An Intelligent Search Platform for Business News

Living in a data driven world, the business news is very crucial for making economic decisions. To help decision makers obtain related business news quickly, two kinds of providers for business news, i.e., the search engine (e.g., Google News) and business portals (e.g., Reuters), are widely used. Though the keyword-based search engine is simple and easy to use, it has relatively low precision of the returned results and cannot directly provide news of particular business domains such as currency and real estate. In contrary, the portals can provide a variety of news of specific business domains, but it is difficult for users to browse since the front page looks so bloated and has many irrelevant ads. To solve the above problems, in this paper we propose and implement a platform named Intelligent Search Platform for Business News (ISPBN). This new platform not only combines the advantages of both search engine and portals, but also provides further analysis to discover the hidden relationships of different business news. To be specific, we incorporate automatic classification technology into the search platform to organize and retrieve business news in different domains. Furthermore, to fast guide users finding diversified and useful news, we construct a dynamic knowledge network graph to display the hidden relationships among news. Finally, we show the performance of our subsystems and present the final user interface of the proposed search platform.

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