The System Design and Development for Transforming Digital News to Linked Open Data
| Autor: | Yan-Wun Lin, 林彥文 |
|---|---|
| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 With the rising of social media and digital news, it greatly changed the habit of people watching news and discussing news topics. People browse news through digital news platform as the main source and discuss news issues on social network. However, due to digital news platforms provided by Taiwanese news publishers using traditional web pages (HTML), the presentation of news pages doesn''t provide the semantics (Metadata) that can be parsed by computer. As a result, the web resources relating to the news contents cannot be linked to the news. In order to solve this problem in digital news, we design a system which transforms digital news data to the Resource Description Framework (RDF). The proposed system recognizes the entities, person and organization, in digital news by the named entity recognition technique then and links them to the knowledge bases such as Wikipedia or DBpedia. Our system also solves the synonym problem when users search news about specific object. In addition, it provides SPARQL query of semantic web to enhance search capability. People not only browse news through digital news platform but discuss news issues on social network. Our system transforms digital news platform data to linked data. Besides, we use Convolutional Neural Networks(CNN) classifier to analyze degree of relatedness between news opinions from social network and entities in the news. By the means, we allow users to search the opinion about specific entity. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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