Feature selection is one of the key problems for machine learning and data mining. In this review paper, a brief historical background of the field is given, followed by a selection of challenges ...which are of particular current interests, such as feature selection for high-dimensional small sample size data, large-scale data, and secure feature selection. Along with these challenges, some hot topics for feature selection have emerged, e.g., stable feature selection, multi-view feature selection, distributed feature selection, multi-label feature selection, online feature selection, and adversarial feature selection. Then, the recent advances of these topics are surveyed in this paper. For each topic, the existing problems are analyzed, and then, current solutions to these problems are presented and discussed. Besides the topics, some representative applications of feature selection are also introduced, such as applications in bioinformatics, social media, and multimedia retrieval.
A fundamental problem in many disciplines is the classification of objects in a domain of interest into a taxonomy. Developing a taxonomy, however, is a complex process that has not been adequately ...addressed in the information systems (IS) literature. The purpose of this paper is to present a method for taxonomy development that can be used in IS. First, this paper demonstrates through a comprehensive literature survey that taxonomy development in IS has largely been ad hoc. Then the paper defines the problem of taxonomy development. Next, the paper presents a method for taxonomy development that is based on taxonomy development literature in other disciplines and shows that the method has certain desirable qualities. Finally, the paper demonstrates the efficacy of the method by developing a taxonomy in a domain in IS.
Information systems security (ISS) behavioral research has produced different models to explain security policy compliance. This paper (1) reviews 11 theories that have served the majority of ...previous information security behavior models, (2) empirically compares these theories (Study 1), (3) proposes a unified model, called the unified model of information security policy compliance (UMISPC), which integrates elements across these extant theories, and (4) empirically tests the UMISPC in a new study (Study 2), which provided preliminary empirical support for the model. The 11 theories reviewed are (1) the theory of reasoned action, (2) neutralization techniques, (3) the health belief model, (4) the theory of planned behavior, (5) the theory of interpersonal behavior, (6) the protection motivation theory, (7) the extended protection motivation theory, (8) deterrence theory and rational choice theory, (9) the theory of self-regulation, (10) the extended parallel processing model, and (11) the control balance theory. The UMISPC is an initial step toward empirically examining the extent to which the existing models have similar and different constructs. Future research is needed to examine to what extent the UMISPC can explain different types of ISS behaviors (or intentions thereof). Such studies will determine the extent to which the UMISPC needs to be revised to account for different types of ISS policy violations and the extent to which the UMISPC is generalizable beyond the three types of ISS violations we examined. Finally, the UMISPC is intended to inspire future ISS research to further theorize and empirically demonstrate the important differences between rival theories in the ISS context that are not captured by current measures.
Extant literature has increased our understanding of the multifaceted nature of the digital divide, showing that it entails more than access to information and communication resources. Research ...indicates that digital inequality mirrors to a significant extent offline inequality related to socioeconomic resources. Bridging digital divides is critical for sustainable digitalized societies. Ιn this paper, we present a literature review of Information Systems research on the digital divide within settings with advanced technological infrastructures and economies over the last decade (2010–2020). The review results are organized in a concept matrix mapping contributing factors and measures for crossing the divides. Building on the results, we elaborate a research agenda that proposes 1 extending established models of digital inequalities with new variables and use of theory, 2 critically examining the effects of digital divide interventions, and 3 better linking digital divide research with research on sustainability.
This essay discusses the use of big data analytics (BDA) as a strategy of enquiry for advancing information systems (IS) research. In broad terms, we understand BDA as the statistical modelling of ...large, diverse, and dynamic data sets of user-generated content and digital traces. BDA, as a new paradigm for utilising big data sources and advanced analytics, has already found its way into some social science disciplines. Sociology and economics are two examples that have successfully harnessed BDA for scientific enquiry. Often, BDA draws on methodologies and tools that are unfamiliar for some IS researchers (e.g., predictive modelling, natural language processing). Following the phases of a typical research process, this article is set out to dissect BDA’s challenges and promises for IS research, and illustrates them by means of an exemplary study about predicting the helpfulness of 1.3 million online customer reviews. In order to assist IS researchers in planning, executing, and interpreting their own studies, and evaluating the studies of others, we propose an initial set of guidelines for conducting rigorous BDA studies in IS.
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