BR112018013550A2 - identificação de entidades utilizando um modelo de aprendizado profundo - Google Patents
identificação de entidades utilizando um modelo de aprendizado profundoInfo
- Publication number
- BR112018013550A2 BR112018013550A2 BR112018013550A BR112018013550A BR112018013550A2 BR 112018013550 A2 BR112018013550 A2 BR 112018013550A2 BR 112018013550 A BR112018013550 A BR 112018013550A BR 112018013550 A BR112018013550 A BR 112018013550A BR 112018013550 A2 BR112018013550 A2 BR 112018013550A2
- Authority
- BR
- Brazil
- Prior art keywords
- entities
- learning model
- deep learning
- entity identification
- user
- Prior art date
Links
- 238000013136 deep learning model Methods 0.000 title abstract 4
- 238000000034 method Methods 0.000 abstract 1
- 230000006855 networking Effects 0.000 abstract 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computing Systems (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- General Business, Economics & Management (AREA)
- Biophysics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biomedical Technology (AREA)
- Computational Linguistics (AREA)
- Molecular Biology (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Information Transfer Between Computers (AREA)
- Machine Translation (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
em uma modalidade, um método inclui acessar um primeiro conjunto de entidades, com o qual um usuário interagiu, e um segundo conjunto de entidades em um sistema de rede social. um primeiro conjunto de representações vetoriais do primeiro conjunto de entidades é determinado usando um modelo de aprendizado profundo. uma entidade-alvo é selecionada a partir do primeiro conjunto de entidades, e a representação vetorial da entidade-alvo é removida do primeiro conjunto. as representações vetoriais restantes no primeiro conjunto são combinadas para determinar uma representação vetorial do usuário. um segundo conjunto de representações vetoriais do segundo conjunto de entidades é determinado usando o modelo de aprendizado profundo. os escores de similaridade são computados entre o usuário e cada uma dentre a entidade-alvo e as entidades no segundo conjunto de entidades. as representações vetoriais de entidades no segundo conjunto de entidades são atualizadas com base nos escores de similaridade usando o modelo de aprendizado profundo.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/984,956 US10402750B2 (en) | 2015-12-30 | 2015-12-30 | Identifying entities using a deep-learning model |
| PCT/US2016/018367 WO2017116488A1 (en) | 2015-12-30 | 2016-02-18 | Identifying entities using a deep-learning model |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| BR112018013550A2 true BR112018013550A2 (pt) | 2018-12-04 |
Family
ID=59225437
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| BR112018013550A BR112018013550A2 (pt) | 2015-12-30 | 2016-02-18 | identificação de entidades utilizando um modelo de aprendizado profundo |
Country Status (10)
| Country | Link |
|---|---|
| US (2) | US10402750B2 (pt) |
| JP (1) | JP6689389B2 (pt) |
| KR (1) | KR20180099812A (pt) |
| CN (1) | CN108604315B (pt) |
| AU (1) | AU2016380683A1 (pt) |
| BR (1) | BR112018013550A2 (pt) |
| CA (1) | CA3009157A1 (pt) |
| IL (1) | IL260165A (pt) |
| MX (1) | MX2018008104A (pt) |
| WO (1) | WO2017116488A1 (pt) |
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-
2015
- 2015-12-30 US US14/984,956 patent/US10402750B2/en active Active
-
2016
- 2016-02-18 CA CA3009157A patent/CA3009157A1/en not_active Abandoned
- 2016-02-18 AU AU2016380683A patent/AU2016380683A1/en not_active Abandoned
- 2016-02-18 CN CN201680079586.2A patent/CN108604315B/zh active Active
- 2016-02-18 BR BR112018013550A patent/BR112018013550A2/pt not_active Application Discontinuation
- 2016-02-18 MX MX2018008104A patent/MX2018008104A/es unknown
- 2016-02-18 WO PCT/US2016/018367 patent/WO2017116488A1/en active Application Filing
- 2016-02-18 JP JP2018534041A patent/JP6689389B2/ja active Active
- 2016-02-18 KR KR1020187021851A patent/KR20180099812A/ko not_active Application Discontinuation
-
2018
- 2018-06-20 IL IL260165A patent/IL260165A/en unknown
-
2019
- 2019-07-15 US US16/512,128 patent/US20190340538A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| KR20180099812A (ko) | 2018-09-05 |
| CA3009157A1 (en) | 2017-07-06 |
| MX2018008104A (es) | 2018-08-23 |
| IL260165A (en) | 2018-07-31 |
| JP2019506664A (ja) | 2019-03-07 |
| CN108604315B (zh) | 2022-01-11 |
| CN108604315A (zh) | 2018-09-28 |
| US10402750B2 (en) | 2019-09-03 |
| AU2016380683A1 (en) | 2018-08-16 |
| WO2017116488A1 (en) | 2017-07-06 |
| JP6689389B2 (ja) | 2020-04-28 |
| US20170193390A1 (en) | 2017-07-06 |
| US20190340538A1 (en) | 2019-11-07 |
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