Learning Resources Based on Analysis of Digital Newspaper Data

被引:0
作者
Sarasa Cabezuelo, Antonio [1 ]
机构
[1] Univ Complutense Madrid, C Prof Garcia Santesmases 9, E-28040 Madrid, Spain
来源
ADVANCES ON P2P, PARALLEL, GRID, CLOUD AND INTERNET COMPUTING (3PGCIC-2017) | 2018年 / 13卷
关键词
SENTIMENTAL ANALYSIS; NETWORKS;
D O I
10.1007/978-3-319-69835-9_57
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Digital newspapers are a source of information with very particular characteristics such as: they collect heterogeneous information on a wide variety of subjects, they can be considered truthful sources of information, generally their html pages have a regular structure, they are maintained permanently archived, they are quickly indexed by the main search engines, and the format of their URLs is regular,. This article describes a work developed in the context of a final degree project from the School of Computer Science at the Complutense University of Madrid. The objective of the work was to analyze the problems related to recover the information of an online newspaper, analyze which tools can be used to extract information, and how the retrieved information can be exploited in order to generate value-added services. To illustrate the results of this work, it has developed a prototype application in Python.
引用
收藏
页码:611 / 621
页数:11
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