[PDF] Data mining, Hypergraph Transversals, and Machine Learning
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Abstract. Several data mining problems can be formulated as problems of nding maximally speci c sentences that are interesting in a database.
Data mining, hypergraph transversals, and machine learning (extended abstract). Authors: Dimitrios Gunopulos ...
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Dual-Bounded Generating Problems: Partial and Multiple Transversals of ...
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Abstract. We consider two generalizations of the notion of transversal to a finite hypergraph, the so-called multiple and partial transversals.
Generating minimal transversals of a hypergraph is an important problem which has many applications in Computer Science, especially in database Theory, Logic, ...
... transversals, data mining and machine learning. MTminer [25] is a recent algorithm based on data mining techniques and concept lattices to compute minimal ...
Abstract. Finding hypergraph transversals is a major algorithmic issue which was shown having many connections with the data mining area.
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A Data Mining Formalization to Improve Hypergraph Minimal ...
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We propose a new algorithm MTMINER to extract minimal transversals and provide experiments showing that our method is efficient in practice. ResearchGate Logo.
3.2 Machine Learning and Data Mining. Im machine learning, the hypergraph transversal problem is related to problems in learning Boolean functions. In a ...
In this paper, a new hypergraph-based summarization model was proposed, in which the nodes are the sentences of the corpus and the hyperedges are themes ...