Patents by Inventor Kaushik Chakrabarti

Kaushik Chakrabarti 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).

  • Wireless communication technology, apparatuses, and methods
    Patent number: 11955732
    Abstract: Millimeter wave (mmWave) technology, apparatuses, and methods that relate to transceivers, receivers, and antenna structures for wireless communications are described. The various aspects include co-located millimeter wave (mmWave) and near-field communication (NFC) antennas, scalable phased array radio transceiver architecture (SPARTA), phased array distributed communication system with MIMO support and phase noise synchronization over a single coax cable, communicating RF signals over cable (RFoC) in a distributed phased array communication system, clock noise leakage reduction, IF-to-RF companion chip for backwards and forwards compatibility and modularity, on-package matching networks, 5G scalable receiver (Rx) architecture, among others.
    Type: Grant
    Filed: December 27, 2022
    Date of Patent: April 9, 2024
    Assignee: Intel Corporation
    Inventors: Erkan Alpman, Arnaud Lucres Amadjikpe, Omer Asaf, Kameran Azadet, Rotem Banin, Miroslav Baryakh, Anat Bazov, Stefano Brenna, Bryan K. Casper, Anandaroop Chakrabarti, Gregory Chance, Debabani Choudhury, Emanuel Cohen, Claudio Da Silva, Sidharth Dalmia, Saeid Daneshgar Asl, Kaushik Dasgupta, Kunal Datta, Brandon Davis, Ofir Degani, Amr M. Fahim, Amit Freiman, Michael Genossar, Eran Gerson, Eyal Goldberger, Eshel Gordon, Meir Gordon, Josef Hagn, Shinwon Kang, Te Yu Kao, Noam Kogan, Mikko S. Komulainen, Igal Yehuda Kushnir, Saku Lahti, Mikko M. Lampinen, Naftali Landsberg, Wook Bong Lee, Run Levinger, Albert Molina, Resti Montoya Moreno, Tawfiq Musah, Nathan G. Narevsky, Hosein Nikopour, Oner Orhan, Georgios Palaskas, Stefano Pellerano, Ron Pongratz, Ashoke Ravi, Shmuel Ravid, Peter Andrew Sagazio, Eren Sasoglu, Lior Shakedd, Gadi Shor, Baljit Singh, Menashe Soffer, Ra'anan Sover, Shilpa Talwar, Nebil Tanzi, Moshe Teplitsky, Chintan S. Thakkar, Jayprakash Thakur, Avi Tsarfati, Yossi Tsfati, Marian Verhelst, Nir Weisman, Shuhei Yamada, Ana M. Yepes, Duncan Kitchin
  • KNOWLEDGE DRIVEN PRE-TRAINED FORM KEY MAPPING
    Publication number: 20240071047
    Abstract: The disclosure herein describes generating input key-standard key mappings for a form. A set of input key-value pairs are received, and a subset of candidate form types are determined from a set of form types using the input key-value pairs. A set of standard keys associated with the determined subset of candidate form types are obtained. A set of input key-standard key pairs are generated using the set of input key-value pairs and the obtained set of standard keys and the set of input key-standard key pairs are narrowed using a narrowing rule. Ranking scores for each input key-standard key pair of the narrowed set of input key-standard key pairs are generated. Each input key of the set of input key-vale pairs is mapped to a standard key of the set of standard keys using at least the generated ranking scores of the narrowed set of input key-standard key pairs.
    Type: Application
    Filed: November 29, 2022
    Publication date: February 29, 2024
    Inventors: Souvik KUNDU, Jianwen ZHANG, Kaushik CHAKRABARTI, Yuet CHING, Leon ROMANIUK, Zheng CHEN, Cha ZHANG, Neta HAIBY, Vinod KURPAD, Anatoly Yevgenyevich PONOMAREV
  • EYES-ON ANALYSIS RESULTS FOR IMPROVING SEARCH QUALITY
    Publication number: 20230153310
    Abstract: Systems are configured for generating and utilizing training data to train learn-to-rank type models in a manner that preserves privacy of client data used for generating the training data. The systems extract features and patterns of the user queries, search results and user interactions with the search results without tracking, storing or transmitting underlying values of the user data to preserve privacy of the user data. Systems are also configured to infer search result quality based on at least the user behavior data, and optionally query intentions, and to generate and label corresponding training data accordingly. This training data is applied to learn-to-rank type models to train the learn-to-rank type model to improve search quality of search results provided by the learn-to-rank type models when new user queries are processed that having features and patterns corresponding to the filtered and labelled training data.
