This book discusses the problem of Maximum-Score Diversity Selection (MSDS). Pure diversity selection, as it is often performed e.g. in early drug discovery, is the selection of a subset of available objects that is as diverse as possible. MSDS adds a second objective, which additionally tries to maximize the "score" of the subset, which usually is the sum of scores of all elements in the subset. Thus, this problem is a classical multi-objective optimization problem since both objectives -- maximizing score and maximizing diversity -- tend to conflict with each other. The author first discusses several diversity measures and then shows that MSDS is an NP-hard optimization problem. Subsequently several methods are presented and developed to efficiently solve this special multi-objective optimization problem. A large experimental evaluation compares the effectiveness of the presented algorithms and shows how they are influenced by the search space structure.
| Autorius: | Thorsten Meinl |
| Leidėjas: | Südwestdeutscher Verlag für Hochschulschriften AG Co. KG |
| Išleidimo metai: | 2015 |
| Knygos puslapių skaičius: | 132 |
| ISBN-10: | 3838120094 |
| ISBN-13: | 9783838120096 |
| Formatas: | 220 x 150 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Maximum-Score Diversity Selection: A study on the selection of the best and most diverse“
