Patents by Inventor Hima P. Karanam
Hima P. Karanam 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).
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Patent number: 10169418Abstract: Methods, systems, and computer program products for deriving a multi-pass matching algorithm for data de-duplication are provided herein. A method includes identifying multiple passes across multiple databases using a set of one or more blocking columns derived from a set of trained input data; identifying, in each of the multiple passes, one or more columns across the multiple databases that match one or more of the blocking columns; selecting a given pass from the multiple passes, wherein said given pass comprises a maximum number of matching columns within the multiple passes; determining, for the given pass, data that conform to the given pass comprising (i) a set of matching columns, (ii) one or more matching types and (iii) one or more weights; and determining one or more subsequent passes across the multiple databases iteratively by removing the data that conform to the given pass.Type: GrantFiled: September 24, 2014Date of Patent: January 1, 2019Assignee: International Business Machines CorporationInventors: Hima P. Karanam, Albert Maier, Marvin Mendelssohn, Heather Stimpson, Dan Dan Zheng
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Patent number: 10163063Abstract: Computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: GrantFiled: March 7, 2012Date of Patent: December 25, 2018Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Patent number: 10095780Abstract: Computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: GrantFiled: February 7, 2017Date of Patent: October 9, 2018Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Patent number: 9996607Abstract: Described herein are methods, systems and computer program products for entity resolution. Entity resolution, also known as entity matching or record linkage, seeks to identify equivalent data objects between or among datasets. An example method includes creating a deterministic model by defining an entity to be resolved, selecting two datasets for comparison, defining matching predicates for attributes of the datasets to select a set of candidate matches, and defining a precedence rule for the candidate matches to select a subset of the candidate matches. The method includes running the deterministic model on the two datasets. Running the deterministic model includes applying the matching predicates and the precedence rule to data in the datasets that correspond to the attributes. The method also includes applying a cardinality rule to results of the running, and outputting the matching candidates for which the cardinality rule is satisfied.Type: GrantFiled: October 31, 2014Date of Patent: June 12, 2018Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Bogdan Alexe, Douglas R. Burdick, Mauricio A. Hernandez-Sherrington, Hima P. Karanam, Rajasekar Krishnamurthy, Lucian Popa, Shivakumar Vaithyanathan
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Publication number: 20170147688Abstract: Computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: ApplicationFiled: February 7, 2017Publication date: May 25, 2017Inventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Publication number: 20160125067Abstract: Embodiments relate to entity resolution. One aspect includes creating a deterministic model by defining an entity to be resolved, selecting two datasets for comparison, defining matching predicates for attributes of the datasets to select a set of candidate matches, and defining a precedence rule for the candidate matches to select a subset of the candidate matches. An aspect further includes running the deterministic model on the two datasets. Running the deterministic model includes applying the matching predicates and the precedence rule to data in the datasets that correspond to the attributes. An aspect also includes applying a cardinality rule to results of the running, and outputting the matching candidates for which the cardinality rule is satisfied.Type: ApplicationFiled: October 31, 2014Publication date: May 5, 2016Inventors: Bogdan Alexe, Douglas R. Burdick, Mauricio A. Hernandez-Sherrington, Hima P. Karanam, Rajasekar Krishnamurthy, Lucian Popa, Shivakumar Vaithyanathan
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Publication number: 20160085807Abstract: Methods, systems, and computer program products for deriving a multi-pass matching algorithm for data de-duplication are provided herein. A method includes identifying multiple passes across multiple databases using a set of one or more blocking columns derived from a set of trained input data; identifying, in each of the multiple passes, one or more columns across the multiple databases that match one or more of the blocking columns; selecting a given pass from the multiple passes, wherein said given pass comprises a maximum number of matching columns within the multiple passes; determining, for the given pass, data that conform to the given pass comprising (i) a set of matching columns, (ii) one or more matching types and (iii) one or more weights; and determining one or more subsequent passes across the multiple databases iteratively by removing the data that conform to the given pass.Type: ApplicationFiled: September 24, 2014Publication date: March 24, 2016Inventors: Hima P. Karanam, Albert Maier, Marvin Mendelssohn, Heather Stimpson, Dan Dan Zheng