    Type: Application
    Filed: January 19, 2022
    Publication date: May 18, 2023
    Inventors: Xi YUN, Jiantao SUN, Zheng CHEN, Kaushik CHAKRABARTI, Leon Melvin ROMANIUK, Pingjun HU, Mingyu WANG, Wei LI, Yaxi LI, Abhilash SRIVASTAVA
  • Progressive spatial searching using augmented structures
    Patent number: 10963471
    Abstract: A location associated with a user of a computing device and a prefix portion of an input string may be received as one or more successive characters of the input string are provided by the user via the computing device. A list of suggested items may be obtained based on a function of respective recommendation indicators and proximities of the items to the location in response to receiving the prefix portion, and based on partially traversing a character string search structure having a plurality of non-terminal nodes augmented with bound indicators associated with spatial regions. The list of suggested items and descriptive information associated with each suggested item may be returned to the user, in response to receiving the prefix portion, for rendering an image illustrating indicators associated with the list in a manner relative to the location, as the user provides each successive character of the input string.
    Type: Grant
    Filed: December 18, 2018
    Date of Patent: March 30, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Kaushik Chakrabarti, Surajit Chaudhuri, Senjuti Basu Roy
  • Performing an operation relative to tabular data based upon voice input
    Patent number: 10956433
    Abstract: Described herein are various technologies pertaining to performing an operation relative to tabular data based upon voice input. An ASR system includes a language model that is customized based upon content of the tabular data. The ASR system receives a voice signal that is representative of speech of a user. The ASR system creates a transcription of the voice signal based upon the ASR being customized with the content of the tabular data. The operation relative to the tabular data is performed based upon the transcription of the voice signal.
    Type: Grant
    Filed: May 21, 2014
    Date of Patent: March 23, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Prabhdeep Singh, Kris Ganjam, Sumit Gulwani, Mark Marron, Yun-Cheng Ju, Kaushik Chakrabarti
  • Leveraging corporal data for data parsing and predicting
    Patent number: 10915564
    Abstract: The techniques discussed herein leverage structure within data of a corpus to parse unstructured data to obtain structured data and/or to predict latent data that is related to the unstructured and/or structured data. In some examples, parsing and/or predicting can be conducted at varying levels of granularity. In some examples, parsing and/or predicting can be iteratively conducted to improve accuracy and/or to expose more hidden data.
    Type: Grant
    Filed: April 29, 2019
    Date of Patent: February 9, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Kris K. Ganjam, Kaushik Chakrabarti
  • Computing features of structured data
    Patent number: 10896229
    Abstract: The present invention extends to methods, systems, and computer program products for computing features of structured data. Aspects of the invention include computing features of table components (e.g., of rows, columns, cells, etc.). Computed features can be used for ranking the table components. When aggregated, features for different components of a table can be used for ranking the table (e.g., a web table).
    Type: Grant
    Filed: November 12, 2018
    Date of Patent: January 19, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Kanstantsyn Zoryn, Zhimin Chen, Kaushik Chakrabarti, James P. Finnigan, Vivek R. Narasayya, Surajit Chaudhuri, Kris Ganjam
  • Understanding tables for search
    Patent number: 10853344
    Abstract: The present invention extends to methods, systems, and computer program products for understanding tables for search. Aspects of the invention include identifying a subject tuple (e.g., a subject column) for a table, detecting a tuple header (e.g., a column header) using other tables, and detecting a tuple header (e.g., a column header) using a knowledge base. Implementations can be utilized in a structured data search system (SDSS) that indexes structured information, such as, tables in a relational database or html tables extracted from web pages. The SDSS allows users to search over the structured information (tables) using different mechanisms including keyword search and data finding data.
    Type: Grant
    Filed: July 27, 2017
    Date of Patent: December 1, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Zhongyuan Wang, Kanstantsyn Zoryn, Zhimin Chen, Kaushik Chakrabarti, James P. Finnigan, Vivek R. Narasayya, Surajit Chaudhuri, Kris Ganjam
  • Refining structured data indexes
    Patent number: 10810181
    Abstract: The present invention extends to methods, systems, and computer program products for refining structured data indexes. Aspects of the invention include associating structured data, such as, for example, tables, with additional content. Additional content can include content outside the <table> and </table> tags of a web table. Indexes for structured data (e.g., table indexes) can be refined based on the additional content to improve the relevance of providing parts of the structured data (e.g., parts of the table) in search results.
