Web Text-based Network Industry Classifications: Preliminary Results

Eric Heiden, Gerard Hoberg, Craig A. Knoblock, Palak Modi, G. Phillips, Gaurangi Raul, Pedro A. Szekely
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引用次数: 4

Abstract

Studies of market structure and product market competition are important in many disciplines, such as economics, finance, accounting and management. Reliable data for such studies is easily available for public firms (e.g., 10-K filings), but no reliable data exists for private firms. In this work we propose to mine the Internet Archive Wayback Machine, a digital archive of the World Wide Web, to build a database of 300,000 companies to support analyses of market structure, product market competition, and innovation. The goal of the WTNIC project is to download pages from the archive to build a profile for each company, and to use machine learning techniques to define similarity between companies based on similarity of their product and service offerings. This paper describes the challenges that must be overcome, our approach to overcome these challenges, and some preliminary results.
基于Web文本的网络行业分类:初步结果
市场结构和产品市场竞争的研究在许多学科中都很重要,如经济学、金融学、会计学和管理学。这类研究的可靠数据很容易为上市公司获得(例如,10-K文件),但没有可靠的数据存在于私营公司。在这项工作中,我们建议挖掘互联网档案时光机,一个万维网的数字档案,建立一个包含30万家公司的数据库,以支持对市场结构、产品市场竞争和创新的分析。WTNIC项目的目标是从存档中下载页面,为每个公司构建概要,并使用机器学习技术根据公司产品和服务的相似性来定义公司之间的相似性。本文描述了必须克服的挑战,我们克服这些挑战的方法,以及一些初步的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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