Analytics of Similar-Sounding Names from the Web with Phonetic Based Clustering

With advancements in modern technology in the current era, very large volumes of big data have been generated and collected in numerous real-life applications. These have formed a connected world comprising webs of agents, data, people, things and trust. Some of these webs have also emerged in health and smart living. As valuable information and knowledge is embedded in these rich sets of webs, web intelligence is in demand. In this paper, we focus a data science task of web content mining. In particular, we conduct big web data analytics to cluster similar-sounding names based on their phonemes. Our phonetic based clustering groups similar-sounding names together, which helps users deal with name disambiguation problems by identifying web records on the same person but with multiple similar-sounding names.