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UNSTRUCTURED DATA ANALYTICS, AI, AND OR/MS

Learning to Correlate Accounts Across Online Social Networks: An Embedding-Based Approach

Published Online:

INFORMS Journal on Computing

    Abstract
    Cross-site account correlation correlates users who have multiple accounts but the same identity across online social networks (OSNs). Being able to identify cross-site users is important for a variety of applications in social networks, security, and ...
Search Personalization Using Machine Learning

Published Online:

Management Science

    Abstract
    Firms typically use query-based search to help consumers find information/products on their websites. We consider the problem of optimally ranking a set of results shown in response to a query. We propose a personalized ranking mechanism based on a user’s ...
Don’t Mention It? Analyzing User-Generated Content Signals for Early Adverse Event Warnings

Published Online:

Information Systems Research

    Abstract
    With greater impetus on broad postmarket surveillance, the Voice of the Customer (VoC) has emerged as an important source of information for understanding consumer experiences and identifying potential issues. In organizations, risk management groups are ...
A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections

Published Online:

Information Systems Research

    Abstract
    From an upset stomach to a life-threatening foodborne illness, getting sick is all too common after eating in restaurants. Although health inspection programs for restaurants are designed to protect consumers, such inspections typically occur sporadically,...
A Semantic Approach for Estimating Consumer Content Preferences from Online Search Queries

Published Online:

Marketing Science

    Abstract
    We extend latent Dirichlet allocation by introducing a topic model, hierarchically dual latent Dirichlet allocation, the output of which provides a basis for estimating consumers’ content preferences on the fly from their search queries.
Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining

Published Online:

Information Systems Research

    Abstract
    The application of predictive data mining techniques in information systems research has grown in recent years, likely because of their effectiveness and scalability in extracting information from large amounts of data. A number of scholars have sought to ...
Artificial Intelligence and Algorithmic Bias: Source, Detection, Mitigation, and Implications

Published Online:

INFORMS TutORials in Operations Research

    Abstract
    Artificial intelligence and machine learning (ML) algorithms are widely used throughout our economy in making decisions that have far-reaching impacts on employment, education, access to credit, and other areas. Initially considered neutral and fair, ML ...
Special Edition of Resoundingly Human Featuring Congressman Jerry McNerney, PhD, Co-Chair of the Congressional Artificial Intelligence Caucus

Jerry McNerney

Published Online: June 30, 2020
INFORMS Resoundingly Human

OR/MS Today logo
Ensuring INFORMS’ place in fast-moving AI race
Ramayya Krishnan

Published Online: March 27, 2019

OR/MS Today

TutORial: Coalescing Data and Decision Sciences for Analytics

Suvrajeet Sen, Yunxiao Deng, and Junyi Liu

Published Online: November 25, 2018
INFORMS YouTube Channel

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Teaching artificial intelligence to do no harm
Joseph Byrum

Published Online: August 31, 2020

Analytics

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Ensuring Responsible Use of Artificial Intelligence
Anupam Datta

Published Online: October 22, 2020

Analytics

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The Intelligent Enterprise: Future of work: Strong AI and what it means for your job (and your company)
Joseph Byrum

Published Online: June 18, 2020

OR/MS Today

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