Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In research and application, social networks are increasingly extracted from relationships inferred by name collocations in text-based documents. Despite the fact that names represent real entities, names are not unique identifiers and it is often unclear when two name observations correspond to the same underlying entity. One confounder stems from ambiguity, in which the same name correctly references multiple entities. Prior name disambiguation methods measured similarity beten two names as a function of their respective documents. ,  propose an alternative similarity metric based on the probability of walking from one ambiguous name to another in a random walk of the social network constructed from all documents.  experimentally validate our model on actor-actor relationships derived from the Internet Movie Database. Using a global similarity threshold,  demonstrate random walks achieve a significant increase in disambiguation capability in comparison to prior models.
['Bradley Malin', 'Edoardo M. Airoldi', 'Kathleen M. Carley']
I am writing a research paper on a idea A Network Analysis Model for Disambiguation of Names in Lists
[{"from": "human", "value": "I am writing a research paper on a idea A Network Analysis Model for Disambiguation of Names in Lists"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In research and application, social networks are increasingly extracted from relationships inferred by name collocations in text-based documents. Despite the fact that names represent real entities, names are not unique identifiers and it is often unclear when two name observations correspond to the same underlying entity. One confounder stems from ambiguity, in which the same name correctly references multiple entities. Prior name disambiguation methods measured similarity beten two names as a function of their respective documents. ,  propose an alternative similarity metric based on the probability of walking from one ambiguous name to another in a random walk of the social network constructed from all documents.  experimentally validate our model on actor-actor relationships derived from the Internet Movie Database. Using a global similarity threshold,  demonstrate random walks achieve a significant increase in disambiguation capability in comparison to prior models."}]