MX2020011102A - Clasificacion de elementos en la genealogia y recomendacion. - Google Patents

Clasificacion de elementos en la genealogia y recomendacion.

Info

Publication number
MX2020011102A
MX2020011102A MX2020011102A MX2020011102A MX2020011102A MX 2020011102 A MX2020011102 A MX 2020011102A MX 2020011102 A MX2020011102 A MX 2020011102A MX 2020011102 A MX2020011102 A MX 2020011102A MX 2020011102 A MX2020011102 A MX 2020011102A
Authority
MX
Mexico
Prior art keywords
genealogy
hints
method includes
feature
hint
Prior art date
Application number
MX2020011102A
Other languages
English (en)
Inventor
Tyler Folkman
Peng Jiang
Tsung- Nan Liu
Yen- Yun Yu
Ruhan Wang
Jack Reese
Azadeh Moghtaderi
Original Assignee
Ancestry Com Operations Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ancestry Com Operations Inc filed Critical Ancestry Com Operations Inc
Publication of MX2020011102A publication Critical patent/MX2020011102A/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/901—Indexing; Data structures therefor; Storage structures
    • G06F16/9027—Trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/211—Selection of the most significant subset of features
    • G06F18/2113—Selection of the most significant subset of features by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G06F18/2148—Generating training patterns; Bootstrap methods, e.g. bagging or boosting characterised by the process organisation or structure, e.g. boosting cascade
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
    • G06F18/2178—Validation; Performance evaluation; Active pattern learning techniques based on feedback of a supervisor
    • 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
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Databases & Information Systems (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

Los sistemas y métodos para entrenar un modelo de clasificación de aprendizaje automático (ML) para clasificar las sugerencias de genealogía se describen en el presente. Un método incluye recuperar una pluralidad de sugerencias de genealogía para una persona objetivo, en que la pluralidad de sugerencias de genealogía corresponde a un elemento de genealogía y tiene un tipo de sugerencia de una pluralidad de tipos de sugerencia; El método incluye generar, para la pluralidad de sugerencias de genealogía, un vector de características que tiene una pluralidad de valores de características, el vector de características está incluido en una pluralidad de vectores de características; El método incluye extender la pluralidad de vectores de características al menos un valor de característica adicional según el número de características de uno o más de los otros tipos de sugerencias de la pluralidad de tipos de sugerencias. El método incluye entrenar el modelo de clasificación ML usando la pluralidad extendida de vectores de características y etiquetas proporcionadas por el usuario.
MX2020011102A 2018-05-08 2019-05-08 Clasificacion de elementos en la genealogia y recomendacion. MX2020011102A (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201862668269P 2018-05-08 2018-05-08
US201862668795P 2018-05-08 2018-05-08
PCT/US2019/031351 WO2019217574A1 (en) 2018-05-08 2019-05-08 Genealogy item ranking and recommendation

Publications (1)

Publication Number Publication Date
MX2020011102A true MX2020011102A (es) 2020-11-13

Family

ID=68463727

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2020011102A MX2020011102A (es) 2018-05-08 2019-05-08 Clasificacion de elementos en la genealogia y recomendacion.

Country Status (8)

Country Link
US (2) US11551025B2 (es)
EP (1) EP3791327A4 (es)
AU (1) AU2019265655B2 (es)
CA (1) CA3095636A1 (es)
IL (1) IL277824A (es)
MX (1) MX2020011102A (es)
NZ (1) NZ768470A (es)
WO (1) WO2019217574A1 (es)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11544630B2 (en) * 2018-10-15 2023-01-03 Oracle International Corporation Automatic feature subset selection using feature ranking and scalable automatic search
US11061902B2 (en) 2018-10-18 2021-07-13 Oracle International Corporation Automated configuration parameter tuning for database performance
US11727284B2 (en) * 2019-12-12 2023-08-15 Business Objects Software Ltd Interpretation of machine learning results using feature analysis
CN111352229B (zh) * 2020-04-07 2021-10-08 华中科技大学 一种虚拟多平面成像系统及方法
CN113779116B (zh) * 2021-09-10 2023-07-11 平安科技（深圳）有限公司 对象排序方法、相关设备及介质
US20230325373A1 (en) * 2022-03-15 2023-10-12 Ancestry.Com Operations Inc. Machine-learning based automated document integration into genealogical trees

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1669896A3 (en) * 2004-12-03 2007-03-28 Panscient Pty Ltd. A machine learning system for extracting structured records from web pages and other text sources
US7844609B2 (en) * 2007-03-16 2010-11-30 Expanse Networks, Inc. Attribute combination discovery
US8856082B2 (en) * 2012-05-23 2014-10-07 International Business Machines Corporation Policy based population of genealogical archive data
US20170213127A1 (en) * 2016-01-24 2017-07-27 Matthew Charles Duncan Method and System for Discovering Ancestors using Genomic and Genealogic Data
US11113609B2 (en) * 2016-04-07 2021-09-07 Ancestry.Com Operations Inc. Machine-learning system and method for identifying same person in genealogical databases

Also Published As

Publication number Publication date
AU2019265655B2 (en) 2024-06-13
US20190347511A1 (en) 2019-11-14
US20230161819A1 (en) 2023-05-25
NZ768470A (en) 2020-10-30
CA3095636A1 (en) 2019-11-14
EP3791327A1 (en) 2021-03-17
AU2019265655A1 (en) 2020-10-15
IL277824A (en) 2020-11-30
WO2019217574A1 (en) 2019-11-14
EP3791327A4 (en) 2022-01-12
US11551025B2 (en) 2023-01-10
US11720632B2 (en) 2023-08-08

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