Eleven commercial toasted white corn tortilla chip products from the United States were evaluated by a group of 80 consumers of age 18-35 and by a trained sensory panel. Proportional odds models in conjunction with pr...
详细信息
Eleven commercial toasted white corn tortilla chip products from the United States were evaluated by a group of 80 consumers of age 18-35 and by a trained sensory panel. Proportional odds models in conjunction with principal components were used for internal and external preference modeling of tortilla chip consumer overall acceptance. The internal preference modeling showed that flavor was the most important attribute to consumer overall acceptance followed by the interaction of appearance by flavor and texture. The external preference modeling showed that one flavor attribute (salt aftertaste) and one texture attribute (crispness) contributed significantly to increase consumer overall acceptance, whereas one appearance attribute (instrumental color a*) significantly lowered consumer overall acceptance. The information reported in this study is important to the tortilla chip industry to produce tortilla chips with greater consumer acceptability. This study implies that proportional odds model using principal components is an alternative tool for consumer preference modeling. (C) 2003 Elsevier Science Ltd. All rights reserved.
This study introduces a new approach for modelingpreference-aware human spatial behavior in cyber-physical-human systems using Graph Neural Networks (GNN) and Reinforcement Learning (RL). Current models often overloo...
详细信息
This study introduces a new approach for modelingpreference-aware human spatial behavior in cyber-physical-human systems using Graph Neural Networks (GNN) and Reinforcement Learning (RL). Current models often overlook the causality and impact of factors influencing preferences. Our approach utilizes GNN for its advanced handling of spatial data, capturing physical, social, and environmental features and their human perception. Integrated with RL, the model dynamically adapts to changes in the surrounding environment. We illustrate the approach in an educational conference room setting, comparing student behavior simulations with and without preferences. The results indicate that preference incorporation leads to significantly more realistic simulations. Copyright (c) 2024 The Authors.
Network-aware cascade size prediction aims to predict the final reposted number of user-generated information via modeling the propagation process in social networks. Estimating the user's reposting probability by...
详细信息
ISBN:
(纸本)9781450387323
Network-aware cascade size prediction aims to predict the final reposted number of user-generated information via modeling the propagation process in social networks. Estimating the user's reposting probability by social influence, namely state activation plays an important role in the information diffusion process. Therefore, Graph Neural Networks (GNN), which can simulate the information interaction between nodes, has been proved as an effective scheme to handle this prediction task. However, existing studies including GNN-based models usually neglect a vital factor of user's preference which influences the state activation deeply. To that end, we propose a novel framework to promote cascade size prediction by enhancing the user preference modeling according to three stages, i.e., preference topics generation, preference shift modeling, and social influence activation. Our end-to-end method makes the user activating process of information diffusion more adaptive and accurate. Extensive experiments on two large-scale real-world datasets have clearly demonstrated the effectiveness of our proposed model compared to state-of-the-art baselines.
Choice problems refer to the problem of selecting the best choices from several available items, and learning users' preferences in choice problems is of great importance in understanding users' decision makin...
详细信息
Choice problems refer to the problem of selecting the best choices from several available items, and learning users' preferences in choice problems is of great importance in understanding users' decision making mechanisms and providing personalized services. Existing works typically assume that people evaluate items independently. In practice, however, users' preferences depend on the market in which items are placed, which is known as the context effects;and the order of users' preferences for two items may even be reversed, which is called preference reversals. In this work, we identify three factors contributing to the context effects: users' adaptive weights, the inter-item comparison, and display positions. We propose a context-dependent preference model named Pacos as a unified framework to address three factors simultaneously, and consider two design methods including an additive method with high interpretability and an ANN-based method with high accuracy. We study the conditions for preference reversals to occur and provide a theoretical proof of the effectiveness of Pacos in predicting when preference reversals would occur. Experimental results show that the proposed method has better performance than prior works in predicting users' choices, and has great interpretability to help understand the cause of preference reversals. (c) 2023 Elsevier B.V. All rights reserved.
In this paper we introduce and investigate weak t-norms and related concepts in order to give a general representation of valued strict preference relations associated with a given valued preference relation. All the ...
详细信息
In this paper we introduce and investigate weak t-norms and related concepts in order to give a general representation of valued strict preference relations associated with a given valued preference relation. All the well-known forms of valued strict preference relations are particular cases of our results. Moreover, when some types of 'rationality' assumptions are made, our unified approach seems to be the only possible one.
