A State of the Art on Social Network Analysis and its Applications on a Semantic Web

The increasingly popular web 2.0 sites provide the largest social network ever analyzed - users are now considered as plain web resources. Some researchers apply classical methods of social network analysis to such networks; others provide models to leverage the semantics of their representation. We present a state of the art of these two approaches and propose an architecture to merge and exploit the best features of each

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Challenges and potential of the Semantic Web for tourism

The paper explores tourism challenges and potential of the Semantic Web from a theoretical and industry perspective. It first examines tourism business networks and explores a main theme of network interoperability - data standards- followed by technology deficiencies of Web 1.0 and 2.0 and Semantic Web solutions. It then explicates Semantic opportunities and challenges for tourism, including an industry perspective through a qualitative approach. Industry leaders considered that the new Web era was imminent and heralded benefits for supply and demand side interoperability, although management and technical challenges could impede progress and delay realisation