Abstract: A system for reducing data collection burden, comprising: one or more programs including instructions for: receiving a first set of metrics for a plurality of facilities; receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities; determining one or more anomalies in the received data; removing the determined one or more anomalies from the received data; selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.

Abstract: A system for reducing data collection burden, comprising: one or more programs including instructions for: receiving a first set of metrics for a plurality of facilities; receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities; determining one or more anomalies in the received data; removing the determined one or more anomalies from the received data; selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.

Abstract: A system for reducing data collection burden, comprising: one or more programs including instructions for: receiving a first set of metrics for a plurality of facilities; receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities; determining one or more anomalies in the received data; removing the determined one or more anomalies from the received data; selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.

Abstract: Quantitatively identifying and forecasting shifts in a mood of social media users is described. An example method includes categorizing the textual messages generated from the social media users over a selected period of time into a plurality of word categories, with each word category containing a set of words associated with the mood of social media users. A score indicating an intensity of the mood of the social media users is calculated for each word category, wherein a value of the score and its corresponding time point define a data point for the word category. Subsequently, breakpoints in the mood of social media users are determined so that the breakpoints minimize a sum of square errors representing a measurement of a consistency of all data points from inferred values of the scores of the data points derived using the breakpoints over the selected period of time.

Abstract: Quantitatively identifying and forecasting shifts in a mood of social media users is described. An example method includes categorizing the textual messages generated from the social media users over a selected period of time into a plurality of word categories, with each word category containing a set of words associated with the mood of social media users. A score indicating an intensity of the mood of the social media users is calculated for each word category, wherein a value of the score and its corresponding time point define a data point for the word category. Subsequently, breakpoints in the mood of social media users are determined so that the breakpoints minimize a sum of square errors representing a measurement of a consistency of all data points from inferred values of the scores of the data points derived using the breakpoints over the selected period of time.

Abstract: In one aspect, a technique is provided for protecting a data set with a parity set defined by a bipartite graph having a degree distribution that includes no parity symbol having a degree less than three. In another aspect, a parity set defined by an irregular bipartite graph is transmitted along with the data set, and corruptions in the data set are decoded using the data set and the parity set. In another aspect, a particularly useful degree distribution for the parity symbols is defined.

Abstract: In one aspect, a technique is provided for protecting a data set with a parity set defined by a bipartite graph having a degree distribution that includes no parity symbol having a degree less than three. In another aspect, a parity set defined by an irregular bipartite graph is transmitted along with the data set, and corruptions in the data set are decoded using the data set and the parity set. In another aspect, a particularly useful degree distribution for the parity symbols is defined.

Abstract: A method and apparatus to calculate probabilistic routing parameters to more efficiently route telephone calls from an origin to one of a plurality of call centers. In particular, the rate of calls routed to each gate of each call center is measured for a previous time frame and used to estimate the rate of calls routed to input nodes of a routing network from an origin for a next time frame. Using these estimated rates of calls routed to the input nodes, a quadratic programming technique is used to calculate probabilistic routing parameters. These parameters are modified either automatically or by a network manager to improve the routing efficiency.