On Automating Decentralized Multi-Step Service Combination
Publication date
2017-09-07
Document type
Conference paper
Author
Organisational unit
Karlsruhe Institute of Technology
Scopus ID
ISBN
Conference
2017 IEEE International Conference on Web Services (ICWS), June 25 2017 to June 30 2017, Honolulu, HI
Book title
2017 IEEE 24th International Conference on Web Services - ICWS 2017 : Proceedings
First page
736
Last page
743
Peer-reviewed
✅
Part of the university bibliography
Nein
Keyword
Accuracy Estimation
Coordination in Multi-Agent System
Named Entity Recognition and-Disambiguation
Service Combination
Abstract
Information on the Web is heterogeneous and available in constantly increasing quantities. Consequently, there are numerous, partly redundant data analytics services, each optimized for data with certain characteristics. Often, analytics tasks require multiple services to be pipelined to find a solution, where combinations of exchangeable services for single steps might outperform one-service-predictions. This work proposes a Multi-Agent System (MAS) perception of prior setting, where decentralized agents are considered to manage services, having to coordinate their decisions to find a consensus. We, first, propose a supervised method for service accuracy estimation and, therefore, exploit locality-sensitive features of training data. Given a committee of services managed by agents, we develop coordination strategies to handle conflicting confidences and reduce erroneous predictions due to service correlation. We evaluate our approach with Named Entity Recognition (NER)- A nd Named Entity Disambiguation (NED) services on text corpora with heterogeneous characteristics (i.e. news articles and tweets). Our empirical results improve the out-of-the-box performance of the original services.
Version
Not applicable (or unknown)
Access right on openHSU
Metadata only access