short-paper

Family History Discovery through Search at Ancestry

Authors:

Azadeh MoghtaderiAuthors Info & Claims

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1389 - 1390

https://doi.org/10.1145/3331184.3331430

Published: 18 July 2019 Publication History

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Abstract

At Ancestry, we apply learning to rank algorithms to a new area to assist our customers in better understanding their family history. The foundation of our service is an extensive and unique collection of billions of historical records that we have digitized and indexed. Currently, our content collection includes 20 billion historical records. The record data consists of birth records, death records, marriage records, adoption records, census records, obituary records, among many others types. It is important for us to return relevant records from diversified record types in order to assist our customers to better understand their family history.

Cited By

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Yang YMiller CJiang PMoghtaderi AHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)A Case Study of Multi-class Classification with Diversified Precision Recall Requirements for Query DisambiguationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401315(1633-1636)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401315

Index Terms

Family History Discovery through Search at Ancestry
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2019

1512 pages

ISBN:9781450361729

DOI:10.1145/3331184

General Chairs:
Benjamin Piwowarski
CNRS - Sorbonne Universite, France
,
Max Chevalier
Universite de Toulouse, CNRS, France
,
Eric Gaussier
Universite Grenoble Alpes, CNRS, France
,
Program Chairs:
Yoelle Maarek
Amazon Research, Israel
,
Jian-Yun Nie
University of Montreal, Canada
,
Falk Scholer
RMIT University, Australia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 July 2019

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Short-paper

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SIGIR '19

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SIGIR

SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 21 - 25, 2019

Paris, France

Acceptance Rates

SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all

Yang YMiller CJiang PMoghtaderi AHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)A Case Study of Multi-class Classification with Diversified Precision Recall Requirements for Query DisambiguationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401315(1633-1636)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401315

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