Instance-Based Learning Algorithms
Machine Learning
Information extraction as a basis for high-precision text classification
ACM Transactions on Information Systems (TOIS)
A database perspective on knowledge discovery
Communications of the ACM
Machine Learning
An Effective Deductive Object-Oriented Database Through Language Integration
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
PBL: Prototype-Based Learning Algorithms
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
DEXA '95 Proceedings of the 6th International Conference on Database and Expert Systems Applications
A Machine Learning Workbench in a DOOD Framework
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
Memory-based learning: using similarity for smoothing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
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We have designed several new lazy learning algorithms for learning problems with many binary features and classes. This particular type of learning task can be found in many machine learning applications but is of special importance for machine learning of natural language. Besides pure instance-based learning we also consider prototype-based learning, which has the big advantage of a large reduction of the required memory and processing time for classification. As an application for our learning algorithms we have chosen natural language database interfaces. In our interface architecture the machine learning module replaces an elaborate semantic analysis component. The learning task is to select the correct command class based on semantic features extracted from the user input. We use an existing German natural language interface to a production planning and control system as a case study for our evaluation and compare the results achieved by the different lazy learning algorithms.