Microsoft SQL Server

Riff

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Description: 
Riff enables detection, prediction and response to health-related events (such as disease outbreaks or pandemics) through a collaborative environment that combines data exploration, integration, search and inferencing – providing more complex analysis and deeper insight.
Summary: 
Although development of Riff has initially been focused on health-related detection scenarios, the unlying system is a general collaboration environment for content creation, social metadata annotation, and automated analysis with potential applicability in a wide range of areas. Several organizations are exploring the use of Riff in areas as wide ranging as humanitarian crisis reporting and conflict early warning. One organization, for example, has recently begun training Riff's integrated SVM machine learning engine to identify hate speech and other potential indicatorsof geopolitical deterioration in news reports.
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Features:

  • Create collaborative workspaces, invite colleagues, subscribe to data sources you choose to monitor
  • Interact securely with your team to sift through the data stream for emerging events
  • Annotate items with tags, comments, ratings, links, locations, files, alerts, and other social metadata
  • Autonomous agents perform data fusion, feature extraction, classification, tagging, geo-coding
  • Integrated hypothesis formation, visualization, machine learning

Contacts Nearby

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Description: 
Contacts Nearby Allows users to discover geographic locations of other people in their extended social network.
Summary: 
Social networks or “friend graphs” are increasingly popular on the internet because they enable applications to learn of trust relationship between users. Combine this information with the geographical location of each user and you get a valuable tool in possible emergency situations.
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The Contacts Nearby application allows users to discover geographic locations of other people in their extended social network. Social networks or “friend graphs” are increasingly popular on the internet because they enable applications to learn of trust relationship between users. Combine this information with the geographical location of each user and you get a valuable tool in possible emergency situations.

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