Color image segmentation has been extensively applied to a lot of applications such as pattern recognition, image compression and matching. In the literature, conventional k-means (MacQueen 1967) is one common algorithm used in pixel-based image segmentation. However, it needs to pre-assign an appropriate cluster number before performing clustering, which is an intractable problem from a practi...

Social media is said to have an impact on the public discourse and communication in the society. It is increasingly being used in the political context. Social networks sites such as Facebook, Twitter and other microblogging services provide an opportunity for public to give opinions about some issues of interest. Twitter is an ideal platform for users to spread not only information in general ...

Convolutional Neural Networks (Convnets) have achieved good results in a range of computer vision tasks the recent years. Though given a lot of attention, visualizing the learned representations to interpret Convnets, still remains a challenging task. The high dimensionality of internal representations and the high abstractions of deep layers are the main challenges when visualizing Convnet fun...

Anomaly detection is an important data analysis task. It is used to identify interesting and emerging patterns, trends and anomalies from data. Anomaly detection is an important tool to detect abnormalities in many different domains including financial fraud detection, computer network intrusion, human behavioural analysis, gene expression analysis and many more. Recently, in the financial sect...

A web of sensor nodes consisting of randomly distributed devices, used to monitor physical or environmental conditions is termed as a wireless sensor network. Sensor nodes discover, store, analyze, and transmit the data from the surroundings to the base station. Transmission of packets is the most crucial task for the networks among all the tasks of a sensor node. But transmission of data consu...

The intrusion detection systems focus on low-level attacks, and only generate isolated alerts. They can’t find logical relations among alerts. In addition, IDS’s accuracy is low; a lot of alerts are false alerts. So it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. To solve this problem different intrusion scenario detection met...

This paper aims to combine learning-to-rank methods with an existing clustering underlying the entities to be ranked. In recent years, learning-to-rank has attracted the interest of many researchers and a large number of algorithmic approaches and methods have been published. Existing learning-to-rank methods have as goal to automatically construct a ranking model from training data. Usually, a...

Business process is collection of standardized and structured tasks inducing value creation of a company. Nowadays, it is recognized as one of significant intangible business assets to achieve competitive advantages. We introduce a novel approach to business process analysis, which has more and more significance as process-aware information systems are spreading widely over a lot of companies. ...

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...