کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
425636 685799 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Knowle: A semantic link network based system for organizing large scale online news events
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Knowle: A semantic link network based system for organizing large scale online news events
چکیده انگلیسی


• Introducing the semantic link network based system—Knowle.
• Using Knowle for processing health news data.
• Knowle has performed from 2009 to now, which has collected about 35 000 news events and 10 million Webpages.

An explosive growth in the volume, velocity, and variety of the data available on the Internet has been witnessed recently. The data originated from multiple types of sources including mobile devices, sensors, individual archives, social networks, Internet of Things, enterprises, cameras, software logs, health data has led to one of the most challenging research issues of the big data era. In this paper, Knowle—an online news management system upon semantic link network model is introduced. Knowle is a news event centrality data management system. The core elements of Knowle are news events on the Web, which are linked by their semantic relations. Knowle is a hierarchical data system, which has three different layers including the bottom layer (concepts), the middle layer (resources), and the top layer (events). The basic blocks of the Knowle system—news collection, resources representation, semantic relations mining, semantic linking news events are given. Knowle does not require data providers to follow semantic standards such as RDF or OWL, which is a semantics-rich self-organized network. It reflects various semantic relations of concepts, news, and events. Moreover, in the case study, Knowle is used for organizing and mining health news, which shows the potential on forming the basis of designing and developing big data analytics based innovation framework in the health domain.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volumes 43–44, February 2015, Pages 40–50
نویسندگان
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