Conditions
A brand-new, unused copy in perfect condition.
Conditions
A brand-new, unused copy in perfect condition.
Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web, combining the information obtained from the Web with other data sources and analyzing the results. Social network mining from the web plays an important role in this case study for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.
This book delineates a prominent research and application arena for the next years. As emphasized in the foreword, the strength of the book is to look at overlapping boundaries between social network and the Semantic Web. Peter Mika shows how Semantic Web and social network analysis can work together as part of the [new] social and Semantic Web. Mika present the history of the fields, basic concepts, and, based upon his own academic research (e.g., Flink, openacademia), the IT infrastructure that support the integration of the Semantic Web and the social network analysis. The technological engine includes RDF, OWL, Sesame, Elmo, and other open source applications and standards. This book is a must read for computer and information researchers. It is a good reading suggestion for practitioners and other researchers whose interests include social web concepts and applications, information classification, knowledge representation, data integration, visualization, web 2.0, and beyond.
