L. Dehaspe and L. De Raedt. Mining a natural language corpus for multi-relational association rules. In Proceedings of the Workshop on Empirical Learning of Natural Language Processing Tasks, pages 35--48, 1997. Invited keynote paper. Home/Search Document Details and Download
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Analyzing and Predicting Patterns of DAMSL Utterance Tags - Core (1 citation) (Correct)
....out additional results based on looking at more complex patterns of DAMSL tags. The addition of cue words and sentence forms to the context should bring new developments as well. Another area for exploration is the use of data mining techniques to extract interesting patterns from the corpus. (Dehaspe Raedt 1997) tries such an approach on part of speech tags in a corpus of Wall Street Journal text. Conclusions Results on hand coded decision trees (given only the context of the last utterance s DAMSL tags) suggest that automatically derived decision trees should be effective DAMSL tag predictors. The ....
Dehaspe, L., and Raedt, L. D. 1997. Mining a natural language corpus for multi-relational association rules.
Three Companions for Data Mining in First Order Logic - De Raedt, Blockeel.. (2001) (6 citations) Self-citation (Dehaspe De raedt) (Correct)
....where each example consists of a single tuple in a relational database. This representation is inadequate for problem domains that require reasoning about the structure of objects in the domain and relations among such objects, such as in bio chemistry [8] natural language processing [15], and traffic control [18] This paper presents three companion systems, where each example corresponds to a small relational database (or Prolog knowledge base) Hence, examples consist of multiple relations and each example can have multiple tuples for these relations. This setting is known in ....
L. Dehaspe and L. De Raedt. Mining a natural language corpus for multi-relational association rules. In Proceedings of the Workshop on Empirical Learning of Natural Language Processing Tasks, pages 35--48, 1997. Invited keynote paper.
Three Companions for First Order Data Mining - De Raedt, Blockeel, Dehaspe.. (1998) (1 citation) Self-citation (Dehaspe De raedt) (Correct)
....employ a limited attribute value representation, where each example consists of a single tuple in a relational database. This representation is inadequate for problem domains that require reasoning about the structure of the domain, such as e.g. in bio chemistry [7] natural language processing [14], This paper presents three companion systems, where each example corresponds to a small relational database (or Prolog knowledge base) Hence, examples consists of multiple relations and each example can have multiple tuples for these relations. This setting is known in the literature as ....
L. Dehaspe and L. De Raedt. Mining a natural language corpus for multi-relational association rules. In Proceedings of the Workshop on Empirical Learning of Natural Language Processing Tasks (ECML'97), pages 35--48, 1997.
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