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Interactive Anomaly...
Interactive Anomaly Detection Based on Clustering and Online Mirror Descent
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- Cheng, Lingyun (författare)
- Högskolan i Halmstad
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- Sundaresh, Sadhana (författare)
- Högskolan i Halmstad
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- Bouguelia, Mohamed-Rafik, 1987- (författare)
- Högskolan i Halmstad,CAISR Centrum för tillämpade intelligenta system (IS-lab)
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- Dikmen, Onur, 1977- (författare)
- Högskolan i Halmstad,CAISR Centrum för tillämpade intelligenta system (IS-lab)
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(creator_code:org_t)
- Berlin : Springer Berlin/Heidelberg, 2020
- 2020
- Engelska.
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Serie: Communications in Computer and Information Science, 1865-0929
- Relaterad länk:
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https://hh.diva-port... (primary) (Raw object)
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- In several applications, when anomalies are detected, human experts have to investigate or verify them one by one. As they investigate, they unwittingly produce a label - true positive (TP) or false positive (FP). In this paper, we propose a method (called OMD-Clustering) that exploits this label feedback to minimize the FP rate and detect more relevant anomalies, while minimizing the expert effort required to inves- tigate them. The OMD-Clustering method iteratively suggests the top-1 anomalous instance to a human expert and receives feedback. Before suggesting the next anomaly, the method re-ranks instances so that the top anomalous instances are similar to the TP instances and dissimi- lar to the FP instances. This is achieved by learning to score anomalies differently in various regions of the feature space. An experimental eval- uation on several real-world datasets is conducted. The results show that OMD-Clustering achieves significant improvement in both detection pre- cision and expert effort compared to state-of-the-art interactive anomaly detection methods.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Nyckelord
- Interactive Anomaly Detection
- Outlier Detection
- User Feedback
- Expert Effort
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)