| CHARLES RIVER ANALYTICS, INC. Patent applications |
| Patent application number | Title | Published |
|---|
| 20120084239 | Methods and Systems for Constructing Bayesian Belief Networks - Methods and systems are described for simplifying a causal influence model that describes influence of parent nodes X | 04-05-2012 |
| 20100023469 | OBJECTIVE DECISION MAKING APPLICATION USING BIAS WEIGHTING FACTORS - A method and system for implementing a weighted belief network that assists collaborative users in making decisions. A belief network structure is employed that further includes user controlled weighting and biasing factors to adjust the probabilities for the various nodes. The various participants have the opportunity to make adjustments to the weighting and credibility of the evidence and participants in the decision making process in order to arrive at what may be perceived as a more objective outcome. As the collaborative environment is established and the belief network is built, each user can apply various weighting and bias scenarios from their own perspective thereby allowing each discrete user to work out their various suspicions regarding the bias of other participants or the actual weight of a discrete piece of supporting evidence in the context of the entire belief network. | 01-28-2010 |
| 20100023300 | SENSOR BASED MONITORING OF SOCIAL NETWORKS - A method and system for detecting and monitoring discrete interactions within a physical social network is provided. The system and method detects attributes associated with human communication activities and distinguishes them from other concurrently detected activities in order to identify discrete interactions that are in turn transmitted across a network having a limited data rate. Generally, in its simplest form a plurality of wireless sensors are deployed across a cross-section of people of interest. Once deployed, the wireless sensors establish an ad-hoc network that transmits a small amount of data relating to the each of the discrete individuals bearing a sensor. The collected data is analyzed through the application of rules set forth in a Bayesian belief network to make a determination regarding the probability that an actual interaction between two individuals bearing sensors in fact occurred. | 01-28-2010 |
| 20090259543 | SENSOR NETWORK OPTIMIZATION ALGORITHM - An algorithm for modeling and optimizing control of a complex and dynamic system is provided to facilitate an allocation of the resources on the network that is the most efficient. The algorithm serves to depict the complex network of available resources using market-based negotiation wherein resources are defined as available buyers and sellers in an efficient market. Selling agents are offering their available resources for sale in accordance with parameters that correspond to the actual limitations of that actual resource and the buyers are looking to make a purchase from one of the sellers that presents a resource with the greatest utility to them. In order to overcome inefficiencies that result from the potential of inefficient allocation, the present invention has further endeavored to introduce an efficiency-arbitrage agent that scans the overall body of transactions to identify and remedy inefficient market transactions. | 10-15-2009 |
