menu
{ "item_title" : "Social Networks and the Semantic Web", "item_author" : [" Peter Mika "], "item_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, 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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/38/771/000/0387710000_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Social Networks and the Semantic Web|Peter Mika

Social Networks and the Semantic Web

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

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 item is Non-Returnable

Details

  • ISBN-13: 9780387710006
  • ISBN-10: 0387710000
  • Publisher: Springer
  • Publish Date: September 2007
  • Dimensions: 9.56 x 6.36 x 0.8 inches
  • Shipping Weight: 1.11 pounds
  • Page Count: 234

Related Categories

You May Also Like...

    1

BAM Customer Reviews