基于信息关系提取的社会网络传播形式相似性评价

Susumu Takeuchi, T. Kondoh, M. Akiyoshi, N. Komoda
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引用次数: 1

摘要

由于CGM(消费者生成的媒体),互联网上的信息急剧增加。但是,普通用户发送的这些信息并没有得到系统的管理,特别是对于初学者来说,利用起来比较困难。为了解决这个问题,通过识别不同信息之间的关系,系统应该同时为用户呈现相关的信息。虽然现有的方法如自然语言处理可以评估不同文本的相似度,但最新信息或其他多媒体内容(如图片、电影等)的相似度很难评估。因此,提出利用社交网络中传播形式的相似性来提取信息之间的关系。通过信息传播形式的相似性来评价信息的相似性和互补关系,进行了初步的实验研究。因此,具有许多重复链接的消息往往是相似的,并且期望方向的符合率可以提取信息的互补关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Similarities of Propagation Forms on Social Network for Extracting Relationships of Information
Information on the Internet has been increased extremely because of CGM (consumer generated media). However, such information sent by ordinary users is not managed systematically, so utilizing it is difficult especially for the beginners. To solve this issue, by identifying relationships between different information, a system should present related information for the users simultaneously. Although the existing methods such as natural language processing can evaluate the similarities of different texts, latest information or other multimedia contents, e.g., pictures, movies, etc, are difficult to evaluate. Therefore, similarities of propagation forms on a social network are proposed to utilize for extracting relationships of information. A preliminary experiment was carried out for evaluating relationships of similarity and complement can be obtained by the similarities of propagation forms of information. As a result, the messages that have many duplicate links tend to be similar, and the rate of coincidence of the directions is expected to extract complementary relationships of information.
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