Communications of the ACM
Equivalence of Relational Algebra and Relational Calculus Query Languages Having Aggregate Functions
Journal of the ACM (JACM)
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Meteor-s web service annotation framework
Proceedings of the 13th international conference on World Wide Web
Apprenticeship learning via inverse reinforcement learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Structured program induction from behavioral traces
Systems and Computers in Japan
Inference of concise DTDs from XML data
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Ontology Reconciliation for Service-Oriented Computing
SCC '06 Proceedings of the IEEE International Conference on Services Computing
An Online Platform for Web APIs and Service Mashups
IEEE Internet Computing
Web Service Matching by Ontology Instance Categorization
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 1
SAWSDL-MX2: A Machine-Learning Approach for Integrating Semantic Web Service Matchmaking Variants
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Automatically labeling the inputs and outputs of web services
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
A planning approach for message-oriented semantic web service composition
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Efficient learning of action schemas and web-service descriptions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Learning symbolic models of stochastic domains
Journal of Artificial Intelligence Research
Learning semantic definitions of online information sources
Journal of Artificial Intelligence Research
A context driven approach for workflow mining
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Mashing Up Oil and Water: Combining Heterogeneous Services for Diverse Users
IEEE Internet Computing
From people to services to UI: distributed orchestration of user interfaces
BPM'10 Proceedings of the 8th international conference on Business process management
A minimalist approach to semantic annotations for web processes compositions
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
A survey of automated web service composition methods
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
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This paper considers the problem of learning task specific web-service descriptions from traces of users successfully completing a task. Unlike prior approaches, we take a traditional machine-learning perspective to the construction of web-service models from data. Our representation models both syntactic features of web-service schemas including lists and optional elements, as well as semantic relations between objects in the task. Together, these learned models form a full schematic model of the dataflow. Our theoretical results, which are the main novelty in the paper, show that this structure can be learned efficiently: the number of traces required for learning grows polynomially with the size of the task. We also present real-world task descriptions mined from tasks using online services from Amazon and Google.