Adaptive rule monitoring system

Alireza Tabebordbar, Amin Beheshti

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

6 Citations (Scopus)

Abstract

Rule-based techniques are gaining importance with their ability to augment large scale data processing systems. However, there still remain key challenges amongst current rule-based techniques, including rule monitoring, adapting and evaluation. Among these challenges, monitoring the precision of rules is highly important as it enables analysts to maintain the accuracy of a rule-based system. In this paper, we propose an Adaptive Rule Monitoring System (ARMS) for monitoring the precision of rules. The approach employs a combination of machine learning and crowdsourcing techniques. ARMS identifies rules deteriorating the performance of a rule based system, using the feedback receives from the crowd. To enable analysts identifying the imprecise rules, ARMS leverage machine learning algorithms to analyze the crowd's feedback. The evaluation results show that ARMS can identify the imprecise rules more successfully compared to the default practice of the system, which rely exclusively on analysts.

Original languageEnglish
Title of host publicationSE4COG 2018 Proceedings of the 1st International Workshop on Software Engineering for Cognitive Services
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages45-51
Number of pages7
ISBN (Print)9781450357401
DOIs
Publication statusPublished - 28 May 2018
EventACM/IEEE 1st International Workshop on Software Engineering for Cognitive Services, SE4COG 2018, co-located with the 40th International Conference on Software Engineering, ICSE 2018 - Gothenburg, Sweden
Duration: 28 May 201829 May 2018

Conference

ConferenceACM/IEEE 1st International Workshop on Software Engineering for Cognitive Services, SE4COG 2018, co-located with the 40th International Conference on Software Engineering, ICSE 2018
CountrySweden
CityGothenburg
Period28/05/1829/05/18

Keywords

  • multi-armed-bandit algorithm
  • rule based systems
  • rule monitoring system

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