Greedy algorithm
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1A Formal Model for Information Selection in MultiSentence Text Extractionsolutions within a known bound of the optimal solution. The greedy algorithm for maximum set coverage has as follows: Start with...

2Detecting Multiple Facets of an Event using GraphBased Unsupervised Methodsset of all documents. 4.3 Greedy Algorithm To solve the above problem, we propose a greedy algorithm. This algorithm computes...

3Explore the Structure of Social Tags by Subsumption Relationsresult. Besides relation discovery, we also propose a greedy algorithm to eliminate the redundant relations by constructing...

4Citation Summarization Through Keyphrase ExtractionRelevance (MMR) summarization method, which is based on a greedy algorithm, is described in (Carbonell and Goldstein, 1998). MMR...

5Exploiting Structured Ontology to Organize Scattered Online Opinionsformulated as a maximum coverage problem, for which a greedy algorithm is known to be a good approximation: we select one aspect...

6Text Summarization Model based on RedundancyConstrained Knapsack ProblemHatzivassiloglou (2004). They solved their model by a greedy algorithm (Khuller et al., 1999). Yih et al. (2007) solved the...

7Fast, Greedy Model Minimization for Unsupervised Taggingpath has been found. 5.3 Fitting the Model Once the greedy algorithm terminates and returns a minimized grammar of tag bigrams...

8MultiDocument Summarization via the Minimum Dominating Set2010  Chaojan Chen,Tao Lidescribed in (Johnson, 1973). Basically, at each stage, the greedy algorithm chooses the set which contains the largest number of...

9Explaining Similarity of Terms2008  Vishnu Vyas,Patrick Pantelinformation gains. This formulation also gives a simple greedy algorithm to the optimization problem when the size of explanation...

10MemoryEfficient Katakana Compound Segmentation using Conditional Random Fieldsusing some dictionarybased heuristic. For example the greedy algorithm may be used where, at first, the longest dictionary...