A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Information retrieval and the average number of input clues
Tekijät: Laihonen T
Kustantaja: AMER INST MATHEMATICAL SCIENCES-AIMS
Julkaisuvuosi: 2017
Journal: Advances in Mathematics of Communications
Tietokannassa oleva lehden nimi: ADVANCES IN MATHEMATICS OF COMMUNICATIONS
Lehden akronyymi: ADV MATH COMMUN
Vuosikerta: 11
Numero: 1
Aloitussivu: 203
Lopetussivu: 223
Sivujen määrä: 21
ISSN: 1930-5346
eISSN: 1930-5338
DOI: https://doi.org/10.3934/amc.2017013
Tiivistelmä
Information retrieval in an associative memory was introduced in a recent paper by Yaakobi and Bruck. The associative memory is represented by a graph where the vertices correspond to the stored information units and the edges to associations between them. The goal is to find a stored information unit in the memory using input clues. In this paper, we study the minimum average number of input clues needed to find the sought information unit in the infinite king grid. We provide a geometric approach to determine the minimum number of input clues. Using this approach we are able to find optimal results and bounds on the number of input clues. The model by Yaakobi and Bruck has also applications to sensor networks monitoring and Levenshtein's sequence reconstruction problem.
Information retrieval in an associative memory was introduced in a recent paper by Yaakobi and Bruck. The associative memory is represented by a graph where the vertices correspond to the stored information units and the edges to associations between them. The goal is to find a stored information unit in the memory using input clues. In this paper, we study the minimum average number of input clues needed to find the sought information unit in the infinite king grid. We provide a geometric approach to determine the minimum number of input clues. Using this approach we are able to find optimal results and bounds on the number of input clues. The model by Yaakobi and Bruck has also applications to sensor networks monitoring and Levenshtein's sequence reconstruction problem.
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