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Personalized Financial News Recommendation Algorithm Based on Ontology
2015
Procedia Computer Science
To deal with the challenge of information overload, in this paper, we propose a financial news recommendation algorithm which help users find the articles that are interesting to read. To settle the ambiguity problem, a new presented OF-IDF method is employed to represent the unstructured text data in the form of key concepts, synonyms and synsets which are all stored in the domain ontology. For users, the recommendation algorithm build the profiles based on their behaviors to detect the
doi:10.1016/j.procs.2015.07.151
fatcat:6g3qzreom5gqbdlf6su7n4lc7q