SBIR Phase IB: Large-Scale Social Network Analysis Software Services for the Telecommunications Industry

SBIR IB 阶段：电信行业大规模社交网络分析软件服务

• 批准号: 1003676
• 负责人: Nathan Eagle
• 金额: $ 5万
• 依托单位: NDM Labs
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1003676&HistoricalAwards=false
• 关键词: SBIR; Phase; IB; Large; Scale

This Small Business Innovation Research Phase I project will investigate the potential of using call log data to assist the telecommunications industry in better serving its customers. Call logs (records of who called whom) can be viewed as social networks, with phone numbers representing vertices and phone calls representing edges. Understanding a customer's social network can potentially provide a much better understanding of their behavior and preference. The technical challenge of this project is both statistical and computational. As the telecommunications industry serves a very large number of customers, their data sets are massive. In the single month, for example, a major telecommunications provider logged 12 billion phone calls made between 250 million phone numbers. The technical objectives are: 1) to further develop s nascent computational platform for extremely large-scale network analysis, and 2) to validate algorithms and procedures, which quantify the effectiveness of operator marketing campaigns. The goal is to create s software-and-services product offering designed to leverage telecom companies' own call logs to help them better value, serve and retain their customers. It is believed that the telecommunications industry has overlooked the richest data in their possession: the call logs themselves. A telecommunications operator has information not just on individuals, but on their calling behavior, their communities, and their communities' calling behavior. A single major operator typically serves over 15 million customers; given the sheer number of subscribers, operators must rely on statistical analysis to monitor customer satisfaction and to anticipate customer needs. Enhancing this knowledge will allow them to optimize their product marketing, to improve their customer care strategies, to more efficiently use their advertising budget, and to anticipate "churn," the cessation of service. The mobile phone market currently reaches over 4 billion subscribers globally. While the past decade has seen significant growth, most markets have reached saturation; mobile phone operators now are shifting their focus from growth to efficient customer retention strategies. This shift in strategy presents an opportunity to apply data mining techniques to call logs, a rich resource that to date has remained unused by the industry.

这个小型企业创新研究阶段I项目将研究使用呼叫日志数据帮助电信行业更好地为客户提供服务的潜力。呼叫日志（谁打电话给谁）可以看作是社交网络，其电话号码代表代表边缘的顶点和电话。了解客户的社交网络可能会更好地了解其行为和偏好。该项目的技术挑战既是统计又是计算。由于电信行业为大量客户提供服务，因此他们的数据集很大。例如，在单个月中，一家主要的电信提供商记录了120亿个电话在2.5亿个电话号码之间。技术目标是：1）进一步开发出较大的计算平台，以进行极大的网络分析，以及2）验证算法和程序，以量化运营商营销活动的有效性。目标是创建旨在利用电信公司自己的呼叫日志来帮助他们更好的价值，服务和保留客户的Software-Services产品产品。据信，电信行业忽略了他们拥有的最丰富数据：呼叫本身。电信运营商不仅有有关个人的信息，而且还提供有关其呼唤行为，社区和社区的呼叫行为的信息。一个主要的运营商通常为超过1500万客户提供服务；鉴于订户数量庞大，运营商必须依靠统计分析来监控客户满意度并预测客户需求。增强这些知识将使他们能够优化其产品营销，改善其客户服务策略，更有效地使用广告预算，并预测服务的“流失”。目前，手机市场在全球范围内达到超过40亿订户。尽管过去十年的增长显着，但大多数市场已经饱和。手机运营商现在将重点从增长转移到有效的客户保留策略。战略的这种转变为应用数据挖掘技术呼叫日志提供了机会，这是迄今为止该行业未使用的丰富资源。