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ANY COMPLETE preference STRUCTURE WITHOUT CIRCUIT ADMITS AN INTERVAL REPRESENTATION

THEORY AND DECISION 1995年第2期39卷 115-126页

作者： ABBAS, M UNIV SCI & TECHNOL HOUARI BOUMEDIENE INST MATHDEPT RECH OPERATALGIERS 16111ALGERIA

This article proves that all complete preference structures where the strict preference relation (P) has no circuit admit a representation by intervals of the real line;the rule for deciding whether an interval is indifferent or preferred to another is less straightforward than for interval orders: strict preference is indeed compatible with a certain degree of overlapping of intervals, the allowed degree being specified by means of a so-called tolerance function.

关键词： DECISION THEORY preference modeling TOLERANCE INTERVAL ORDERS TOLERANCE GRAPHS PHI-TOLERANCE INTERVAL GRAPHS

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Rank-heterogeneous preference Models for School Choice 23

Rank-heterogeneous Preference Models for School Choice

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29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

作者： Awadelkarim, Amel Seshadri, Arjun Ashlagi, Itai Lo, Irene Ugander, Johan Stanford Univ Stanford CA 94305 USA Amazon San Francisco CA USA

ISBN: (纸本)9798400701030

School choice mechanism designers use discrete choice models to understand and predict families' preferences. The most widely-used choice model, the multinomial logit (MNL), is linear in school and/or household attributes. While the model is simple and interpretable, it assumes the ranked preference lists arise from a choice process that is uniform throughout the ranking, from top to bottom. In this work, we introduce two strategies for rank-heterogeneous choice modeling tailored for school choice. First, we adapt a context-dependent random utility model (CDM), considering down-rank choices as occurring in the context of earlier up-rank choices. Second, we consider stratifying the choice modeling by rank, regularizing rank-adjacent models towards one another when appropriate. Using data on household preferences from the San Francisco Unified School District (SFUSD) across multiple years, we show that the contextual models considerably improve our out-of-sample evaluation metrics across all rank positions over the non-contextual models in the literature. Meanwhile, stratifying the model by rank can yield more accurate first-choice predictions while down-rank predictions are relatively unimproved. These models provide performance upgrades that school choice researchers can adopt to improve predictions and counterfactual analyses.

关键词： school choice discrete choice preference modeling ranking models

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Improving Algorithm Response to preference Changes in Multiobjective Optimisation Using Archives

Improving Algorithm Response to Preference Changes in Multio...

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IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Taylor, Kendall Li, Xiaodong Chan, Jeffrey RMIT Univ Sch Sci Melbourne Vic Australia

ISBN: (纸本)9781728121536

Using evolutionary algorithms to solve optimisation problems with multiple objectives has proven very successful over the past few decades. The ability of these methods to efficiently find sets of solutions representing trade-offs between conflicting objectives has enhanced decision making in a wide variety of fields. Increasingly though, such techniques are being adapted to incorporate end-user preferences in order to reduce search spaces and provide smaller sets of targeted solutions. Eliciting these preferences interactively during optimisation has also become popular and helps a decision maker explore and learn and the problem and its range of solutions. Interactivity also facilitates the correction of mistakes and inaccurate preferences, leading to more satisfactory solutions, faster. In order to achieve these benefits an algorithm must be able to rapidly respond to changes in preferences. This work explores the use of secondary population archives to ensure a preference-based algorithm can change its search focus efficiently and effectively. When preferences change and the search is redirected to a new region of interest, an archive of previously found solutions can be consulted and solutions close to the new region can be included in the current population. This work shows how such archives can be implemented and how they can improve responsiveness for certain problems.

关键词： Interactive optimisation preference modeling Multiobjective optimisation Evolutionary computation

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preference-ORIENTED FORM DESIGN: APPLICATION TO CARS' HEADLIGHTS

PREFERENCE-ORIENTED FORM DESIGN: APPLICATION TO CARS' HEADLI...

