Patents by Inventor Charu Aggarwal

Charu Aggarwal has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20200327456
    Abstract: Embodiments for implementing enhanced ensemble model diversity and learning by a processor. One or more data sets may be created by combining one or more clusters of data points of a minority class with selected data points of a majority class. One or more ensemble models may be created from the one or more data sets using a supervised machine learning operation. An occurrence of an event may be predicted using the one or more ensemble models.
    Type: Application
    Filed: April 11, 2019
    Publication date: October 15, 2020
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Saket SATHE, Deepak TURAGA, Charu AGGARWAL, Raju PAVULURI, Yuan-Chi CHANG
  • Patent number: 10331671
    Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.
    Type: Grant
    Filed: May 25, 2018
    Date of Patent: June 25, 2019
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Charu Aggarwal, Yanjie Fu, Srinivasan Parthasarathy, Deepak Turaga
  • Publication number: 20180300371
    Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.
    Type: Application
    Filed: May 25, 2018
    Publication date: October 18, 2018
    Inventors: Charu AGGARWAL, Yanjie FU, Srinivasan PARTHASARATHY, Deepak TURAGA
  • Patent number: 10031945
    Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.
    Type: Grant
    Filed: December 20, 2016
    Date of Patent: July 24, 2018
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Charu Aggarwal, Yanjie Fu, Srinivasan Parthasarathy, Deepak Turaga
  • Publication number: 20170228432
    Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.
    Type: Application
    Filed: December 20, 2016
    Publication date: August 10, 2017
    Inventors: Charu Aggarwal, Yanjie Fu, Srinivasan Parthasarathy, Deepak Turaga
  • Patent number: 9576031
    Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.
    Type: Grant
    Filed: February 8, 2016
    Date of Patent: February 21, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Charu Aggarwal, Yanjie Fu, Srinivasan Parthasarathy, Deepak Turaga
  • Patent number: 8914371
    Abstract: A method and system for detecting an event from a social stream. The method includes the steps of: receiving a social stream from a social network, where the social stream includes at least one object and the object includes a text, sender information of the text, and recipient information of the text; assigning said object to a cluster based on a similarity value between the object and the clusters; monitoring changes in at least one of the clusters; and triggering an alarm when the changes in at least one of the clusters exceed a first threshold value, where at least one of the steps is carried out using a computer device.
    Type: Grant
    Filed: December 13, 2011
    Date of Patent: December 16, 2014
    Assignee: International Business Machines Corporation
    Inventors: Charu Aggarwal, Karthik Subbian
  • Patent number: 8655805
    Abstract: A method for classifying objects in a graph data stream, including receiving a training stream of graph data, the training stream including a plurality of objects along with class labels that are associated with each of the objects, first determining discriminating sets of edges in the training stream for the class labels, wherein a discriminating set of edges is one that is indicative of the object that contains these edges having a given class label, receiving an incoming data stream of the graph data, wherein class labels have not yet been assigned to objects in the incoming data stream, second determining, based on the discriminating sets of edges, class labels that are associated with the objects in the incoming data stream; and outputting to an information repository object class label pairs based on the second determining.
    Type: Grant
    Filed: August 30, 2010
    Date of Patent: February 18, 2014
    Assignee: International Business Machines Corporation
    Inventor: Charu Aggarwal
  • Publication number: 20130151522
    Abstract: A method and system for detecting an event from a social stream. The method includes the steps of: receiving a social stream from a social network, where the social stream includes at least one object and the object includes a text, sender information of the text, and recipient information of the text; assigning said object to a cluster based on a similarity value between the object and the clusters; monitoring changes in at least one of the clusters; and triggering an alarm when the changes in at least one of the clusters exceed a first threshold value, where at least one of the steps is carried out using a computer device.
    Type: Application
    Filed: December 13, 2011
    Publication date: June 13, 2013
    Applicant: International Business Machines Corporation
    Inventors: Charu Aggarwal, Karthik Subbian
  • Patent number: 8375061
    Abstract: In a method for representing a text document with a graphical model, a document including a plurality of ordered words is received and a graph data structure for the document is created. The graph data structure includes a plurality of nodes and edges, with each node representing a distinct word in the document and each edge identifying a number of times two nodes occur within a predetermined distance from each other. The graph data structure is stored in an information repository.
    Type: Grant
    Filed: June 8, 2010
    Date of Patent: February 12, 2013
    Assignee: International Business Machines Corporation
    Inventor: Charu Aggarwal
  • Publication number: 20120054129
    Abstract: A method for classifying objects in a graph data stream, including receiving a training stream of graph data, the training stream including a plurality of objects along with class labels that are associated with each of the objects, first determining discriminating sets of edges in the training stream for the class labels, wherein a discriminating set of edges is one that is indicative of the object that contains these edges having a given class label, receiving an incoming data stream of the graph data, wherein class labels have not yet been assigned to objects in the incoming data stream, second determining, based on the discriminating sets of edges, class labels that are associated with the objects in the incoming data stream; and outputting to an information repository object class label pairs based on the second determining.
