Abstract

As interest in family history research increases, greater numbers of amateurs are participating in genealogy. However, finding sources that provide useful information on individuals in genealogical research is often an overwhelming task, even for experts. Many tools assist genealogists in their work, including many computer-based systems. Prior to this work, recommender systems had not yet been applied to genealogy, though their ability to navigate patterns in large amounts of data holds great promise for the genealogical domain. We create the Family History Source Recommender System to mimic human behavior in locating sources of genealogical information. The recommender system is seeded with existing source data from the FamilySearch database. The typical recommender systems algorithms are not designed for family history work, so we adjust them to fit the problem. In particular, recommendations are created for deceased individuals, with multiple users being able to consume the same recommendations. Additionally, our similarity computation takes into account as much information about individuals as possible in order to create connections that would otherwise not exist. We use offline n-fold cross-validation to validate the results. The system provides results with high accuracy.

Degree

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

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