| Patent application number | Description | Published |
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| 20140317033 | PREDICTIVE AND DESCRIPTIVE ANALYSIS ON RELATIONS GRAPHS WITH HETEROGENEOUS ENTITIES - A system, method and computer program product provides a random walk model with heterogeneous graphs to leverage multiple source data and accomplish prediction tasks. The system and method components include: 1) A heterogeneous graph formulation including heterogeneous instances of abstract objects as graph nodes and multiple relations as edges connecting those nodes. The different types of relations, such as client-vendor relation and client-product relation, are often quantified as the weights of edges connecting those entities; 2) To accomplish prediction tasks with such information, launching a multi-stage random walk model over the heterogeneous graph. The random walk within a subgraph with homogenous nodes usually produces the relevance between entities of the same type. The random walk across different type of nodes provides the prediction of decisions, such as a client purchasing a product. | 10-23-2014 |
| 20150059438 | FOOD STEGANOGRAPHY - The present disclosure relates to methods and systems for calculating a food additive. A first method includes identifying chemical compounds of an averse food ingredient, identifying chemical compounds of a flavorful food ingredient and calculating a set of chemical compounds for the food additive such that an olfactory perception of a mixture of the averse food ingredient, the flavorful food ingredient and the food additive is the same as an olfactory perception of only the flavorful food ingredient. A first device includes a database storing information identifying chemical compounds of an averse food ingredient and identifying chemical compounds of a flavorful food ingredient, and a processor for calculating a food additive such that an olfactory perception of flavors of a mixture of the averse food ingredient, the flavorful food ingredient and the food additive is the same as an olfactory perception of only the flavorful food ingredient. | 03-05-2015 |
| 20150066386 | FOOD STEGANOGRAPHY - The present disclosure relates to methods and systems for calculating a food additive. A first method includes identifying chemical compounds of an averse food ingredient, identifying chemical compounds of a flavorful food ingredient and calculating a set of chemical compounds for the food additive such that an olfactory perception of a mixture of the averse food ingredient, the flavorful food ingredient and the food additive is the same as an olfactory perception of only the flavorful food ingredient. A first device includes a database storing information identifying chemical compounds of an averse food ingredient and identifying chemical compounds of a flavorful food ingredient, and a processor for calculating a food additive such that an olfactory perception of flavors of a mixture of the averse food ingredient, the flavorful food ingredient and the food additive is the same as an olfactory perception of only the flavorful food ingredient. | 03-05-2015 |
| 20150161531 | ASSOCIATION-BASED PRODUCT DESIGN - A method for designing a new product includes automatically identifying a plurality of components of stored products, wherein the plurality of components is associated with an existing component included in a design of the new product, automatically selecting a new component from among the plurality of components, wherein a relationship between the existing component and the new component optimizes a design objective for the new product, automatically adding the new component to the design for the new product, and iteratively repeating the identifying, the selecting, and the adding until a stopping criterion is met, wherein the design for the new product is complete when the stopping criterion is met. | 06-11-2015 |
| 20150199614 | COMPUTING PERSONALIZED PROBABILISTIC FAMILIARITY BASED ON KNOWN ARTIFACT DATA - Software that uses personalized information pertaining to a user to determine how familiar (or “novel” or “surprising”) a new artifact will be to the user, by performing the following steps: (i) receiving the identity of a first user; (ii) receiving a first dataset pertaining to the first user; (iii) receiving the identity of a first artifact; and (iv) applying a probabilistic familiarity algorithm to the first dataset with respect to the first artifact to yield a probabilistic familiarity value for the first artifact with respect to the first user. The first dataset is received over a computer network, and the first dataset includes at least one piece of personalized information for the first user. | 07-16-2015 |
| 20150317376 | METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AUTOMATING EXPERTISE MANAGEMENT USING SOCIAL AND ENTERPRISE DATA - A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context. The method can also use the context-specific weights obtained from the co-association information in a matrix completion procedure, and finally merge the context-specific outputs to obtain overall skills predictions, analyses and inferences. A computer program product and a system are also disclosed for performing the method. | 11-05-2015 |
| 20150324711 | ASSOCIATION-BASED PRODUCT DESIGN - A method for designing a new product includes automatically identifying a plurality of components of stored products, wherein the plurality of components is associated with an existing component included in a design of the new product, automatically selecting a new component from among the plurality of components, wherein a relationship between the existing component and the new component optimizes a design objective for the new product, automatically adding the new component to the design for the new product, and iteratively repeating the identifying, the selecting, and the adding until a stopping criterion is met, wherein the design for the new product is complete when the stopping criterion is met. | 11-12-2015 |
| 20160048853 | GENERATING WORK PRODUCTS USING WORK PRODUCT METRICS AND PREDICTED CONSTITUENT AVAILABILITY - A method includes predicting availability of a plurality of constituents for one or more future epochs, obtaining one or more metrics for each of a plurality of existing work products, each of the plurality of existing work products using at least one constituent, and generating at least one work product for each of the one or more future epochs based in part on the predicted availability of the constituents and the one or more metrics for the existing work products. The metrics for the existing work products may include quality metrics and novelty metrics. | 02-18-2016 |
| 20160071211 | NONPARAMETRIC TRACKING AND FORECASTING OF MULTIVARIATE DATA - Risk management is facilitated by tracking and forecasting multivariate data using nonparametric statistical procedures. Enhanced matrix factorization is used for developing a nonparametric tracking and forecasting algorithm, based on Kalman smoothing, that applies a state space model to both (i) factor loading, and (ii) factor time series of multivariate data in the matrix factorization. One example of use is tracking and forecasting financial risk according to a yield curve based on multivariate financial data. The forecasted yield curve change forms the bases, for example, of risk exposure adjustments associated with US Treasury bond investment. | 03-10-2016 |