    Type: Application
    Filed: August 30, 2010
    Publication date: March 1, 2012
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventor: Charu Aggarwal
  • Patent number: 8086550
    Abstract: Uncertain data is classified by constructing an error adjusted probability density estimate for the data, and applying a subspace exploration process to the probability density estimate to classify the data.
    Type: Grant
    Filed: August 28, 2007
    Date of Patent: December 27, 2011
    Assignee: International Business Machines Corporation
    Inventors: Charu Aggarwal, Philip S. Yu
  • Publication number: 20110302168
    Abstract: In a method for representing a text document with a graphical model, a document including a plurality of ordered words is received and a graph data structure for the document is created. The graph data structure includes a plurality of nodes and edges, with each node representing a distinct word in the document and each edge identifying a number of times two nodes occur within a predetermined distance from each other. The graph data structure is stored in an information repository.
    Type: Application
    Filed: June 8, 2010
    Publication date: December 8, 2011
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventor: Charu Aggarwal
  • Patent number: 8051021
    Abstract: A system and method for resource adaptive classification of data streams. Embodiments of systems and methods provide classifying data received in a computer, including discretizing the received data, constructing an intermediate data structure from said received data as training instances, performing subspace sampling on said received data as test instances and adaptively classifying said received data based on statistics of said subspace sampling.
    Type: Grant
    Filed: September 12, 2006
    Date of Patent: November 1, 2011
    Assignee: International Business Machines Corporation
    Inventors: Charu Aggarwal, Philip Shi-lung Yu
  • Patent number: 7904471
    Abstract: Privacy in data mining of sparse high dimensional data records is preserved by transforming the data records into anonymized data records. This transformation involves creating a sketch-based private representation of each data record, each data record containing only a small number of non-zero attribute value in relation to the high dimensionality of the data records.
    Type: Grant
    Filed: August 9, 2007
    Date of Patent: March 8, 2011
    Assignee: International Business Machines Corporation
    Inventors: Charu Aggarwal, Philip S. Yu
  • Patent number: 7684963
    Abstract: Systems and methods for providing density-based traffic generation. Data are clustered to create partitions, and transforms of clustered data are constructed in a transformed space. Data points are generated via employing grid discretization in the transformed space, and density estimates of the generated data points are employed to generate synthetic pseudo-points.
    Type: Grant
    Filed: March 29, 2005
    Date of Patent: March 23, 2010
    Assignee: International Business Machines Corporation
    Inventor: Charu Aggarwal
  • Publication number: 20090060095
    Abstract: Uncertain data is classified by constructing an error adjusted probability density estimate for the data, and applying a subspace exploration process to the probability density estimate to classify the data.
    Type: Application
    Filed: August 28, 2007
    Publication date: March 5, 2009
    Applicant: INTERNATIONAL BUSINESS MACHINE CORPORATION
    Inventors: Charu Aggarwal, Philip S. Yu
  • Publication number: 20090049069
    Abstract: Privacy in data mining of sparse high dimensional data records is preserved by transforming the data records into anonymized data records. This transformation involves creating a sketch-based private representation of each data record, each data record containing only a small number of non-zero attribute value in relation to the high dimensionality of the data records.
    Type: Application
    Filed: August 9, 2007
    Publication date: February 19, 2009
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Charu Aggarwal, Philip S. Yu
  • Publication number: 20080040346
    Abstract: Methods and apparatus for generating at least one output data set from at least one input data set for use in association with a data mining process are provided. First, data statistics are constructed from the at least one input data set. Then, an output data set is generated from the data statistics. The output data set differs from the input data set but maintains one or more correlations from within the input data set. The correlations may be the inherent correlations between different dimensions of a multidimensional input data set. A significant amount of information from the input data set may be hidden so that the privacy level of the data mining process may be increased.
    Type: Application
    Filed: October 15, 2007
    Publication date: February 14, 2008
    Applicant: International Business Machines Corporation
    Inventors: Charu Aggarwal, Philip Shi-Lung Yu
  • Publication number: 20070288465
    Abstract: Improved techniques are disclosed for detecting patterns of interaction among a set of entities and analyzing community evolution in a stream environment. By way of example, a technique for processing data from a data stream includes the following steps/operations. A data point of the data stream representing an interaction event is obtained. An interaction graph is updated on-line based on the data point representing the interaction event. The updated interaction graph is stored in a nonvolatile memory. An interaction evolution is determined off-line from the updated interaction graph stored in the nonvolatile memory.
    Type: Application
    Filed: October 5, 2005
    Publication date: December 13, 2007
    Applicant: International Business Machines Corporation
    Inventors: Charu Aggarwal, Philip Yu