity and... Read More about MRAR : mining multi-relation association rules.

A fuzzy method for discovering cost-effective actions from data (2014)
Journal Article
Kalanat, N., Shamsinejadbabaki, P., & Saraee, M. (2014). A fuzzy method for discovering cost-effective actions from data. Journal of Intelligent and Fuzzy Systems, 28(2), 757-765. https://doi.org/10.3233/IFS-141357

Data mining techniques are often confined to the delivery of frequent patterns and stop short of suggesting how to act on these patterns for business decision-making. They require human experts to post-process the discovered patterns manually. Theref... Read More about A fuzzy method for discovering cost-effective actions from data.

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.

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.

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.

Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings (2013)
Book
(2013). E. Métais, F. Meziane, M. Saraee, & S. Vadera (Eds.), Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings. Springer

This book constitutes the refereed proceedings of the 18th International Conference on Applications of Natural Language to Information Systems, held in Salford, UK, in June 2013. The 21 long papers, 15 short papers and 17 poster papers presented... Read More about Natural language processing and information systems : 18th international conference on applications of natural language to information systems, NLDB 2013, Salford, UK, June 2013; Proceedings.

Sentiment classification in Persian: Introducing a mutual information-based method for feature selection (2013)
Presentation / Conference
Bagheri, A., Saraee, M., & de Jong, F. (2013, May). Sentiment classification in Persian: Introducing a mutual information-based method for feature selection. Presented at 21st Iranian Conference on Electrical Engineering (ICEE), 2013, Mashhad, Iran

With the enormous growth of online reviews in Internet, sentiment analysis has received more and more attention in information retrieval and natural language processing community. Up to now there are very few researches conducted on sentiment analysi... Read More about Sentiment classification in Persian: Introducing a mutual information-based method for feature selection.

Finding association rules in linked data, a centralization approach (2013)
Presentation / Conference
Ramezani, R., Saraee, M., & Nematbakhsh, M. (2013, May). Finding association rules in linked data, a centralization approach. Presented at 21st Iranian Conference on Electrical Engineering (ICEE), 2013, Mashhad, Iran

Linked Data is used in the Web to create typed links between data from different sources. Connecting diffused data by using these links provides new data which could be employed in different applications. Association Rules Mining (ARM) is a data mini... Read More about Finding association rules in linked data, a centralization approach.

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 multi-armed bandit approach to cost-sensitive decision tree learning (2012)
Presentation / Conference
Lomax, S., Vadera, S., & Saraee, M. (2012, December). A multi-armed bandit approach to cost-sensitive decision tree learning. Presented at 2012 IEEE 12th International Conference on Data Mining Workshops, Brussels, Belgium

Several authors have studied the problem of inducing decision trees that aim to minimize costs of misclassification and take account of costs of tests. The approaches adopted vary from modifying the information theoretic attribute selection measure u... Read More about A multi-armed bandit approach to cost-sensitive decision tree learning.