Outputs (50)

SSAM : towards supervised sentiment and aspect modeling on different levels of labeling (2017)
Journal Article
Zahedi, E., & Saraee, M. (2018). SSAM : towards supervised sentiment and aspect modeling on different levels of labeling. Soft Computing, 22(23), 7989-8000. https://doi.org/10.1007/s00500-017-2746-9

Abstract In recent years people want to express their opinion on every online service or product, and there are now a huge number of opinions on the social media, online stores and blogs. However, most of the opinions are presented in plain text and... Read More about SSAM : towards supervised sentiment and aspect modeling on different levels of labeling.

Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine (2016)
Journal Article
Rashno, A., Nazari, B., Sadri, S., & Saraee, M. (2017). Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine. Neurocomputing, 226, 66-79. https://doi.org/10.1016/j.neucom.2016.11.030

one of the most important tasks of Mars rover, a robot which explores the Mars surface, is the process of automatic segmentation of images taken by front-line Panoramic Camera (Pancam). This procedure is highly significant since the transformation co... Read More about Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine.

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.

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.

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.