Kumar et al., 2018 - Google Patents
Faster approximation algorithm for the k-regret minimizing set and related problemsKumar et al., 2018
View PDF- Document ID
- 8029991073278688791
- Author
- Kumar N
- Sintos S
- Publication year
- Publication venue
- 2018 Proceedings of the Twentieth Workshop on Algorithm Engineering and Experiments (ALENEX)
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Snippet
Efficient multi-criteria decision making often requires looking at a small set of representative objects from a large collection. A recently proposed method for finding representative objects is the k-regret minimizing set (k-RMS problem). Intuitively, given a large set of …
- 230000004048 modification 0 abstract description 3
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- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30533—Other types of queries
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- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
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