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17th International Conference on Engineering Design

作者： Petiot, Jean-Francois Dagher, Antoine Ecole Cent Nantes IRCCyN CNRS UMR 6597 F-44321 Nantes 3 France

ISBN: (纸本)9781904670063

The integration of customer preferences is nowadays a challenge in new product development. In this paper, we describe a method which integrates the customer preferences for the design of geometrical forms. We illustrate the approach by the design of a car's headlight. From a product space, the method is based on the definition of a perceptual space, built by multidimensional scaling, and which lead to the definition of interpretable perceptual dimensions. Objective measures of the form, computed from the design variables of the design model, are selected to interpret the perceptual dimensions. These measures are representative of the overall form and of the curvature variations. At this level, the Fourier coefficients of a closed curve are used to represent the information on the curvature variations. Next, from the preferences of a customer, the target values of the selected measures corresponding to a preference optimum are calculated. We show in the paper the interest of this approach for the design of forms. The method is illustrated by the design of a car's headlight, modeled by Bezier curves and integrated in a front-end.

关键词： customer centered design perceptual space multidimensional scaling preference modeling form design Fourier coefficients

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Interactive Multiobjective Optimisation: preference Changes and Algorithm Responsiveness 18

Interactive Multiobjective Optimisation: Preference Changes ...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Taylor, Kendall Li, Xiaodong RMIT Univ Sch Sci Melbourne Vic Australia

ISBN: (纸本)9781450356183

For optimisation problems with multiple objectives and large search spaces, it may not be feasible to find all optimal solutions. Even if possible, a decision maker (DM) is only interested in a small number of these solutions. Incorporating a DM's solution preferences into the process reduces the problem's search space by focusing only on regions of interest. Allowing a DM to interact and alter their preferences during a single optimisation run facilitates learning and mistake correction, and improves the search for desired solutions. In this paper, we apply an interactive framework to four leading multi-objective evolutionary algorithms (MOEAs), which use reference points to model preferences. Furthermore, we propose a new performance metric for algorithm responsiveness to preference changes, and evaluate these algorithms using this metric. Interactive algorithms must respond to changes in DM preferences and we show how our new metric is able to differentiate between the four algorithms when run on the ZDT suite of test problems. Finally, we identify characteristics of these methods that determine their level of response to change.

关键词： Interactive optimisation preference modeling Multiobjective optimisation Evolutionary computation

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Context-Aware preference Model Based on a Study of Difference between Real and Supposed Situation Data

Context-Aware Preference Model Based on a Study of Differenc...

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17th International Conference on User modeling, Adaptation and Personalization

作者： Ono, Chihiro Takishima, Yasuhiro Motomura, Yoichi Asoh, Hideki KDDI R&D Labs Inc 2-1-15 Ohara Fujimino Saitama 3568502 Japan AIST Digital Human RC Tokyo 1350064 Japan AIST Intelligent Syst RI Ibaraki 3058568 Japan

ISBN: (纸本)9783642022463

We propose a novel approach for constructing statistical preference models for context-aware recommender systems. To do so, one of the most important but difficult problems is acquiring sufficient training data in various contexts/situations. Particularly, some situations require a heavy workload to set them up or to collect subjects under those situations. To avoid this, often a large amount of data in a supposed situation is collected, i.e., a situation where the subject pretends/imagines that he/she is in a specific situation. Although there may be difference between the preference in the real situation and the supposed situation, this has not been considered in existing researches. Here, to study the difference, we collected a certain amount of corresponding data. We asked subjects the same question about preference both in the real and the supposed situation. Then we proposed a new model construction method using a difference model constructed from the correspondence data and showed the effectiveness through the experiments.

关键词： preference modeling context-awareness recommender systems statistical modeling

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Simulation of preference Information in an Interactive Reference Point-Based Method for the Bi-Objective Inventory Routing Problem

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2015年第1-2期22卷 17-35页

作者： Huber, Sandra Geiger, Martin Sevaux, Marc Helmut Schmidt Univ Logist Management Dept Hamburg Germany Univ Bretagne Sud Ctr Rech Lab STICC F-56321 Lorient France

In the research area of multiple criteria decision making, very few publications exist that explicitly design the simulation of a decision maker (DM) in an interactive approach. For this reason, we outline some methods widely used in the literature to identify common assumptions of simulating the DM's responses and the required input preference information. Our paper aims at covering the identified gap by introducing experimental concepts. Such concepts are used for theoretical analyses of a combined search-and-decision-making procedure. Simulating the DM is a fruitful idea because the algorithm can be tested without integrating a human decision maker. Finally, we conduct experiments based on the proposed settings for a multiobjective inventory routing problem, which is a relevant and challenging logistic problem. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： reference points simulation of the decision maker's responses preference modeling inventory routing problem

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Comparison of Travel Mode Choice Between Taxi and Subway Regarding Traveling Convenience

