AncestryAI: A Tool for Exploring Computationally Inferred Family Trees

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Journal Title
Journal ISSN
Volume Title
Conference article in proceedings
Date
2019-01-01
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
257-261
Series
Proceedings of the 26th International Conference on World Wide Web Companion
Abstract
Many people are excited to discover their ancestors and thus decide to take up genealogy. However, the process of finding the ancestors is often very laborious since it involves comparing a large number of historical birth records and trying to manually match the people mentioned in them. We have developed AncestryAI, an open-source tool for automatically linking historical records and exploring the resulting family trees. We introduce a record-linkage method for computing the probabilities of the candidate matches, which allows the users to either directly identify the next ancestor or narrow down the search. We also propose an efficient layout algorithm for drawing and navigating genealogical graphs. The tool is additionally used to crowdsource training and evaluation data so as to improve the matching algorithm. Our objective is to build a large genealogical graph, which could be used to resolve various interesting questions in the areas of computational social science, genetics, and evolutionary studies. The tool is openly available at: http://emalmi.kapsi.fi/ancestryai/.
Description
| openaire: EC/H2020/654024/EU//SoBigData
Keywords
family trees, genealogy, graph drawing, probabilistic modeling, record linkage
Other note
Citation
Malmi , E , Rasa , M & Gionis , A 2019 , AncestryAI: A Tool for Exploring Computationally Inferred Family Trees . in 26th International World Wide Web Conference 2017, WWW 2017 Companion . ACM , Switzerland , pp. 257-261 , International World Wide Web Conference , Perth , Australia , 03/04/2017 . https://doi.org/10.1145/3041021.3054728