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Searching for a person's name is a common online activity. However, Websearch engines provide few accurate results to queries containing names. Incontrast to a general word which has only one correct spelling, there areseveral legitimate spellings of a given name. Today, most techniques used tosuggest synonyms in online search are based on pattern matching and phoneticencoding, however they often perform poorly. As a result, there is a need foran effective tool for improved synonym suggestion. In this paper, we propose arevolutionary approach for tackling the problem of synonym suggestion. Ournovel algorithm, GRAFT, utilizes historical data collected from genealogywebsites, along with network algorithms. GRAFT is a general algorithm thatsuggests synonyms using a graph based on names derived from digitized ancestralfamily trees. Synonyms are extracted from this graph, which is constructedusing generic ordering functions that outperform other algorithms that suggestsynonyms based on a single dimension, a factor that limits their performance.We evaluated GRAFT's performance on three ground truth datasets of forenamesand surnames, including a large-scale online genealogy dataset with over 16million profiles and more than 700,000 unique forenames and 500,000 surnames.We compared GRAFT's performance at suggesting synonyms to 10 other algorithms,including phonetic encoding, string similarity algorithms, and machine and deeplearning algorithms. The results show GRAFT's superiority with respect to bothforenames and surnames and demonstrate its use as a tool to improve synonymsuggestion.

It Runs in the Family: Searching for Synonyms Using Digitized Family Trees