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

SBIR 第一阶段：电信行业大规模社交网络分析软件服务

• 批准号: 0912640
• 负责人: Nathan Eagle
• 金额: $ 10万
• 依托单位: NDM Labs
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0912640&HistoricalAwards=false
• 关键词: SBIR; Phase; Large; Scale; Social

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.This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

这个小型企业创新研究第一阶段项目将调查使用通话记录数据来帮助电信业更好地为客户服务的潜力。通话记录(谁呼叫谁的记录)可以被视为社交网络，电话号码代表顶点，电话呼叫代表边缘。了解客户的社交网络可能会更好地了解他们的行为和偏好。这个项目的技术挑战既是统计上的，也是计算上的。由于电信行业服务的客户数量非常庞大，他们的数据集非常庞大。例如，在一个月内，一家主要电信提供商记录了2.5亿个电话号码之间的120亿个电话呼叫。技术目标是：1)进一步开发S新生的计算平台，用于超大规模网络分析；2)验证量化运营商营销活动有效性的算法和程序。其目标是创建S软件和服务产品，旨在利用电信公司自己的通话记录来帮助它们更好地价值、服务和留住客户。据信，电信行业忽视了他们拥有的最丰富的数据：通话记录本身。电信运营商不仅拥有关于个人的信息，而且拥有关于他们的呼叫行为、他们的社区以及他们社区的呼叫行为的信息。一家主要运营商通常为超过1500万客户提供服务；考虑到用户的绝对数量，运营商必须依靠统计分析来监测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他们的产品营销，改进他们的客户服务战略，更有效地利用他们的广告预算，并预测“流失”，即停止服务。移动电话市场目前在全球拥有超过40亿用户。虽然过去十年出现了显著增长，但大多数市场已经饱和；移动电话运营商现在正将重点从增长转向高效的客户保留战略。战略的这一转变提供了将数据挖掘技术应用于呼叫日志的机会，呼叫日志是一种到目前为止仍未被行业使用的丰富资源。该奖项由2009年美国复苏和再投资法案(公法111-5)资助。