    Type: Grant
    Filed: April 11, 2018
    Date of Patent: October 20, 2020
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Kanstantsyn Zoryn, Zhimin Chen, Kaushik Chakrabarti, James P. Finnigan, Vivek R. Narasayya, Surajit Chaudhuri, Kris Ganjam
  • Retrieval of attribute values based upon identified entities
    Patent number: 10776375
    Abstract: Various technologies that facilitate performance of a data finding data (DFD) search are described herein. A user specifies entities, for example, by entering the entities into a query field, selecting the entities from a computer-executable application, or the like. The user further specifies an attribute of the entities that is of interest. A query is constructed based upon the entities and the attribute, and a search for tables is performed based upon the entities and the attribute. Values of the attribute for the selected entities are identified in a table, and the values of the attribute are returned.
    Type: Grant
    Filed: May 21, 2014
    Date of Patent: September 15, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Kris Ganjam, Zhimin Chen, Kaushik Chakrabarti, Surajit Chaudhuri, Vivek Narasayya, James Finnigan, Kanstantsyn Zoryn
  • Concept expansion using tables
    Patent number: 10769140
    Abstract: Concept expansion using tables, such as web tables, can return entities belonging to a concept based on an input of the concept and at least one seed entity that belongs to the concept. A concept expansion frontend can receive the concept and seed entity and provide them to a concept expansion framework. The concept expansion framework can expand the coverage of entities for concepts, including tail concepts, using tables by leveraging rich content signals corresponding to concept names. Such content signals can include content matching the concept that appear in captions, early headings, page titles, surrounding text, anchor text, and queries for which the page has been clicked. The concept expansion framework can use the structured entities in tables to infer exclusive tables. Such inference differs from previous label propagation methods and involves modeling a table-entity relationship. The table-entity relationship reduces semantic drift without using a reference ontology.
    Type: Grant
    Filed: June 29, 2015
    Date of Patent: September 8, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Philip A. Bernstein, Kaushik Chakrabarti, Zhimin Chen, Yeye He, Chi Wang, Kris K. Ganjam
  • Aggregate-query database system and processing
    Patent number: 10740328
    Abstract: A processing unit can determine a first subset of a data set including data records selected based on measure values thereof. The processing unit can determine an index mapping a predicate to data records associated with that predicate and approximation values of the records. The processing unit can process a query against the first subset to provide a first result and a first accuracy value, determine that the first accuracy value does not satisfy an accuracy criterion, and process the query against the index. In some examples, the processing unit can process the query against a second subset including data records satisfying a predetermined predicate. In some examples, the processing unit can receive data records and determine the first subset. Data records can include respective measure values. Data records with higher measure values can occur in the first subset more frequently than data records with lower measure values.
    Type: Grant
    Filed: June 24, 2016
    Date of Patent: August 11, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Bolin Ding, Silu Huang, Chi Wang, Kaushik Chakrabarti, Surajit Chaudhuri
  • Semantic matching and annotation of attributes
    Patent number: 10726018
    Abstract: Techniques and constructs to facilitate semantic matching and automated annotation (SMA) of attributes can take entity names and a keyword describing an attribute associated with the named entities as input and leverage a corpus of data such as data from tables, which can include HTML web tables, to automatically populate values associated with the named entities for the attribute. The constructs enable accurate SMA of attributes, such as attributes that relate to the entity and include numeric values in a different unit than the query, in a different scale than the query, and/or reflecting a time different from that of the query. An entity augmentation application programming interface (API) may be used to accept queries that include numeric criteria, parameters, or arguments, including query attributes represented by numeric values, which may be in different units or scales, and attributes represented by numeric values that can vary by time.
    Type: Grant
    Filed: February 10, 2014
    Date of Patent: July 28, 2020
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Kaushik Chakrabarti, Meihui Zhang
  • Techniques for digital entity correlation
    Patent number: 10628490
    Abstract: Techniques for using digital entity correlation to generate a composite knowledge graph from constituent graphs. In an aspect, digital attribute values associated with primary entities may be encoded into primitives, e.g., using a multi-resolution encoding scheme. A pairs graph may be constructed, based on seed pairs calculated from correlating encoded primitives, and further expanded to include subjects and objects of the seed pairs, as well as pairs connected to relationship entities. A similarity metric is computed for each candidate pair to determine whether a match exists. The similarity metric may be based on summing a weighted landing probability over all primitives associated directly or indirectly with each candidate pair. By incorporating primitive matches from not only the candidate pair but also from pairs surrounding the candidate pair, entity matching may be efficiently implemented on a holistic basis.
