Complex Problem Solving: Identity Matching Based on Social Contextual Information
Xu, Jennifer, Wang, G. Alan, Li, Jiexun, Chau, Michael, Journal of the Association for Information Systems
Complex problems like drug crimes often involve a large number of variables interacting with each other. A complex problem may be solved by breaking it into parts (i.e., sub-problems), which can be tackled more easily. The identity matching problem, for example, is a part of the problem of drug and other types of crimes. It is often encountered during crime investigations when a single criminal is represented by multiple identity records in law enforcement databases. Because of the discrepancies among these records, a single criminal may appear to be different people. Following Enid Mumford's three-stage problem solving framework, we design a new method to address the problem of criminal identity matching for fighting drug-related crimes. Traditionally, the complexity of criminal identity matching was reduced by treating criminals as isolated individuals who maintain certain personal identities. In this research, we recognize the intrinsic complexity of the problem and treat criminals as interrelated rather than isolated individuals. In other words, we take into consideration of the social relationships between criminals during the matching process. We study not only the personal identities but also the social identities of criminals. Evaluation results were quite encouraging and showed that combining social features with personal features could improve the performance of criminal identity matching. In particular, the social features become more useful when data contain many missing values for personal attributes.
Keywords: Complex problems, design science, identity matching, social contextual information.
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Modern society is increasingly facing various complex problems that are "pervasive, spreading unhindered into regions, countries, and economic activities which seem powerless to resist the invasion" (Mumford, 1998, p. 447). Globalization, for example, is such a complex problem that, while bringing numerous opportunities to organizations, has also brought substantial challenges and pressure. Defining complex problems seems to be a good starting point for solving them; however, there has not been a widely accepted definition (Gray, 2002; Quesada et al., 2005). Funke (1991) suggested that complex problems can be understood by contrasting them with simple problems, which can be solved by simple reasoning and pure logic (Quesada et al., 2005), and that they can be characterized by their intransparency, polytely (from the Greek words poly telos meaning many goals), complexity, connectivity of variables, dynamic, and time-delayed effects. In other words, the defining characteristics of complex problems are a large number of variables (complexity) that interact in a nonlinear fashion (connectivity), changing over time (dynamic and time-dependent), and to achieve multiple goals (polytely).
One of the two examples that Mumford used to illustrate complex problem solving (Mumford, 1998; Mumford, 1999) is drug crimes, which clearly have all these features: a large number of people interact and cooperate frequently; they play different roles and spread across different countries and regions; they form networks of personnel to carry out various activities (drug production, transportation, distribution, sales, and money laundering); they change from time to time in response to the uncertainty and dynamics in their environments; their goals are to effectively and efficiently maximize profit and minimize damage and loss. Although drug crimes are not directly related to many organizations, they are likely to become one of our society's major problems that will have social, health, and economic impact on our lives (Mumford, 1998).
Solving drug crimes is by no means an easy task. Like many other complex problems, the drug problem consists of many sub-problems, which themselves are also complex. Identity matching is such a sub-problem of drug crimes. …