@inbook{7173b437e4624ccba64e09baeeb85707,
title = "Binary Selection Preference Decision-Making Model Based on Preference Distance",
abstract = "Portfolio optimization refers to the realization of objectives such as maximizing returns and minimizing risks by allocating different assets when resources are limited. This paper improves the interactive multi-criteria decision-making method for multi-objective portfolio decision-making problems, focusing on optimizing the preference feedback link. Introducing the idea of semi-supervised learning, a new preference feedback method of dichotomous selection is proposed, which improves the interaction effect of the model and makes the model better approach the preference of decision makers. At the same time, through the establishment of an initial preference distance model and self-learning of the decision-makers{\textquoteright} preference characteristics, in order to continuously update the decision-makers{\textquoteright} preference distances for different portfolio options.",
keywords = "Distance measurement learning, Preference feedback, Semi-supervised learning",
author = "Xu Jin and Shicheng Hu and Zicong Wang",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2022",
doi = "10.1007/978-3-030-81007-8\_66",
language = "英语",
series = "Lecture Notes on Data Engineering and Communications Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "585--593",
booktitle = "Lecture Notes on Data Engineering and Communications Technologies",
address = "德国",
}