TK-Indexing : An Indexing Method for SNS Data Based on NoSQL

Hyungseop Shim, Jeong-Dong Kim, Kwangsoo Seol, D. Baik
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Abstract

Currently, contents generated by SNS services are increasing exponentially, as the number of SNS users increase. The SNS is commonly used to post personal status and individual interests. Also, the SNS is applied in socialization, entertainment, product marketing, news sharing, and single person journalism. As SNS services became available on smart phones, the users of SNS services can generate and spread the social issues and controversies faster than the traditional media. The existing indexing methods for web contents have limitation in terms of real-time indexing for SNS contents, as they usually focus on diversity and accuracy of indexing. To overcome this problem, there are real-time indexing techniques based on RDBMSs. However, these techniques suffer from complex indexing procedures and reduced indexing targets. In this regard, we introduce the TK-Indexing method to improve the previous indexing techniques. Our method indexes the generation time of SNS contents and keywords by way of NoSQL to indexing SNS contents in real-time.
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tk -索引:一种基于NoSQL的SNS数据索引方法
目前,随着SNS用户的增加,SNS服务产生的内容呈指数级增长。社交网络通常用于发布个人状态和个人兴趣。此外,社交网络还应用于社交、娱乐、产品营销、新闻分享和单人新闻等领域。随着社交网络服务在智能手机上的普及,社交网络用户可以比传统媒体更快地产生和传播社会问题和争议。现有的网络内容索引方法注重索引的多样性和准确性,在SNS内容的实时索引方面存在一定的局限性。为了克服这个问题,出现了基于rdbms的实时索引技术。然而,这些技术的缺点是索引过程复杂,索引目标减少。在这方面,我们引入了tk -标引方法来改进以前的标引技术。该方法通过NoSQL对SNS内容和关键词的生成时间进行索引,实现SNS内容的实时索引。
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