Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scans in order to provide a radiation therapist with a “second reader” opinion about the tumour location. For each PET slice, our system extracts a set of attributes, passes them to a trained Support Vector Machine (SVM),...

Recent literature reports the growing interests in data analysis using Formal Concept Analysis (FCA), in which data is represented in the form of object and attribute relations. FCA analyzes and then subsequently visualizes the data based on duality called Galois connection. Attribute exploration is a knowledge acquisition process in FCA, which interactively determines the implications holding ...

In this paper, we describe the Adaptive Place Advisor, a conversational recommendation system designed to help users decide on a destination. We view the selection of destinations as an interactive, conversational process, with the advisory system inquiring about desired item characteristics and the human responding. The user model, which contains preferences regarding items, attributes, values...

Automatic estimation of demographic attributes (e.g., age, gender, and race) from a face image is a topic of growing interest with many potential applications. Most prior work on this topic has used face images acquired under constrained and cooperative scenarios. This paper addresses the more challenging problem of automatic age, gender, and race estimation from real-life face images (face ima...

By introducing the concept of Cloud Computing, the architecture of e-Learning has been changed, So, we propose an autonomous learning support system that encourages learners’ interaction by “the Architecture of Participation”. We developed learning management system based on SNS. This system has two models that describe 1) learner’s acquired knowledge, and 2) learner’s participatory attributes....

In connection with the problem that the food processing information system is poor due to the absence of knowledge acquisition and a knowledge selfupdating function, a knowledge acquisition approach, based on a Support Vector Machine (SVM) is proposed. First, the approach establishes a set of predicted samples for the relationship between the food processing parameters and product quality; then...

In this paper, we describe the Adaptive Place Advisor, a user adaptive, conversational recommendation system designed to help users decide on a destination, specifically a restaurant. We view the selection of destinations as an interactive, conversational process, with the advisory system inquiring about desired item characteristics and the human responding. The user model, which contains prefe...

This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, t...

The acquisition of intra-subject data from multiple images is routinely performed to provide complementary information where a single image is not sufficient. However, these images are not always co-registered since they are acquired with different scanners, affected by subject's movements during scans, and consist of different image attributes, e.g. image resolution, field of view (FOV) and in...

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses...