Name
Title | ||
|---|---|---|
Multi-objective Evolutionary Algorithms in the Automatic Learning of Boolean Queries: A Comparative Study |
Abstract | ||
|---|---|---|
The performance of Information Retrieval Systems (IRSs) is usually measured using two different criteria, precision and recall. In such a way, the problem of tuning an IRS may be considered as a multi-objective optimization problem. In this contribution, we focus on the automatic learning of Boolean queries in IRSs by means of multi-objective evolutionary techniques. We present a comparative study of four multi-objective evolutionary optimization techniques of general-purpose (NSGA-II, SPEA2 and two MOGLS) to learn Boolean queries. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72434-6_8 | THEORETICAL ADVANCES AND APPLICATIONS OF FUZZY LOGIC AND SOFT COMPUTING |
Keywords | Field | DocType |
information retrieval systems,genetic programming,inductive query by example,multi-objective evolutionary algorithms,query learning | Interactive evolutionary computation,Evolutionary algorithm,Human-based evolutionary computation,Computer science,Precision and recall,Evolutionary computation,Genetic programming,Artificial intelligence,Evolutionary programming,Optimization problem,Machine learning | Conference |
Volume | ISSN | Citations |
42.0 | 1615-3871 | 0 |
PageRank | References | Authors |
0.34 | 14 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Gabriel López-herrera | 1 | 423 | 18.65 |
| Enrique Herrera-Viedma | 2 | 13105 | 642.24 |
| Francisco Herrera | 3 | 27391 | 1168.49 |
| Carlos Porcel | 4 | 450 | 24.12 |
| Sergio Alonso | 5 | 1669 | 53.28 |