Patents by Inventor Mengyan LU
Mengyan LU 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).
-
Patent number: 12229513Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: GrantFiled: August 4, 2023Date of Patent: February 18, 2025Assignee: Microsoft Technology Licensing, LLCInventors: Ying Suresh Wang, Min Li, Mengyan Lu
-
Publication number: 20230376692Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: ApplicationFiled: August 4, 2023Publication date: November 23, 2023Applicant: Microsoft Technology Licensing, LLCInventors: Ying Suresh WANG, Min LI, Mengyan LU
-
Patent number: 11763088Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: GrantFiled: March 31, 2022Date of Patent: September 19, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Ying Wang, Min Li, Mengyan Lu
-
Patent number: 11392772Abstract: A coding information extractor disclosed herein uses machine learning approach to extract coding information from documents. An implementation of the coding information extractor is implemented using various computer process instructions including scanning a document to generate a plurality of tokens, determining one or more features of the plurality of tokens using term frequency (TF), inverse document frequency (IDF), and code type similarity features, and determining field type, field name, and field value of the one or more of the tokens using named entity recognition (NER).Type: GrantFiled: December 25, 2018Date of Patent: July 19, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Ying Wang, Min Li, Mengyan Lu, Xiaoliang Shi
-
Publication number: 20220222443Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: ApplicationFiled: March 31, 2022Publication date: July 14, 2022Applicant: Microsoft Technology Licensing, LLCInventors: Ying WANG, Min LI, Mengyan LU
-
Patent number: 11321529Abstract: A date extractor disclosed herein allows extracting dates and date ranges from documents. An implementation of the date extractor is implemented using various computer process instructions including scanning a document to generate a plurality of tokens, assigning labels to token using named entity recognition machine to generate a named entity vector, extracting dates from the named entity vector by comparing each of the named entities of the named entity vector to predetermined patterns of dates to generate a date vector, generating a plurality of date pairs from the date vector, and extracting date-ranges by comparing the plurality of date pairs to predetermined patterns of date ranges.Type: GrantFiled: December 25, 2018Date of Patent: May 3, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Ying Wang, Min Li, Mengyan Lu
-
Patent number: 11301633Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: GrantFiled: December 25, 2018Date of Patent: April 12, 2022Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ying Wang, Min Li, Mengyan Lu
-
Publication number: 20210326534Abstract: A date extractor disclosed herein allows extracting dates and date ranges from documents. An implementation of the date extractor is implemented using various computer process instructions including scanning a document to generate a plurality of tokens, assigning labels to token using named entity recognition machine to generate a named entity vector, extracting dates from the named entity vector by comparing each of the named entities of the named entity vector to predetermined patterns of dates to generate a date vector, generating a plurality of date pairs from the date vector, and extracting date-ranges by comparing the plurality of date pairs to predetermined patterns of date ranges.Type: ApplicationFiled: December 25, 2018Publication date: October 21, 2021Inventors: Ying WANG, Min LI, Mengyan LU
-
Publication number: 20210312132Abstract: A coding information extractor disclosed herein uses machine learning approach to extract coding information from documents. An implementation of the coding information extractor is implemented using various computer process instructions including scanning a document to generate a plurality of tokens, determining one or more features of the plurality of tokens using term frequency (TF), inverse document frequency (IDF), and code type similarity features, and determining field type, field name, and field value of the one or more of the tokens using named entity recognition (NER).Type: ApplicationFiled: December 25, 2018Publication date: October 7, 2021Inventors: Ying WANG, Min LI, Mengyan LU, Xiaoliang SHI
-
Publication number: 20210312131Abstract: A technical document scanner disclosed herein determines and categorizes various common issues among a large number of documents. An implementation of the technical document scanner is implemented using various computer process instructions including scanning a technical document to extract content, applying named entity recognition on the extracted content from the technical document to extract named entities, applying relation extraction on the named entities to extract relations between the named entities, and analyzing the relations between the entities to compose lists of high relevance entities for issue checking.Type: ApplicationFiled: December 25, 2018Publication date: October 7, 2021Inventors: Ying WANG, Min LI, Mengyan LU
