The Web has become one of the largest and most readily accessible repositories of human knowledge. The traditional search engines index only surface Web whose pages are easily found. The focus has now been moved to invisible Web or hidden Web, which consists of a large warehouse of useful data such as images, sounds, presentations and many other types of media. To use such data, there is a need...

We propose a novel deep web crawling framework based on reinforcement learning. The crawler is regarded as an agent and deep web database as the environment. The agent perceives its current state and submits a selected action (query) to the environment according to Q-value. Based on the framework we develop an adaptive crawling method. Experimental results show that it outperforms the state of ...

Group formation in e-learning environments is a challenging area. In this paper we present a web-based group formation tool that supports the instructor to create both homogeneous and heterogeneous groups based on up to three criteria and the learner to negotiate the grouping. Moreover, the instructor is allowed to manually group students based on specific criteria. A discriminative feature of ...

We investigated various learning antecedents that have been the research subjects of Learning Analytics (LA) studies and explored the content and quantity of the LA literature with respect to each antecedent through text mining the LAK dataset. Our goal was to simultaneously reveal to what extent do LA researchers address learning antecedents and how they incorporated these in the implementatio...

The growth in the application of information technology to learning/training underscores the need to understand the impact of these technologies. This paper reports the results of a multi-period quasiexperiment focusing on two e-learning methods: contemporary web-based and video-based training methods. Drawing on the two foundational disciplines of Information Systems and Education, this study ...

We give an overview of recent exciting achievements of deep reinforcement learning (RL). We start with background of deep learning and reinforcement learning, as well as introduction of testbeds. Next we discuss Deep Q-Network (DQN) and its extensions, asynchronous methods, policy optimization, reward, and planning. After that, we talk about attention and memory, unsupervised learning, and lear...

Unpredicted loading caused by blast or impact may lead to severe damage in structures. Such damage may affect the whole structural performance. Connections are the key contributor to the integrity and energy dissipation capacity of the structural steel systems and play the most important role in mitigating such consequences. In the view of the importance of connections, finite element analysis ...

This paper deals with the problem of constructing an intelligent Focused Crawler, i.e. a system that is able to retrieve documents of a specific topic from the Web. The crawler must contain a component which assigns visiting priorities to the links, by estimating the probability of leading to a relevant page in the future. Reinforcement Learning was chosen as a method that fits this task nicely...