Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: News companies produce news items that describe events that happen in the world. These news items usually contain mentions to persons, organizations, locations and other types of  named entities  that are involved in the events being described. These named entities may have an ambiguous meaning, which impacts the performance of free-text information retrieval systems.  the IdentityRank algorithm, designed to address the problem of named entity disambiguation in news items, is described. It has been developed as part of the EU-funded project  News Engine b Services  (NEWS) and is specifically designed to operate within the editorial environment of a news company. The algorithm was implemented and evaluated using several corpora of actual news items, achieving an average accuracy of around 96%.
['Norberto Fernández', 'Jesús Arias Fisteus', 'Luis Sánchez', 'Gonzalo Miguel López']
I am writing a research paper on a idea IdentityRank: Named entity disambiguation in the news domain
[{"from": "human", "value": "I am writing a research paper on a idea IdentityRank: Named entity disambiguation in the news domain"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: News companies produce news items that describe events that happen in the world. These news items usually contain mentions to persons, organizations, locations and other types of  named entities  that are involved in the events being described. These named entities may have an ambiguous meaning, which impacts the performance of free-text information retrieval systems.  the IdentityRank algorithm, designed to address the problem of named entity disambiguation in news items, is described. It has been developed as part of the EU-funded project  News Engine b Services  (NEWS) and is specifically designed to operate within the editorial environment of a news company. The algorithm was implemented and evaluated using several corpora of actual news items, achieving an average accuracy of around 96%."}]