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Patent number: 9213574Abstract: A method, system and a computer program product for determining resources allocation in a distributed computing environment. An embodiment may include identifying resources in a distributed computing environment, computing provisioning parameters, computing configuration parameters and quantifying service parameters in response to a set of service level agreements (SLA). The embodiment may further include iteratively computing a completion time required for completion of the assigned task and a cost. Embodiments may further include computing an optimal resources configuration and computing at least one of an optimal completion time and an optimal cost corresponding to the optimal resources configuration. Embodiments may further include dynamically modifying the optimal resources configuration in response to at least one change in at least one of provisioning parameters, computing parameters and quantifying service parameters.Type: GrantFiled: January 30, 2010Date of Patent: December 15, 2015Assignee: International Business Machines CorporationInventors: Tanveer A Faruquie, Hima P Karanam, Mukesh K Mohania, L Venkata Subramaniam, Girish Venkatachaliah
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Patent number: 9104709Abstract: According to one embodiment of the present invention, a system controls cleansing of data within a database system, and comprises a computer system including at least one processor. The system receives a data set from the database system, and one or more features of the data set are selected for determining values for one or more characteristics of the selected features. The determined values are applied to a data quality estimation model to determine data quality estimates for the data set. Problematic data within the data set are identified based on the data quality estimates, where the cleansing is adjusted to accommodate the identified problematic data. Embodiments of the present invention further include a method and computer program product for controlling cleansing of data within a database system in substantially the same manner described above.Type: GrantFiled: March 16, 2012Date of Patent: August 11, 2015Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A Faruquie, Hima P Karanam, Mukesh K Mohania, L Venkata Subramaniam
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Patent number: 8996524Abstract: Methods, computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: GrantFiled: March 8, 2012Date of Patent: March 31, 2015Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Patent number: 8700542Abstract: Systems, methods, and computer products for optimally managing large rule sets are disclosed. Rule dependencies of rules within a set of rules may be determined as a function of rules execution frequency data generated from applying the rules over a data set. The rules within the set of rules may be clustered into rules clusters based on the determined rule dependencies, in which the rules clusters comprise disjoint subsets of the rules within the set of rules. Cluster frequency data for the rules clusters may be used to arrive at an optimal ordering. Each rule within the set of rules may be assigned a unique identification that may capture an execution order of the rules within the set of rules.Type: GrantFiled: December 15, 2010Date of Patent: April 15, 2014Assignee: International Business Machines CorporationInventors: Mohan N. Dani, Tanveer A. Faruquie, Hima P. Karanam, L. Venkata Subramaniam, Girish Venkatachaliah
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Patent number: 8560506Abstract: A method of blocking column selection can include determining a first parameter for each column set of a plurality of column sets, wherein the first parameter indicates distribution of blocks in the column set, and determining a second parameter for each column set. The second parameter can indicate block size for the column set. For each column set, a measure of blockability that is dependent upon at least the first parameter and the second parameter can be calculated using a processor. The plurality of column sets can be ranked according to the measures of blockability.Type: GrantFiled: April 16, 2012Date of Patent: October 15, 2013Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Patent number: 8560505Abstract: Blocking column selection can include determining a first parameter for each column set of a plurality of column sets, wherein the first parameter indicates distribution of blocks in the column set, and determining a second parameter for each column set. The second parameter can indicate block size for the column set. For each column set, a measure of blockability that is dependent upon at least the first parameter and the second parameter can be calculated using a processor. The plurality of column sets can be ranked according to the measures of blockability.Type: GrantFiled: December 7, 2011Date of Patent: October 15, 2013Assignee: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Publication number: 20130238610Abstract: Computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: ApplicationFiled: March 7, 2012Publication date: September 12, 2013Applicant: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Publication number: 20130238611Abstract: Methods, computer program products and systems are provided for mining for sub-patterns within a text data set. The embodiments facilitate finding a set of N frequently occurring sub-patterns within the data set, extracting the N sub-patterns from the data set, and clustering the extracted sub-patterns into K groups, where each extracted sub-pattern is placed within the same group with other extracted sub-patterns based upon a distance value D that determines a degree of similarity between the sub-pattern and every other sub-pattern within the same group.Type: ApplicationFiled: March 8, 2012Publication date: September 12, 2013Applicant: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Marvin Mendelssohn, Mukesh K. Mohania, L. Venkata Subramaniam