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Tsinghua Science and Technology 2018年第2期23卷 135-144页

作者： Li Li Shuofeng Wang Meng Li Jiyuan Tan Department of Automation BNRist Tsinghua University Department of Automation Tsinghua University Department of Civil Engineering Tsinghua University Beijing Key Laboratory of Urban Road Intelligent Traffic Control North China University of Technology

In this study, we investigate travel mode choice behavior between taxi and subway with an emphasis on the influence of traveling convenience. In the first stage, we examine the Origin-Destination(OD) points of Beijing taxi trips and compare these locations with the respective nearest subway station. Statistics reveal several interesting conclusions. First, for approximately 24.89% of all trips, no convenient subway connections exist between the OD pairs. As such, a taxi becomes the only viable choice. Second, for 80.23% of the remaining 75.11%of trips(equivalent to 60.26% of all trips), access distance from either the origin or the destination to the nearest subway station is greater than 500 meters. This phenomenon indicates that walking distance plays an important role in travel mode choice. In the second stage, we examine groups of taxi trips with similar travel distances and travel times to reveal common features. We establish a preference rule in terms of travel distance and travel *** determines whether an individual driver will take a taxi or the subway, using a pairwise comparison-based preference regression model. Tests indicate that more than 95% of taxi trips can be correctly predicted by this preference rule. This conclusion reveals that traveling convenience dominates the travel model choice between taxi and subway. All these findings shed light on the factors that influence travel mode choice behavior.

关键词： travel mode choice behaviors taxi subway preference modeling

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Towards multicriteria clustering:: An extension of the k-means algorithm

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2004年第2期158卷 390-398页

作者： De Smet, Y Guzmán, LM Free Univ Brussels Serv Math Gest B-1050 Brussels Belgium

The research within the multicriteria classification field is mainly focused on the assignment of actions to pre-defined classes. Nevertheless the building of multicriteria categories remains a theoretical question still not studied in detail. To tackle this problem, we propose an extension of the well-known k-means algorithm to the multicriteria framework. This extension relies on the definition of a multicriteria distance based on the preference structure defined by the decision maker. Thus, two alternatives will be similar if they are preferred, indifferent and incomparable to more or less the same actions. Armed with this multicriteria distance, we will be able to partition the set of alternatives into classes that are meaningful from a multicriteria perspective. Finally, the examples of the country risk problem and the diagnosis of firms will be treated to illustrate the applicability of this method. (C) 2003 Elsevier B.V. All rights reserved.

关键词： multiple criteria analysis clustering preference modeling k-means algorithm

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Online social image ranking in diversified preferences

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EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2020年第1期2020卷 1-28页

作者： Zhao, Xuezhuan Pei, Lishen Li, Tao Zhang, Zheng Zhengzhou Univ Aeronut Wenyuan Rd Zhengzhou 450046 Peoples R China Henan Univ Econ & Law Jinshui Rd Zhengzhou 450046 Peoples R China Civil Avit Univ China Informat Technol Res Base Civil Aviat Adm Tianjin 300300 Peoples R China HeNan Radio Televis Univ Wenyuan Rd Zhengzhou 450046 Peoples R China

Due to the prevalence of social media service, effective and efficient online image retrieval is in urgent need to satisfy diversified requirements of Web users. Previous studies are mainly focusing on bridging the semantic gap by well-established content modeling with semantic information and social tagging information, but they are not flexible in aggregating the diversified expectations of the online users. In this paper, we present OSIR, a solution framework to facilitate the diversified preference styles in online social media image searching by textual query inputs. First, we propose an efficient Online Multiple Kernel Ranking (OMKR) model which is constructed on multiple query dimensions and complimentary feature channels, and trained by minimizing the triplet loss on hard negative samples. By optimizing the ranking performance with multi-dimensional queries, the semantic consistency between the image ranking and textual query input is directly maximized without relying on the intermediate semantic annotation procedure. Second, we construct random walk-based preference modeling by domain-specific similarity calculation on heterogeneous social attributes. By re-ranking the rank output of OMKR based on each preference ranking model, we obtain a set of ranking lists encoding different potential aspects of user preference. Last, we propose an effective and efficient position-sensitive rank aggregation approach to aggregate multiple ranking results based on the user preference specification. Extensive experiment on two social media datasets demonstrates the advantages of our approach in both retrieval performance and user experience.

关键词： Social media image retrieval Online multiple kernel Ranking preference modeling Rank aggregation

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