Making large-scale support vector machine learning practical
Advances in kernel methods
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Using string-kernels for learning semantic parsers
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
PANTO: A Portable Natural Language Interface to Ontologies
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Constructing composite web services from natural language requests
Web Semantics: Science, Services and Agents on the World Wide Web
How useful are natural language interfaces to the semantic web for casual end-users?
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Understanding the semantic structure of noun phrase queries
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
TAGME: on-the-fly annotation of short text fragments (by wikipedia entities)
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Search computing
Search computing: multi-domain search on ranked data
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Talking to the semantic web – query interfaces to ontologies for the casual user
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
| Hi-index | 0.00 |
Natural language interfaces to data services will be a key technology to access unstructured data repositories in a natural way. This involves solving the complex problem of recognizing relevant services given an ambiguous, potentially ungrammatical natural language question. In this paper, we address the requirements of natural language interfaces to data services. While current approaches deal with single-domain questions, we study both rule-based and machine learning methods to address multi-domain questions to support conjunctive queries over data services. Our results denote high accuracy with both approaches.