Guided Diverse Concept Miner (GDCM): Uncovering Relevant Constructs for Managerial Insights from Text

IF 5 3区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Information Systems Research Pub Date : 2024-05-10 DOI:10.1287/isre.2020.0494

Dokyun “DK” Lee, Zhaoqi “ZQ” Cheng, Chengfeng Mao, Emaad Manzoor

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引用次数: 0

Abstract

The Guided Diverse Concept Miner (GDCM) is an innovative deep learning algorithm tailored for the extraction of managerially relevant concepts from textual data, emphasizing the autonomy in discovering insights without predefined labels or guidance. This tool stands out by embedding words, documents, and concepts within the same vector space, which simplifies the interpretation of unearthed concepts and ensures their alignment with managerial outcomes. Central to GDCM’s methodology is its capacity to focus on concepts that are highly correlated with user-specified managerial outcomes, termed guiding variables, thereby enhancing the relevance and application of extracted insights in decision-making processes. The algorithm’s design inherently promotes the diversity of the recovered concepts, ensuring a broad spectrum of insights. Through practical application in analyzing customer reviews related to online purchases, GDCM not only identified key concepts influencing conversion rates but also validated its findings against established theories and prior causal research. This validation underscores GDCM’s utility in generating actionable, diverse insights tailored to specific managerial contexts, marking a significant advancement in how businesses leverage textual data for strategic decisions.

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引导式多样化概念挖掘器（GDCM）：从文本中发现相关结构，获得管理启示

引导式多样化概念挖掘器（GDCM）是一种创新的深度学习算法，专为从文本数据中提取与管理相关的概念而定制，强调在没有预定义标签或引导的情况下自主发现见解。该工具通过将单词、文档和概念嵌入同一向量空间而脱颖而出，从而简化了对所发现概念的解释，并确保其与管理结果相一致。GDCM 方法论的核心在于，它能够将重点放在与用户指定的管理结果（称为指导变量）高度相关的概念上，从而提高了提取的见解在决策过程中的相关性和应用性。该算法的设计从本质上促进了回收概念的多样性，确保了洞察力的广泛性。通过分析与在线购买相关的客户评论的实际应用，GDCM 不仅确定了影响转换率的关键概念，还根据既定理论和先前的因果研究验证了其发现。这一验证强调了 GDCM 在生成针对特定管理环境的可操作的多样化见解方面的实用性，标志着企业在如何利用文本数据进行战略决策方面取得了重大进展。

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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来源期刊

Information Systems Research Multiple-

CiteScore

9.10

自引率

8.20%

发文量

120

期刊介绍： ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.