Fish-net algorithm is a novel field learning algorithm which derives classification rules by looking at the range of values of each attribute instead of the individual point values. In this paper, we present a Feature Selection Fish-net learning algorithm to solve the Dual Imbalance problem on text classification. Dual imbalance includes the instance imbalance and feature imbalance. The instanc...

This work proposes a novel system for Violent Scenes Detection, which is based on the combination of visual and audio features with machine learning at segment-level. Multiple Kernel Learning is applied so that multimodality of videos can be maximized. In particular, Mid-level Violence Clustering is proposed in order for mid-level concepts to be implicitly learned, without using manually tagged...

When analysing social media conversations, in search of the public opinion about an unfolding event that is being discussed in real-time (e.g., presidential debates, major speeches, etc.), it is important to distinguish between two groups of participants: opinion-makers and opinion-holders. To address this problem, we propose a supervised machinelearning approach, which uses inexpensively acqui...

The formation of new synapses has been suggested to underlie learning and memory. However, previous work from this laboratory has demonstrated that hippocampus-dependent associative learning does not induce a net gain in the total number of hippocampal synapses and, hence, a net synaptogenesis. The aim of the present work was to determine whether associative learning involves a specific synapto...

This paper presents results from a longitudinal study on first-year students’ expectations and actual reported use of information and communication technologies (ICT) at university. The study was interested in firstly, knowing if students from the Net Generation (≤ 25 years) would appropriate more ICT time for both social life and leisure, and study purposes than older students, as this forms t...

distinguishing productive zones of a drilled oil well plays a very important role for petroleum engineers to decide where to perforate to produce oil. conventionally, net pay zones are determined by applying a set of cut-offs on perophysical logs. as a result, the conventional method finds productive intervals crisply. in this investigation, a net index value is proposed, then; diffusivity equa...

Many databases store data in relational format, with different types of entities and information about links between the entities. The field of statistical-relational learning (SRL) has developed a number of new statistical models for such data. In this paper we focus on learning class-level or first-order dependencies, which model the general database statistics over attributes of linked objec...

This paper discusses the issue of learner participation in a net-based higher education course. With the starting point in recent educational policies formulated by the European Union and the results of an evaluation report from the Swedish Net University, I raise the question of which pedagogical aspects need to be considered in order to support active learner participation in these types of l...

Multiple kernel learning (MKL), structured sparsity, and multi-task learning have recently received considerable attention. In this paper, we show how different MKL algorithms can be understood as applications of either regularization on the kernel weights or block-norm-based regularization, which is more common in structured sparsity and multi-task learning. We show that these two regularizati...