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This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines the professional fraudster, formalises the main types and subtypes of known fraud, and presents the nature of data evidence collected within affected industries. Within the business(More)
Jackendoff (2002) posed four challenges that linguistic combinatoriality and rules of language present to theories of brain function. The essence of these problems is the question of how to neurally instantiate the rapid construction and transformation of the compositional structures that are typically taken to be the domain of symbolic processing. He(More)
Entity resolution, also known as data matching or record linkage, is the task of identifying and matching records from several databases that refer to the same entities. Traditionally, entity resolution has been applied in batch-mode and on static databases. However, many organisations are increasingly faced with the challenge of having large databases(More)
Most research into entity resolution (also known as record linkage or data matching) has concentrated on the quality of the matching results. In this paper, we focus on matching time and scalability, with the aim to achieve large-scale real-time entity resolution. Traditional entity resolution techniques have assumed the matching of two static databases. In(More)
We provide an overview of Vector Symbolic Architectures (VSA), a class of structured associative memory models that offers a number of desirable features for artificial general intelligence. By directly encoding structure using familiar , computationally efficient algorithms, VSA bypasses many of the problems that have consumed unnecessary effort and(More)
" A system's resilience is the single most important security property it has. "-Bruce Schneier, 2003, " Beyond Fear: Thinking Sensibly about Security in an Uncertain World " Abstract Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure,(More)
—Identity crime is well known, prevalent, and costly; and credit application fraud is a specific case of identity crime. The existing non-data mining detection systems of business rules and scorecards, and known fraud matching have limitations. To address these limitations and combat identity crime in real-time, this paper proposes a new multi-layered(More)
— Analogy-making is a key function of human cog-nition. Therefore, the development of computational models of analogy that automatically learn from examples can lead to significant advances in cognitive systems. Analogies require complex, relational representations of learned structures, which is challenging for both symbolic and neurally inspired models.(More)