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,...
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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 recommendationalgorithm build the profiles based on their behaviors to detect the genuine interests and predict current interests automatically and in real time by applying the thinking of relevance feedback. Finally, the experiment conducted on a financial news dataset demonstrates that the proposed algorithm significantly outperforms the performance of a traditional recommender. (C) 2015 Published by Elsevier B.V.
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,...
详细信息
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 recommendationalgorithm build the profiles based on their behaviors to detect the genuine interests and predict current interests automatically and in real time by applying the thinking of relevance feedback. Finally, the experiment conducted on a financial news dataset demonstrates that the proposed algorithm significantly outperforms the performance of a traditional recommender.
With the development of Internet technology, the main source of human access to news reporters changes from the original traditional print media to the Internet-based technology news portal. However, with the data tec...
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ISBN:
(纸本)9781479986798
With the development of Internet technology, the main source of human access to news reporters changes from the original traditional print media to the Internet-based technology news portal. However, with the data technology incoming, the information is exploding on the Internet. If the company can provide some news that users are interested in from the data of ocean, the company can gain the favorites of users. This paper is based on links of web structure and Sequential Pattern by analyzing the user's click-stream behavior to obtain the browsing habits and preferences of users. Through using the recommendation technology, it can help predict the interests of users and reduce the users' searching time for news.
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