A framework of a mechanical translation between Japanese and English by analogy principle
Proc. of the international NATO symposium on Artificial and human intelligence
An Information Retrieval Approach for Automatically Constructing Software Libraries
IEEE Transactions on Software Engineering
The use of a lattice in knowledge processing
The use of a lattice in knowledge processing
International Journal of Man-Machine Studies
A hybrid nearest-neighbor and nearest-hyperrectangle algorithm
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Information retrieval through hybrid navigation of lattice representations
International Journal of Human-Computer Studies
Empirical Learning of Natural Language Processing Task
ECML '97 Proceedings of the 9th European Conference on Machine Learning
Classification by Voting Feature Intervals
ECML '97 Proceedings of the 9th European Conference on Machine Learning
Efficient Retrieval from Hierarchies of Objects using Lattice Operations
ICCS '93 Proceedings on Conceptual Graphs for Knowledge Representation
Embedded machine learning systems for natural language processing: a general framework
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
A revision learner to acquire verb selection rules from human-made rules and examples
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Memory-Based Lexical Acquisition and Processing
Proceedings of the Third International EAMT Workshop on Machine Translation and the Lexicon
Adaptation Guided Retrieval in EBMT: A Case-Based Approach to Machine Translation
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
Filling knowledge gaps in a broad coverage machine translation system
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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Grammatically incorrect sentences result either from an unknown (possibly misspelled) word, an incorrect word order or even an omitted / redundant word. Sentences with these errors are a bottleneck to NLP systems because they cannot be parsed correctly. Human beings are able to overcome this problem (either occurring in spoken or written language) since they are capable of doing a semantic similarity search to find out if a similar utterance has been heard before or a syntactic similarity search for a stored utterance that shares structural similarities with the input. If the syntactic and semantic analysis of the rest of the input can be done correctly, then a 'gap' that exists in the utterance, can be uniquely identified. In this paper, a system named SAUCOLA which is based on a concept lattice, that mimics human skills in resolving knowledge gaps that exist in written language is presented. The preliminary results show that correct stored sentences can be retrieved based on the words contained in the incorrect input sentence.