作者:
ROY, BUNIV PARIS 09
PL DU MARECHAL DE LATTRE DE TASSIGNYF-75775 PARIS 16FRANCE
In the first part of this paper, we describe the main features of real-world problems for which the outranking approach is appropriate and we present the concept of outranking relations. The second part is devoted to ...
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In the first part of this paper, we describe the main features of real-world problems for which the outranking approach is appropriate and we present the concept of outranking relations. The second part is devoted to basic ideas and concepts used for building outranking relations. The definition of such outranking relations is given for the main ELECTRE methods in Part 3. The final part of the paper is devoted to some practical considerations.
In a multicriteria decision problem it may happen that the preference of the decision-maker on some criterion is modeled by means of a semiorder structure. If the available information is qualitative, one often needs ...
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In a multicriteria decision problem it may happen that the preference of the decision-maker on some criterion is modeled by means of a semiorder structure. If the available information is qualitative, one often needs a numerical representation of the semiorder. We investigate the set of representations of a semiorder and show that, once a unit has been fixed, there exists a minimal representation. This representation can be calculated by linear programming and exhibits some interesting properties: all values are integer multiples of the unit and are as scattered as possible in the sense that, in the set of all representations contained in the same bounded interval, the minimal representation is a representation for which the minimal distance between two values is maximal. The minimal representation can also be interpreted as a generalisation of the rank function associated to linear orders.
作者:
De Mol, RobinDe Tre, GuyUniv Ghent
Fac Engn & Architecture Dept Telecommun & Informat Proc Databases Documents & Content Management Res Grp Sint Pietersnieuwstr 41 B-9000 Ghent Belgium
Some industrial purposes require specific marine resources. Companies rely on information from resource models to decide where to go and what the cost will be to perform the required extractions. Such models, however,...
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ISBN:
(纸本)9783319914732;9783319914725
Some industrial purposes require specific marine resources. Companies rely on information from resource models to decide where to go and what the cost will be to perform the required extractions. Such models, however, are typical examples of imprecise data sets wherein most data is estimated rather than measured. This is especially true for marine resource models, for which acquiring real data samples is a long and costly endeavor. Consequently, such models are largely computed by interpolating data from a small set of measurements. In this paper, we discuss how we have applied fuzzy set theory on a real data set to deal with these issues. It is further explained how the resulting fuzzy model can be queried so it may be used in a decision making context. To evaluate queries, we use a novel preference modeling and evaluation technique specifically suited for dealing with uncertain data, based on suitability distributions. The technique is illustrated by evaluating an example query and discussing the results.
The problematic addressed in this article is dealing with the improvement of retrieval in Case-Based Reasoning for system design. The retrieval activity is based on the evaluation of similarities between requirements ...
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ISBN:
(纸本)9781467329453
The problematic addressed in this article is dealing with the improvement of retrieval in Case-Based Reasoning for system design. The retrieval activity is based on the evaluation of similarities between requirements (target) and the solutions (sources). However, similarities between features is often a subjective kind of knowledge difficult to formalize within companies. Based on an ontology of domain, the approach permits to retrieve compatible solutions rather than similar ones using a model of designer preferences. The requirements are modeled by means of constraints. When constraints are confronted to solutions in order to evaluate a compatibility measure, missing information within solutions with regard to requirements are taken into account using semantic similarities between concepts. A case study validates the proposals.
The emerging of sequential recommender (SR) has attracted increasing attention in recent years, which focuses on understanding and modeling the temporal dynamic of user behaviors hidden in the sequence of user-item in...
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ISBN:
(纸本)9783030757656;9783030757649
The emerging of sequential recommender (SR) has attracted increasing attention in recent years, which focuses on understanding and modeling the temporal dynamic of user behaviors hidden in the sequence of user-item interactions. However, with the tremendous increase of users and items, SR still faces several challenges: (1) the hardness of modeling user interests from spare explicit feedback;(2) the time and semantic irregularities hidden in the user's successive actions. In this study, we present a neural network-based sequential recommender model to learn the temporal-aware user preferences and item popularity jointly from reviews. The proposed model consists of the semantic extracting layer and the dynamic feature learning layer, besides the embedding layer and the output layer. To alleviate the data sparse issue, the semantic extracting layer focuses on exploiting the enriched semantic information hidden in reviews. To address the time and semantic irregularities hidden in user behaviors, the dynamic feature learning layer leverages convolutional fitters with varying size, integrating with a time-ware controller to capture the temporal dynamic of user and item features from multiple temporal dimensions. The experimental results demonstrate that our proposed model outperforms several state-of-art methods consistently.
Deep Learning (DL) models are increasingly dealing with heterogeneous data (i.e., a mix of structured and unstructured data), calling for adequate eXplainable Artificial Intelligence (XAI) methods. Nevertheless, only ...
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ISBN:
(纸本)9783031700736;9783031700743
Deep Learning (DL) models are increasingly dealing with heterogeneous data (i.e., a mix of structured and unstructured data), calling for adequate eXplainable Artificial Intelligence (XAI) methods. Nevertheless, only some of the existing techniques consider the uncertainty inherent to the data. To this end, this study proposes a pipeline to explain heterogeneous data-based DL models by combining embedding analysis, rule extraction methods, and probabilistic models. The proposed pipeline has been tested using synthetic data (multi-individual food items tracking). This study has achieved (i) inference enhancement through probabilistic and evidential reasoning, (ii) generation of logical explanations based on extracted rules and predictions, and (iii) integration of textual data into the explanation pipeline through embedding analysis.
An increasing number of websites, such as Trip Advisor, reflecting the multilateral nature of their products, provide visitors with the possibility to evaluate each item on more than one criterion. The rating scale us...
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ISBN:
(纸本)9781479929023
An increasing number of websites, such as Trip Advisor, reflecting the multilateral nature of their products, provide visitors with the possibility to evaluate each item on more than one criterion. The rating scale used usually is represented by a lexical or symbolic scale, such as the five-star rating system. Such scales can be regarded as interval because the symbolic or lexical semantics convey information about the strength of user preferences in addition to their order. In this paper we present I-Rec, a new multi-criteria, model-based recommender system tailored to interval scale ratings, which provides improved results over similar state of the art multi-criteria methods.
In Business Process Management Systems, human resource management typically covers two steps: resource assignment at design time and resource allocation at run time. Although concepts like role-based assignment often ...
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ISBN:
(纸本)9783642450051;9783642450044
In Business Process Management Systems, human resource management typically covers two steps: resource assignment at design time and resource allocation at run time. Although concepts like role-based assignment often yield several potential performers for an activity, there is a lack of mechanisms for prioritizing them, e. g., according to their skills or current workload. In this paper, we address this research gap. More specifically, we introduce an approach to define resource preferences grounded on a validated, generic user preference model initially developed for semantic web services. Furthermore, we show an implementation of the approach demonstrating its feasibility.
Many engineering and marketing tools exist to help a designer optimize quantitative attributes of a product, such as height, weight, volume, or cost. However, these methods cannot effectively take into consideration a...
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ISBN:
(纸本)9781904670216
Many engineering and marketing tools exist to help a designer optimize quantitative attributes of a product, such as height, weight, volume, or cost. However, these methods cannot effectively take into consideration attributes for which there is a significant interaction between the product attributes with respect to the consumer's preference, such as aesthetics. This research has begun the work of developing this necessary functional relationship for product attribute interactions and has created a methodology for further research. To accomplish this, this study considered consumer preference for product colors. Colors were represented by their red, green, and blue light components, and preference information for each of these attributes was gathered by presenting individuals with a small sample of colors, applied to backpacks, in a short choice survey.
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