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Compressing SMS Messages for Lowering Communication Costs in Rural Africa 压缩短信以降低非洲农村的通信成本
Pub Date : 2016-11-18 DOI: 10.1145/3001913.3006636
Roshan Ramankutty, S. Figueira
Traditional compression algorithms appear to be largely unsuccessful with regards to short strings. In developing countries without connectivity to the web and data infrastructure, SMS remains one of the few ways of handling text-based information. With SMS service providers typically charging for SMS messages on a per-message basis, there exists a need to provide some form of short string compression, specifically with regards to highly structured data. This paper seeks to answer whether or not dictionary structures produce better results of compression than traditional algorithms with respect to highly structured data. To determine whether or not this approach would work, we developed a configurable parser that, when properly configured, accepts the various forms of structured data as provided by the client. We then compare the results to traditional compression mechanisms and measure the success.
对于短字符串,传统的压缩算法似乎在很大程度上是不成功的。在没有网络连接和数据基础设施的发展中国家,短信仍然是处理基于文本的信息的少数几种方式之一。由于SMS服务提供商通常以每条消息为基础对SMS消息收费,因此需要提供某种形式的短字符串压缩,特别是对于高度结构化的数据。本文试图回答,对于高度结构化的数据,字典结构是否比传统算法产生更好的压缩结果。为了确定这种方法是否有效,我们开发了一个可配置的解析器,在正确配置后,它可以接受客户端提供的各种形式的结构化数据。然后,我们将结果与传统压缩机制进行比较,并衡量其成功程度。
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引用次数: 0
Proceedings of the 7th Annual Symposium on Computing for Development 第七届计算促进发展年会论文集
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引用次数: 0
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Proceedings of the 7th Annual Symposium on Computing for Development
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