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In this paper we present an approach to add self-adaptive features to software systems not initially designed to be self-adaptive. Rapid changes in users needs, available resources, and types of system faults are everyday concerns in operating complex systems. The ability to face these issues in a (semi-)automatic fashion is a welcome feature. MAPE-K (Monitor, Analyze, Plan, Execute — Knowledge),...
Intelligent Tutoring Systems (ITS) are software systems for human learning and training. Promising works integrate ITS and game environments in order to use both the pedagogical soundness of traditional ITS and the engagement power of games. Such integration could be more effective embedding these systems into the Internet of Things. The main result of this work is the definition of an ontology-based...
The fundamental objective of an information search system based on interest center and the user profile is to return, from a collection of documents, the elements that are relevant to specific user needs. The selection of only documents interesting a user is done on the basis of interest center, calculated from the information about the user named user profile. The information retrieval systems converge...
the idea of Service-Oriented Computing (SOC) is to understand users' requirements for Service-Based Applications (SBAs). We propose an adaptation-centric approach which allows: (i) modeling users' requirements for Service-Oriented System with the MAP formalism using an Intentional Service Model (ISM); (ii) ontology and the aspect according to the contextual changes in order to inject it in the process...
The emergence of pervasive computing and user mobility leads to the need for dynamic adaptation of user interaction on the documents which generally are multimedia oriented. The exchange of multimedia documents has a special place. In this paper we propose an approach for modeling context in pervasive computing environments for multimedia documents adaptation. Many researchers work in the area of...
The main goal of many researches focuses on improving subscriber experience by proposing a variety of services and features to better fit his needs and expectations. In order to improve the response to this subscriber expectation and considering the huge amount of information available in the network combined with performance expectation, we combine services' descriptions with subscriber requests...
Human activity recognition, especially exceptional activity recognition has been regarded as an important aspect in intelligent service robotics. Several challenges in activity recognition — unexpected and untypical exceptional behaviors, a small but growing number of training examples — make it hard to solve this problem. Despite the variety of human behaviors, there are some normal patterns, especially...
People use reminders to recall tasks to-do. But sophisticated enough tools are unavailable. Context-Awareness in mobile computing is more engaging area in gathering information about the user's current situation and would be ideal to integrate with the reminders to generate context-aware reminder where rich context is used to identify when a reminder should be presented to its recipient. Here we have...
How users experience a web-site's usability is mostly subjective. There is an ISO standard adressing usability requirements (EN ISO 9241-11). However, its propositions are kept rather general and focus strongly on individual usage situations. Nevertheless, there are usability critera for websites that can be considered negative, e.g. bad contrast, a high readability index, or discrepancies between...
This paper is intended to provide a solution for developing context-aware smart applications preserving the users' privacy in the Internet of Things (IoT). In this sense, we present a framework called Semantic Web-based Context Management (SeCoMan) aimed at offering a set of predefined queries to provide applications with information about indoor location of users and objects, as well as context-aware...
To facilitate the sharing and combination of knowledge by Global Software Engineering (GSE) researchers and practitioners, the need for a common terminology and knowledge classification scheme has been identified, and as a consequence, a taxonomy and an extension were proposed. In addition, one systematic literature review and a survey on respectively the state of the art and practice of effort estimation...
Lexical inference problem is a significant component of some recent core AI and NLP research problems like machine reading and textual entailment. In this paper, we propose method utilizing the Probabilistic Soft Logic (PSL) model for Chinese lexical inference. The proposed PSL model not only can integrate two complementary traditional methods, i.e., the lexical-knowledge-based method and the distributional...
In this short paper, we describe a conceptual approach in which Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are employed towards knowledge discovery in online drug transactions. The transactions are acquired by performing Named-Entity Recognition (NER) on documents crawled from online public sources such as Twitter and Instagram, and are structured based on a CG ontology created to model...
User annotation of images has become a popular solution for image classification and retrieval. This paper reports a machine learning approach in taxonomy induction that applies image annotations involved in different levels of meaning making from the participants. Results of the study indicate the effectiveness of the method. The study suggests that the discussed machine learning procedures can be...
As the notion of context-awareness evolves in different paradigms, the development of context-aware systems involves several processes. These processes include, inter alia, context modeling and reasoning as well as adaptation. In [1], we presented an approach that consists of context modeling and reasoning hand in hand based on relational concept analysis and descriptive logic, respectively. An essential...
In this work, given the context of the driver, of the vehicle and of the environment, our objective is to correctly recognize the traffic situation and provide the driver with the corresponding assistance by providing notification or alert about the situation or the infraction that was committed, or acting directly on the vehicle. To do so, we need to consider the signal processing related to these...
The paper explores the issues and challenges for Trust and Reputation arising from Cloud Computing, Cyber Physical Systems and Social Media. It develops the Semantics of Trust and Reputation Systems and the use of Big Data Predictive Analytics for Trust and Reputation Prediction.
Ontology mapping is a common way to solve heterogeneous problem in ontologies and achieve the goal of ontology integration. In a distributed environment, it is necessary to find the mappings between ontologies before they are merged. There is a number of mapping approaches based on concept similarities which are widely used but with large amount of calculations exist. Aiming at mapping between ontologies...
In recent years homeland security is becoming increasingly sensitive to threats posed by the tactics of subversive groups or individuals with malicious intent. Networked groups and organizations leverage various means of communication, ranging from simple phone calls to more sophisticated forms of collaborations. Such data provide a rich collection of evidence from which to infer relationships of...
Over the course of Dave Hall's career, he highlighted various concerns associated with the implementation of data fusion methods. Many of the issues included the role of uncertainty in data fusion, practical implementation of sensor fusion systems, and incorporating new technology into information fusion designs. These thoughts were communicated through technical books and Handbook collections of...
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