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Publication number: 20130151487Abstract: Blocking column selection can include determining a first parameter for each column set of a plurality of column sets, wherein the first parameter indicates distribution of blocks in the column set, and determining a second parameter for each column set. The second parameter can indicate block size for the column set. For each column set, a measure of blockability that is dependent upon at least the first parameter and the second parameter can be calculated using a processor. The plurality of column sets can be ranked according to the measures of blockability.Type: ApplicationFiled: December 7, 2011Publication date: June 13, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: SNIGDHA CHATURVEDI, TANVEER A. FARUQUIE, HIMA P. KARANAM, MARVIN MENDELSSOHN, MUKESH K. MOHANIA, L. VENKATA SUBRAMANIAM
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Publication number: 20130151490Abstract: A method of blocking column selection can include determining a first parameter for each column set of a plurality of column sets, wherein the first parameter indicates distribution of blocks in the column set, and determining a second parameter for each column set. The second parameter can indicate block size for the column set. For each column set, a measure of blockability that is dependent upon at least the first parameter and the second parameter can be calculated using a processor. The plurality of column sets can be ranked according to the measures of blockability.Type: ApplicationFiled: April 16, 2012Publication date: June 13, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: SNIGDHA CHATURVEDI, TANVEER A. FARUQUIE, HIMA P. KARANAM, MARVIN MENDELSSOHN, MUKESH K. MOHANIA, L. VENKATA SUBRAMANIAM
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Publication number: 20120179658Abstract: According to one embodiment of the present invention, a system controls cleansing of data within a database system, and comprises a computer system including at least one processor. The system receives a data set from the database system, and one or more features of the data set are selected for determining values for one or more characteristics of the selected features. The determined values are applied to a data quality estimation model to determine data quality estimates for the data set. Problematic data within the data set are identified based on the data quality estimates, where the cleansing is adjusted to accommodate the identified problematic data. Embodiments of the present invention further include a method and computer program product for controlling cleansing of data within a database system in substantially the same manner described above.Type: ApplicationFiled: March 16, 2012Publication date: July 12, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Mukesh K. Mohania, L. Venkata Subramaniam
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Publication number: 20120158619Abstract: Systems, methods, and computer products for optimally managing large rule sets are disclosed. Rule dependencies of rules within a set of rules may be determined as a function of rules execution frequency data generated from applying the rules over a data set. The rules within the set of rules may be clustered into rules clusters based on the determined rule dependencies, in which the rules clusters comprise disjoint subsets of the rules within the set of rules. Cluster frequency data for the rules clusters may be used to arrive at an optimal ordering.Type: ApplicationFiled: December 15, 2010Publication date: June 21, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: MOHAN N. DANI, TANVEER A. FARUQUIE, HIMA P. KARANAM, L.V. SUBRAMANIAM, GIRISH VENKATACHALIAH
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Publication number: 20120150825Abstract: According to one embodiment of the present invention, a system controls cleansing of data within a database system, and comprises a computer system including at least one processor. The system receives a data set from the database system, and one or more features of the data set are selected for determining values for one or more characteristics of the selected features. The determined values are applied to a data quality estimation model to determine data quality estimates for the data set. Problematic data within the data set are identified based on the data quality estimates, where the cleansing is adjusted to accommodate the identified problematic data. Embodiments of the present invention further include a method and computer program product for controlling cleansing of data within a database system in substantially the same manner described above.Type: ApplicationFiled: December 13, 2010Publication date: June 14, 2012Applicant: International Business Machines CorporationInventors: Snigdha Chaturvedi, Tanveer A. Faruquie, Hima P. Karanam, Mukesh K. Mohania, L. Venkata Subramaniam