Patent application number | Description | Published |
20130036116 | PRIVACY-AWARE ON-LINE USER ROLE TRACKING - Access is obtained to a first nonnegative factor matrix and a second nonnegative factor matrix obtained by factorizing a nonnegative asymmetric matrix which represents a set of data which tracks time-stamped activities of a plurality of entities. The first nonnegative factor matrix is representative of initial role membership of the entities, and the second nonnegative factor matrix is representative of initial role activity descriptions. At a given one of the time stamps, while holding a change in the first nonnegative factor matrix constant, a change in the second nonnegative factor matrix is updated to reflect time variance of the set of data at the given one of the time stamps, without accessing actual data values at previous ones of the time stamps. At the given one of the time stamps, while holding a change in the second nonnegative factor matrix constant, a change in the first nonnegative factor matrix is updated, to reflect the time variance of the set of data at the given one of the time stamps, without accessing the actual data values at the previous ones of the time stamps. The role membership of the entities and the role activity descriptions, at the given one of the time stamps, are updated based on the updating steps. A suitable technique for nonnegative symmetric matrices is also provided. | 02-07-2013 |
20130046768 | FINDING A TOP-K DIVERSIFIED RANKING LIST ON GRAPHS - A method, system and computer program product for finding a diversified ranking list for a given query. In one embodiment, a multitude of date items responsive to the query are identified, a marginal score is established for each data item; and a set, or ranking list, of the data items is formed based on these scores. This ranking list is formed by forming an initial set, and one or more data items are added to the ranking list based on the marginal scores of the data items. In one embodiment, each of the data items has a measured relevance and a measured diversity value, and the marginal scores for the data items are based on the measured relevance and the measured diversity values of the data items. | 02-21-2013 |
20130046769 | MEASURING THE GOODNESS OF A TOP-K DIVERSIFIED RANKING LIST - A method, system and computer program product for measuring a relevance and diversity of a ranking list to a given query. The ranking list is comprised of a set of data items responsive to the query. In one embodiment, the method comprises calculating a measured relevance of the set of data items to the query using a defined relevance measuring procedure, and determining a measured diversity value for the ranking list using a defined diversity measuring procedure. The measured relevance and the measured diversity value are combined to obtain a measure of the combined relevance and diversity of the ranking list. The measured relevance of the set of data items may be based on the individual relevance of each of the data items to the query, and the diversity value may be based on the similarities of the data items to each other. | 02-21-2013 |
20130346467 | EFFICIENT EGONET COMPUTATION IN A WEIGHTED DIRECTED GRAPH - An embodiment of the invention pertains to a weighted directed graph comprising multiple nodes and edges that each extends between two nodes. The embodiment includes processing edges to generate a forward and reverse edge corresponding to each edge. Forward and reverse edges are processed to generate indirect edges, each comprising two edge components, and extending between two nodes. One node associated with each forward edge, each reverse edge, and each indirect edge is selected to be the key node of its associated edge. All forward, reverse and indirect edges having a particular node as their respective key nodes are placed into a group. All edges of the group are then selectively processed to provide information pertaining to an egonet of the graph that has the particular node as its egonode. | 12-26-2013 |
20140025617 | DETERMINING SOFT GRAPH CORRESPONDENCE - A method for determining a correspondence between a first node set of a first graph and a second node of a second graph includes building a feature representation for each of the first graph and the second graph, and inferring the correspondence between the first node set and the second node set based on the feature representations. | 01-23-2014 |
20140025689 | DETERMINING A SIMILARITY BETWEEN GRAPHS - A method for determining a similarity between a plurality of graphs includes inferring a low-rank representation of a first graph, inferring a low-rank representation of a second graph, wherein the low-rank representations of the first and second graphs are stored in memory, estimating a left interaction between the first and second graphs, estimating a middle interaction between the first and second graphs, estimating a right interaction between the first and second graphs, wherein the estimations are based on the low-rank representations of the first and second graphs stored in memory, and aggregating the left interaction, the middle interaction and the right interaction into a kernel, wherein the kernel is indicative of the similarity between the first and second graphs. | 01-23-2014 |
20140067873 | EFFICIENT EGONET COMPUTATION IN A WEIGHTED DIRECTED GRAPH - An embodiment of the invention pertains to a weighted directed graph comprising multiple nodes and edges that each extends between two nodes. The embodiment includes processing edges to generate a forward and reverse edge corresponding to each edge. Forward and reverse edges are processed to generate indirect edges, each comprising two edge components, and extending between two nodes. One node associated with each forward edge, each reverse edge, and each indirect edge is selected to be the key node of its associated edge. All forward, reverse and indirect edges having a particular node as their respective key nodes are placed into a group. All edges of the group are then selectively processed to provide information pertaining to an egonet of the graph that has the particular node as its egonode. | 03-06-2014 |
20140074796 | DYNAMIC ANOMALY, ASSOCIATION AND CLUSTERING DETECTION - Techniques are provided for dynamic anomaly, association and clustering detection. At least one code table is built for each attribute in a set of data containing one or more attributes. One or more clusters associated with one or more of the code tables are established. One or more new data points are received. A determination is made if a given one of the new data points is an anomaly. At least one of the one or more code tables is updated responsive to the determination. When a compression cost of a given one of the new data points is greater than a threshold compression cost for each of the one or more clusters, the given one of the new data points is an anomaly. | 03-13-2014 |
20140074838 | ANOMALY, ASSOCIATION AND CLUSTERING DETECTION - Techniques are provided for anomaly, association and clustering detection. At least one code table is built for each attribute in a set of data. A first code table corresponding to a first attribute and a second code table corresponding to a second attribute are selected. The first code table and the second code table are merged into a merged code table, and a determination is made to accept or reject the merged code table. An anomaly is detected when a total compression cost for a data point is greater than a threshold compression cost inferred from one or more code tables. An association in a data table is detected by merging attribute groups, splitting data groups, and assigning data points to data groups. A cluster is inferred from a matrix of data and code words for each of the one or more code tables. | 03-13-2014 |