Text Assisted Insight Ranking Using Context-Aware Memory Network

Context-Aware Semantic Association Ranking

Discovering complex and meaningful relationships, which we call Semantic Associations, is an important challenge. Just as ranking of documents is a critical component of today’s search engines, ranking of relationships will be essential in tomorrow’s semantic search engines that would support discovery and mining of the Semantic Web. Building upon our recent work on specifying types of Semantic...

Context-aware handover using active network technology

Context-aware computing can play a major role to improve the services of mobile networking systems. In this paper, we focus on optimizing handover decisions in heterogeneous environments, where the user has a choice among different mobile networks and access points. In our approach, the decision is not only based on the signal quality, but also on the knowledge about the context of mobile devic...

Context-Aware Ranking with Factorization Models

Salient Object Detection using a Context-Aware Refinement Network

Recently there has been remarkable success in pushing the state of the art in salient object detection. Most of the improvements are driven by employing end-to-end deeper feed-forward networks. However, in many cases precisely detecting salient regions requires representation of fine details. Combining high-level and low-level features using skip connections is a strategy that has been proposed...

Optimal Memory - aware Sensor Network

Gossiping is an important problem in Radio Networks that has been well studied, leading to many important results. However, due to the strong resource limitations of sensor nodes, previous solutions are frequently not feasible in Sensor Networks. In this paper, we study the gossiping problem in the restrictive context of Sensor Networks. By exploiting the geometry of sensor node distributions, ...