Patents by Inventor Christopher Alan MEEK
Christopher Alan MEEK 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: 20240119099Abstract: A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.Type: ApplicationFiled: December 15, 2023Publication date: April 11, 2024Applicant: Microsoft Technology Licensing, LLCInventors: Gonzalo A. RAMOS, Jin A. SUH, Shiqian Rachel NG, Christopher Alan MEEK, Haekyu PARK
-
Publication number: 20240104405Abstract: In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogenous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units.Type: ApplicationFiled: December 6, 2023Publication date: March 28, 2024Applicant: Microsoft Technology Licensing, LLCInventors: Gonzalo A. RAMOS, Jin A SUH, Christopher Alan MEEK, Shiqian Rachel NG, Napol RACHATASUMRIT
-
Patent number: 11900061Abstract: A method and system for predicting an intended time interval for a content segment may include receiving a request for natural language processing (NLP) of the content segment, the content segment including one or more temporal expressions, accessing contextual data associated with each of the one or more temporal expressions, decoding the content segment into a program that describes a temporal logic of the content segment based on the one or more temporal expressions, evaluating the program using the contextual data to predict an intended time interval for the content segment, and providing the intended time interval as an output.Type: GrantFiled: April 14, 2021Date of Patent: February 13, 2024Assignee: Microsoft Technology Licensing, LLCInventors: Pamela Bhattacharya, Christopher Alan Meek, Oleksandr Polozov, Alex James Boyd
-
Patent number: 11887011Abstract: In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogeneous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units.Type: GrantFiled: February 8, 2021Date of Patent: January 30, 2024Assignee: Microsoft Technology Licensing, LLCInventors: Gonzalo A. Ramos, Jin A Suh, Christopher Alan Meek, Shiqian Rachel Ng, Napol Rachatasumrit
-
Patent number: 11847178Abstract: A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.Type: GrantFiled: March 1, 2022Date of Patent: December 19, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Gonzalo A. Ramos, Jin A. Suh, Shiqian Rachel Ng, Christopher Alan Meek, Haekyu Park
-
Publication number: 20230281259Abstract: A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.Type: ApplicationFiled: March 1, 2022Publication date: September 7, 2023Applicant: Microsoft Technology Licensing, LLCInventors: Gonzalo A. RAMOS, Jin A. SUH, Shiqian Rachel NG, Christopher Alan MEEK, Haekyu PARK
-
Publication number: 20220343079Abstract: A method and system for predicting an intended time interval for a content segment may include receiving a request for natural language processing (NLP) of the content segment, the content segment including one or more temporal expressions, accessing contextual data associated with each of the one or more temporal expressions, decoding the content segment into a program that describes a temporal logic of the content segment based on the one or more temporal expressions, evaluating the program using the contextual data to predict an intended time interval for the content segment, and providing the intended time interval as an output.Type: ApplicationFiled: April 14, 2021Publication date: October 27, 2022Applicant: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Pamela BHATTACHARYA, Christopher Alan MEEK, Oleksandr POLOZOV, Alex James BOYD
-
Publication number: 20220253719Abstract: In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogeneous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units.Type: ApplicationFiled: February 8, 2021Publication date: August 11, 2022Applicant: Microsoft Technology Licensing, LLCInventors: Gonzalo A. RAMOS, Jin A. SUH, Christopher Alan MEEK, Shiqian Rachel NG, Napol RACHATASUMRIT