The delivery of multimedia content often needs the adaptation of the content in order to satisfy user constraints. With the Digital Item Adaptation part, the MPEG-21 standard already defines a useful frame-work to han...
详细信息
The delivery of multimedia content often needs the adaptation of the content in order to satisfy user constraints. With the Digital Item Adaptation part, the MPEG-21 standard already defines a useful frame-work to handle this task. However, in modern service-oriented architectures the functionality of adaptation is split over several services. Hence, the central instantiation of a suitable service chain needs to tackle a complex multi-objective optimization problem. In this problem between content choice and possible adaptations the current preference model in the MPEG-7/21 standard still lacks expressiveness. In the course of this paper we demonstrate this shortcoming and how the integration of more powerful models can ease the instantiation problem. Furthermore we explain how to efficiently evaluate preference trade-offs by evaluating skyline queries as currently investigated in the field of information systems. As a running example we use preference-based content adaptation in a typical media streaming application with Web services as basic modules. The contribution of our framework is to enable a central coordinator to instantiate an executable service composition chain by integrating all needed Web services to adapt the multimedia content in the best possible fashion in the sense of Pareto optimality.
作者：
Yager, RRIona Coll
Inst Machine Intelligence New Rochelle NY 10801 USA
We consider the problem of group decision making where the selection process is based upon a group preference function, obtained by an aggregation of the participating agents individual preference functions. We descri...
详细信息
We consider the problem of group decision making where the selection process is based upon a group preference function, obtained by an aggregation of the participating agents individual preference functions. We describe some methods for formulating the group preference from the individual preference functions. We note the possibility of the individual agents strategically manipulating the information they provide, so as to further their own goal of getting their most preferred alternative selected by the group. With this in mind, we suggest ways of modifying the formulation of the group decision functions to discourage strategic manipulation by the participating agents.
An original methodology for using rough sets to preference modeling in multi-criteria decision problems is presented. This methodology operates on a pairwise comparison table (PCT), including pairs of actions describe...
详细信息
An original methodology for using rough sets to preference modeling in multi-criteria decision problems is presented. This methodology operates on a pairwise comparison table (PCT), including pairs of actions described by graded preference relations on particular criteria and by a comprehensive preference relation. It builds up a rough approximation of a preference relation by graded dominance relations. Decision rules derived from the rough approximation of a preference relation can be used to obtain a recommendation in multi-criteria choice and ranking problems. The methodology is illustrated by an example of multi-criteria programming of water supply systems. (C) 1999 Published by Elsevier Science B.V. All rights reserved.
This paper studies the use of product-based possibilistic networks for representing preferences in multidimensional decision problems. This approach uses symbolic possibility weights and defines a partial preference o...
详细信息
This paper studies the use of product-based possibilistic networks for representing preferences in multidimensional decision problems. This approach uses symbolic possibility weights and defines a partial preference order among solutions to a set of conditional preference statements on the domains of discrete decision variables. In the case of Boolean decision variables, this partial ordering is shown to be consistent with the preference ordering induced by the ceteris paribus assumption adopted in CP-nets. Namely, by completing the possibilistic net ordering with suitable constraints between products of symbolic weights, all CP-net preferences can be recovered. Computing procedures for comparing solutions are provided. The flexibility and representational power of the approach is stressed. (C) 2017 Elsevier Inc. All rights reserved.
Conflict arises in decision making when the choice alternatives present strong advantages and disadvantages over one another, that is, when the trade-offs involved are large. Conflict affects human response to choice,...
详细信息
Conflict arises in decision making when the choice alternatives present strong advantages and disadvantages over one another, that is, when the trade-offs involved are large. Conflict affects human response to choice, in particular, it increases decision difficulty and response unreliability. On the other hand, larger trade-offs, i.e., higher conflict, reveal more information about an individual's preferences and mitigate the influence of measurement unreliability on preference model estimation. This suggests, somewhat counterintuitively, that there may exist some optimal level of conflict for efficient measurement of preferences. How to determine this level? This issue is examined from behavioral and analytical angles. We outline a general analysis of the interaction between trade-off size and modeling accuracy, and demonstrate its application on a simple example. The kind of analysis developed here can be conveniently implemented in a computer spreadsheet, and would be especially valuable when large amounts of preference data are to be collected, as in consumer preference studies, experimental research, and contingent valuation surveys.
暂无评论