5,011 research outputs found
An Approach for Sentiment Classification of Music
No full textIn recent years, the music recommendation systems and dynamic generation of playlists have become extremely promising research areas. Thanks to the widespread use of the Internet, users can store a consistent set of music data and use them in the everyday context thanks to portable music players. The problem of modern music recommendation systems is how to process this large amount of data and extract meaningful content descriptors. The aim of this paper is to compare different approaches to decode the content within the mood of a song and to propose a new set of features to be considered for classification
Context Awareness in Pervasive Information Management
No full textContext has been defined as the knowledge that can be used to characterize the situation of any entity that is relevant for the (pervasive) system under consideration: given a target application scenario, a context-aware system supports users and devices by providing selective access to the set of data and operations (e.g., interesting services and information, environmental data, close-by people, points of interest etc.) which is relevant in each specific context. More than that, the relative importance of a piece of information to the same user in different contexts or, reciprocally, to different users in the same context may vary enormously; thus the system can personalize information even further by ranking the provided data on the basis of (contextual) user preferences. This chapter presents an introduction to context-aware information management, first providing a literature review and then introducing the main steps needed to design a context-aware system. Context-related problems particularly relevant within pervasive data management are then discussed. We briefly analyze techniques to efficiently associate contexts with information chunks, the evolution issues which arise when the context representation changes over time, the discovery and application of contextual user preferences, and, last but certainly not least, how context awareness can be enforced in the middleware of a pervasive system
A Network Management System Based on Ontology and Slow Intelligence System
No full textThe last decade has witnessed an intense spread of computer networks that has been further accelerated with the introduction of wireless networks: this growth has increased significantly the problems of network management. Especially in small companies the management of such networks is often complex and faults have significant impacts on their businesses. A possible solution is the adoption of the Simple Network Management Network
administrators can manage network performance, find and solve network problems, and plan for network growth by the use of the SNMP. Over the past years much efforts has been given to make more effective the Simple Network Management Protocol and new approaches has been developed. In particular a promising approach involves the use of Ontology. The ontology based network management has recently evolved from a theoretical proposal to a more mature technology and this is the starting point of this paper where a novel approach to the network management based on the use of the Slow Intelligence System methodologies and Ontology based techniques is proposed. The Slow Intelligence System is a generalpurpose system characterized by being able to improve performance over time through a process involving various phases as enumeration, propagation, adaptation, elimination and concentration. Therefore, the proposed approach aims to develop a system able to acquire, according to the Simple Network Management Protocol, information from the various hosts
that are in the managed networks and apply actions in order to solve problems. To check the feasibility of this approach and its performance an experimental campaign in a real scenario has been designed and the first experimental results in a real scenario are showed
Ontology for E-Learning: A Bayesian Approach
No full textIn the last decade, the evolution of educational technologies has forced an extraordinary interest in new methods for delivering learning content to learners. Today, distance education represents an effective way for supporting and sometimes substituting the traditional formative processes, thanks to the technological improvements achieved in the field in recent years. However, the role of technology has often been overestimated. The amount of information students can obtain from the Internet is huge, and as a result, they can easily be confused. Teachers can also be disconcerted by this vast quantity of content and are often unable to suggest the correct content to their students. In the open scientific literature, it is widely recognized that an important factor for success in delivering learning content is related to the capability for customizing the learning process for the specific needs of a given learner. This task is still far from having been fully accomplished, and there is a real interest in investigating new approaches and tools to adapt the formative process to specific individual needs. In this scenario, the introduction of ontology formalism can improve the quality of the formative process, allowing the introduction of new and effective services. Ontologies can lead to important improvements in the definition of a course’s knowledge domain, in the generation of an adapted learning path, and in the assessment phase. This paper provides an initial discussion of the role of ontologies in the context of e-learning. The improvements related to the introduction of ontologies formalism in the e-learning field are discussed, and a novel algorithm for ontology building through the use of Bayesian networks is shown. Finally, the application of this algorithm in the assessment process and some experimental results are illustrated
Improving security in cloud by formal modeling of IaaS resources
No full textNowadays, it is a matter of fact that Cloud is a "must" for all complex services requiring great amount of resources. Big-Data Services are a striking example: they actually perform many kind of analysis (like analytics) on very big repositories. Many File Systems and middleware exist for efficient distribution and management of data and they usually use Cloud Resources. Anyway Several problems arose about Security of data: Virtualization is the base of Cloud resources and, even if we consider data storage as virtually separated elements, security issues exist if privilege escalation allows for gaining control on any data on physical hosts. In this paper we show how it is possible to cope Model Driven Engineering techniques to security analysis and monitoring of Cloud infrastructures. For reducing overhead, we provide a formal profile of hosts thermal behaviors. Depending on services input workloads, we detect and forecast malicious actions by comparisons with real thermal data
CHIS: A big data infrastructure to manage digital cultural items
No full textIn this paper, we describe CHIS (Cultural Heritage Information System), a big data infrastructure that can be used to query, browse, analyze and process digital contents related to cultural heritage from a set of heterogeneous and distributed repositories. CHIS is characterized by the following technical features: capability to gather information from distributed and heterogeneous data sources (e.g., Sensor Networks, Social Media Networks, Digital Libraries and Archives, Multimedia Collections, Web Data Services, etc.); advanced data management techniques and technologies; ability to provide useful and personalized data to users based on their preferences and context; advanced information retrieval facilities, data analytics and other utilities/services, according to the SOA paradigm. By means of a set of ad-hoc APIs, and value-added data processing and analytics services, our system can support several applications: mobile multimedia guides for cultural environments, web portals to promote the cultural heritage of a given organization, multimedia recommender and storytelling systems and so on. We discuss the main ideas that characterize the system, showing its use for several applications
Parametri caratteristici di un ambiente per E-Learning:un modello per la loro valutazione
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