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- W3168396738 abstract "With English being considered as a universal language of communication and interaction, the study of the words that sound the same but spell differently has become an extensive area of research. In the context of social networks, people names can have different spellings yet the same pronunciation (i.e., homophonic names). Chris and Kris, John and Jon, as well as Justin and Justyn are some examples of these homophonic names. When exploring historical records, there may be situations in which two different entries correspond to the same individual, and the only difference in the two entries might be the spelling of the individual's name. Similar situations occur when individual's names are translated from their native language to another language. In this paper, we present a solution to identify the right person in social networks. The solution incorporates graph theory and linear algebra, and makes good use of double metaphone codes to measure the phonetic distance between two names. Based on the measured phonetic distance, homophonic names are grouped into the same cluster. This phonetic distance-based clustering helps to identify the right person in social networks." @default.
- W3168396738 created "2021-06-22" @default.
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- W3168396738 date "2020-12-01" @default.
- W3168396738 modified "2023-10-18" @default.
- W3168396738 title "Identifying the Right Person in Social Networks with Double Metaphone Codes" @default.
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- W3168396738 doi "https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00125" @default.
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