| Social Networks and the Semantic Web 2007 Edition Contributor(s): Mika, Peter (Author) |
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ISBN: 0387710000 ISBN-13: 9780387710006 Publisher: Springer OUR PRICE: $104.49 Product Type: Hardcover - Other Formats Published: September 2007 Annotation: Whether we changed the Web or the Web has changed us is difficult to discern, even with the wisdom of hindsight. Social Networks and the Semantic Web 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 study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies. Social Networks and The Semantic Web is designed for researchers and advanced-level students of the semantic Web and Web services, information systems, social and information sciences. This book is useful for practitioners in industry as well. Foreword by Frank van Harmelen, author of the Semantic Web Primer |
| Additional Information |
| BISAC Categories: - Computers | Information Technology - Computers | Networking - Hardware - Computers | Databases - General |
| Dewey: 004 |
| LCCN: 2007926707 |
| Series: Semantic Web and Beyond |
| Physical Information: 0.8" H x 6.36" W x 9.56" (1.11 lbs) 252 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. It reveals how social network mining from the web plays an important role 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. |