    Type: Grant
    Filed: November 5, 2015
    Date of Patent: April 21, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Mohamed Yakout, Kaushik Chakrabarti, Maria Pershina
  • LEVERAGING CORPORAL DATA FOR DATA PARSING AND PREDICTING
    Publication number: 20190251109
    Abstract: The techniques discussed herein leverage structure within data of a corpus to parse unstructured data to obtain structured data and/or to predict latent data that is related to the unstructured and/or structured data. In some examples, parsing and/or predicting can be conducted at varying levels of granularity. In some examples, parsing and/or predicting can be iteratively conducted to improve accuracy and/or to expose more hidden data.
    Type: Application
    Filed: April 29, 2019
    Publication date: August 15, 2019
    Inventors: Kris K. GANJAM, Kaushik Chakrabarti
  • Leveraging corporal data for data parsing and predicting
    Patent number: 10311092
    Abstract: The techniques discussed herein leverage structure within data of a corpus to parse unstructured data to obtain structured data and/or to predict latent data that is related to the unstructured and/or structured data. In some examples, parsing and/or predicting can be conducted at varying levels of granularity. In some examples, parsing and/or predicting can be iteratively conducted to improve accuracy and/or to expose more hidden data.
    Type: Grant
    Filed: June 28, 2016
    Date of Patent: June 4, 2019
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Kris K. Ganjam, Kaushik Chakrabarti
  • PROGRESSIVE SPATIAL SEARCHING USING AUGMENTED STRUCTURES
    Publication number: 20190129898
    Abstract: A location associated with a user of a computing device and a prefix portion of an input string may be received as one or more successive characters of the input string are provided by the user via the computing device. A list of suggested items may be obtained based on a function of respective recommendation indicators and proximities of the items to the location in response to receiving the prefix portion, and based on partially traversing a character string search structure having a plurality of non-terminal nodes augmented with bound indicators associated with spatial regions. The list of suggested items and descriptive information associated with each suggested item may be returned to the user, in response to receiving the prefix portion, for rendering an image illustrating indicators associated with the list in a manner relative to the location, as the user provides each successive character of the input string.
    Type: Application
    Filed: December 18, 2018
    Publication date: May 2, 2019
    Inventors: Kaushik Chakrabarti, Surajit Chaudhuri, Senjuti Basu Roy
  • COMPUTING FEATURES OF STRUCTURED DATA
    Publication number: 20190080006
    Abstract: The present invention extends to methods, systems, and computer program products for computing features of structured data. Aspects of the invention include computing features of table components (e.g., of rows, columns, cells, etc.). Computed features can be used for ranking the table components. When aggregated, features for different components of a table can be used for ranking the table (e.g., a web table).
    Type: Application
    Filed: November 12, 2018
    Publication date: March 14, 2019
    Inventors: Kanstantsyn ZORYN, Zhimin CHEN, Kaushik CHAKRABARTI, James P. FINNIGAN, Vivek R. NARASAYYA, Surajit CHAUDHURI, Kris GANJAM
  • Progressive spatial searching using augmented structures
    Patent number: 10204142
    Abstract: A location associated with a user of a computing device and a prefix portion of an input string may be received as one or more successive characters of the input string are provided by the user via the computing device. A list of suggested items may be obtained based on a function of respective recommendation indicators and proximities of the items to the location in response to receiving the prefix portion, and based on partially traversing a character string search structure having a plurality of non-terminal nodes augmented with bound indicators associated with spatial regions. The list of suggested items and descriptive information associated with each suggested item may be returned to the user, in response to receiving the prefix portion, for rendering an image illustrating indicators associated with the list in a manner relative to the location, as the user provides each successive character of the input string.
    Type: Grant
    Filed: November 30, 2014
    Date of Patent: February 12, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Kaushik Chakrabarti, Surajit Chaudhuri, Senjuti Basu Roy
  • Computing features of structured data
    Patent number: 10127315
    Abstract: The present invention extends to methods, systems, and computer program products for computing features of structured data. Aspects of the invention include computing features of table components (e.g., of rows, columns, cells, etc.). Computed features can be used for ranking the table components. When aggregated, features for different components of a table can be used for ranking the table (e.g., a web table).
    Type: Grant
    Filed: July 8, 2014
    Date of Patent: November 13, 2018
    Inventors: Kanstantsyn Zoryn, Zhimin Chen, Kaushik Chakrabarti, James P. Finnigan, Vivek R. Narasayya, Surajit Chaudhuri, Kris Ganjam