Efficient On/Off-Line Query Pre-processing for Telecom Social Streaming Data

Social media are primarily generated and transmitted over Internet from mobile based applications/tools, e.g., Flickr, YouTube, etc., for sharing and discussing information among people. Most of these applications are putting forward from desktop to mobile client side, since smart devices are growing by leaps and bounds, and they tend to take fully advantage of tunnels that telecom companies offer. Like any other industries, telecom operators also face tough competitions from "over-the-top"(OTT) service providers. Therefore, they are prone to bring in Big Data analytical techniques to take fully use of streaming data they possessed. To this end, in this paper, we propose a novel query system specifically designed for telecom networks that integrates both online pre-processing and offline analytics for social streaming data. Furthermore, our framework is able to speedup the query processing by creating and parsing an Abstract Syntax Tree (AST). Extensive experimental results show the effectiveness of proposed and implemented system.

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