Multiagent systems for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. This raises th...
Gabriella Castelli, Marco Mamei, Franco Zambonelli
In e-commerce applications, no systematic research has been provided to evaluate if the use of a detailed and rich contextual representation improves the user modeling predictive p...
Cosimo Palmisano, Alexander Tuzhilin, Michele Gorg...
The ability to model cognitive agents depends crucially on being able to encode and infer with contextual information at many levels (such as situational, psychological, social, or...
Srini Narayanan, Katie Sievers, Steven J. Maiorano
Abstract. Because the notion of context is multi-disciplinary [17], it encompasses lots of issues in Information Retrieval. In this paper, we define the context as the information ...
Argumentation allows agents to exchange additional information to argue about their beliefs and other mental attitudes during the negotiation process. Utterances and subsequent obs...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Cont...
Joel Pinto, B. Yegnanarayana, Hynek Hermansky, Mat...
Search and recommendation systems must include contextual information to effectively model users’ interests. In this paper, we present a systematic study of the effectiveness of...
Context-aware systems in a smart space environment must be aware of the surrounding contexts and adapt to changing contexts in highly dynamic environments. Data managements of con...
Vision-based road detection is important in different areas of
computer vision such as autonomous driving, car collision warning
and pedestrian crossing detection. However, curre...