Implementation of search mechanism for implicit dependences in process mining

Kalynychenko, Olga; Chalyi, Serhii; Bodyanskiy, Yevgeniy; Golian, Vira; Golian, Nataliia

doi:10.1109/idaacs.2013.6662657

Cited by 22 publications

(29 citation statements)

References 1 publication

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“…The developed method implements a three-stage scheme for detecting shilling attacks based on a comparison of temporal rules. These rules describe implicit time dependencies between the user's choices in the specified processes [14]. At the first two stages, a set of modified rules is constructed.…”

Section: Methods For Detecting Shilling Attacks Using Temporal Rules Tmentioning

confidence: 99%

Method for Detecting Shilling Attacks in E-Commerce Systems Using Weighted Temporal Rules

Chala

Novikova

Chernyshova

2019

EUREKA: Physics and Engineering

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The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such attacks is to artificially change the rating of individual goods or services by users in order to increase their sales. A method for detecting shilling attacks based on a comparison of weighted temporal rules for the processes of selecting objects with explicit and implicit feedback from users is proposed. Implicit dependencies are specified through the purchase of goods and services. Explicit feedback is formed through the ratings of these products. The temporal rules are used to describe hidden relationships between the choices of user groups at two consecutive time intervals. The method includes the construction of temporal rules for explicit and implicit feedback, their comparison, as well as the formation of an ordered subset of temporal rules that capture potential shilling attacks. The method imposes restrictions on the input data on sales and ratings, which must be ordered by time or have timestamps. This method can be used in combination with other approaches to detecting shilling attacks. Integration of approaches allows to refine and supplement the existing attack patterns, taking into account the latest changes in user priorities.

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Section: Methods For Detecting Shilling Attacks Using Temporal Rules Tmentioning

confidence: 99%

Method for Detecting Shilling Attacks in E-Commerce Systems Using Weighted Temporal Rules

Chala

Novikova

Chernyshova

2019

EUREKA: Physics and Engineering

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“…The agent generates a continuous stream of user activity sequence data, which can be used for research into techniques for predicting the next action that a user may take -see our first Use Case in section IV.A -and on application dependencies in analytic processes, such as that carried out in [10]. b) Chrome Instrumenter: We also developed an instrumentation and visualization capability for the Google Chrome web browser, which we called ChromeInstrumenter.…”

Section: B Instrumentation Agentsmentioning

confidence: 99%

A Versatile Platform for Instrumentation of Knowledge Worker's Computers to Improve Information Analysis

Jones

Thakur

Cox

et al. 2016

2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService)

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Information analysis tasks are becoming increasingly complex as the growth in volume and variety of available data continues to outpace methods to automatically analyze it. The result is an increasing burden on knowledge workers. Industry and academia are currently lacking platforms and tools that can help provide enterprise-wide understanding of how humans analyze information. Through instrumentation of knowledge worker's activities during analysis tasks, we can enable research into techniques that address this need.Several research and design challenges need to be addressed, however, to develop scalable, robust and efficient instrumentation methods for collecting streaming data on relevant humanmachine interactions. This data is typically high volume and multi-modal. We present an instrumentation platform to meet these and future challenges in better understanding and improving the craft of information analysis. Our platform provides an extensible framework to instrument analyst's workstations during information processing tasks, and includes a streaming data processing pipeline that supports real-time analysis of large volumes of event data. We have built the instrumentation platform using the latest open-source scalable and flexible web components and hardware infrastructure. Researchers from science, engineering, and humanities are using our platform to gain insight into tool usage, analytical workflows, and collaboration patterns. Several use cases from these groups are described. Our platform provides a unique, pragmatic and holistic foundation to understand the behavior of knowledge workers, and to support applications that assist with information analysis.

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“…These methods transform the implicit knowledge of experts into an explicit form [1]. The usage of such methods, in contrast to withdraw the embedded knowledge [6], requires a great deal of time spent by ex perts and knowledge engineers. This does not always allow you to maintain the KB in its current state.…”

Section: Research Of Existing Solutions Of the Problemmentioning

confidence: 99%

Development of information technology for the automated construction and expansion of the temporal knowledge base in the tasks of supporting management decisions

Chala

2019

TAPR

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Implementation of search mechanism for implicit dependences in process mining

Cited by 22 publications

References 1 publication

Method for Detecting Shilling Attacks in E-Commerce Systems Using Weighted Temporal Rules

Method for Detecting Shilling Attacks in E-Commerce Systems Using Weighted Temporal Rules

A Versatile Platform for Instrumentation of Knowledge Worker's Computers to Improve Information Analysis

Development of information technology for the automated construction and expansion of the temporal knowledge base in the tasks of supporting management decisions

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