The Learnability of Description Logics with Equality Constraints
Machine Learning - Special issue on computational learning theory, COLT'92
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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Similarity of documents based on the vector sequence model
IHI'04 Proceedings of the 2004 international conference on Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets
Towards constructing story databases using maximal analogies between stories
IHI'04 Proceedings of the 2004 international conference on Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets
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Given two documents in the form of texts, we present a notion of maximal analogy representing a generalized event sequence of documents with a maximal set of events. They are intended to be used as extended indices of documents to automatically organize a document database from various viewpoints. The maximal analogy is defined so as to satisfy a certain consistency condition and a cost condition. Under the consistency condition, a term in an event sequence is generalized to more abstract term independently of its occurrence positions. The cost condition is introduced so that meaningless similarities between documents are never concluded. As the cost function is monotone, we can present an optimized bottom-up search procedure to discover a maximal analogy under an upper bound of cost. We also show some experimental results based on which we discuss a future plan.