Social and Semantic Contexts in Tourist Mobile Applications

The ongoing growth of the World Wide Web along with the increase possibility of access information through a variety of devices in mobility, has defi nitely changed the way users acquire, create, and personalize information, pushing innovative strategies for annotating and organizing it. In this scenario, Social Annotation Systems have quickly gained a huge popularity, introducing millions of metadata on di fferent Web resources following a bottom-up approach, generating free and democratic mechanisms of classi cation, namely folksonomies. Moving away from hierarchical classi cation schemas, folksonomies represent also a meaningful mean for identifying similarities among users, resources and tags. At any rate, they suff er from several limitations, such as the lack of specialized tools devoted to manage, modify, customize and visualize them as well as the lack of an explicit semantic, making di fficult for users to bene fit from them eff ectively. Despite appealing promises of Semantic Web technologies, which were intended to explicitly formalize the knowledge within a particular domain in a top-down manner, in order to perform intelligent integration and reasoning on it, they are still far from reach their objectives, due to di fficulties in knowledge acquisition and annotation bottleneck. The main contribution of this dissertation consists in modeling a novel conceptual framework that exploits both social and semantic contextual dimensions, focusing on the domain of tourism and cultural heritage. The primary aim of our assessment is to evaluate the overall user satisfaction and the perceived quality in use thanks to two concrete case studies. Firstly, we concentrate our attention on contextual information and navigation, and on authoring tool; secondly, we provide a semantic mapping of tags of the system folksonomy, contrasted and compared to the expert users' classi cation, allowing a bridge between social and semantic knowledge according to its constantly mutual growth. The performed user evaluations analyses results are promising, reporting a high level of agreement on the perceived quality in use of both the applications and of the speci c analyzed features, demonstrating that a social-semantic contextual model improves the general users' satisfactio

Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study

Recommender systems engage user profiles and appropriate filtering techniques to assist users in finding more relevant information over the large volume of information. User profiles play an important role in the success of recommendation process since they model and represent the actual user needs. However, a comprehensive literature review of recommender systems has demonstrated no concrete study on the role and impact of knowledge in user profiling and filtering approache. In this paper, we review the most prominent recommender systems in the literature and examine the impression of knowledge extracted from different sources. We then come up with this finding that semantic information from the user context has substantial impact on the performance of knowledge based recommender systems. Finally, some new clues for improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.3, August 201

Global Diffusion of the Internet XV: Web 2.0 Technologies, Principles, and Applications: A Conceptual Framework from Technology Push and Demand Pull Perspective

Web 2.0, the current Internet evolution, can be described by several key features of an expanded Web that is more interactive; allows easy social interactions through participation and collaboration from a variety of human sectors; responds more immediately to users\u27 queries and needs; is easier to search; and provides a faster, smoother, realistic and engaging user search capability, often with automatic updates to users. The purpose of this study is three-fold. First, the primary goal is to propose a conceptual Web 2.0 framework that provides better understanding of the Web 2.0 concept by classifying current key components in a holistic manner. Second, using several selective key components from the conceptual framework, this study conducts case analyses of Web 2.0 applications to discuss how they have adopted the selective key features (i.e., participation, collaboration, rich user experience, social networking, semantics, and interactivity responsiveness) of the conceptual Web 2.0 framework. Finally, the study provides insightful discussion of some challenges and opportunities provided by Web 2.0 to education, business, and social life

Extracting Usage Patterns and the Analysis of Tag Connection Dynamics within Collaborative Tagging Systems

Collaborative tagging has become a very popular way of annotation, thanks to the fact that any entity may be labeled by any individual based on his own reason. In this paper we present the results of the case study carried out on the basis of data gathered at different time intervals from the social tagging system developed and implemented on Întelepciune.ro. Analyzing collective data referring to the way in which community members associate different tags, we have observed that between tags, links are formed which become increasingly stable with the passing of time. Following the application of methodology specific to network analysis, we have managed to extract information referring to tag popularity, their influence within the network and the degree to which a tag depends upon another. As such, we have succeeded in determining different semantic structures within the collective tagging system and see their evolution at different stages in time. Furthermore, we have pictured the way in which tag rec-ommendations can be executed and that they can be integrated within recommendation sys-tems. Thus, we will be able to identify experts and trustworthy content based on different cat-egories of interest