Name
Abstract | ||
|---|---|---|
Time series in time domains with a hierarchical structure may be summarized by means of sets of quantified fuzzy sentences of the form "Q of D is A", where Q is a quantifier, D is a linguistic time interval, and A is a linguistic value. Finding concise and accurate summaries that cover the whole time domain is a hard optimization problem, that we solve by proposing a multi-objective memetic algorithm based on NSGA-II with the addition of a number of intelligent mutation operators that apply heuristics to improve solutions. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2001858.2001954 | GECCO (Companion) |
Keywords | Field | DocType |
fuzzy sentence,accurate summary,time series,time domain,intelligent mutation operator,hard optimization problem,linguistic time interval,hierarchical structure,whole time domain,linguistic value,multi-objective memetic algorithm,linguistic summarization,memetic algorithm,optimization problem,fuzzy logic | Memetic algorithm,Time domain,Mathematical optimization,Of the form,Computer science,Fuzzy logic,Linguistic summarization,Heuristics,Linguistic value,Artificial intelligence,Optimization problem,Machine learning | Conference |
Citations | PageRank | References |
6 | 0.53 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rita Castillo-Ortega | 1 | 124 | 7.30 |
| Nicolás Marín | 2 | 570 | 41.16 |
| Daniel Sanchez | 3 | 928 | 39.02 |
| Andrea Tettamanzi | 4 | 667 | 84.56 |