Customer requirement preference is an important part of customer satisfaction. In view of similar case retrieval technology for existing product level, in the process of solving similar cases, there ...is no consideration for customer requirement preference. This article proposes a similar case solution method considering customer requirement preference. First, we deal with the expression of customer requirements and transform them into operable parameter forms according to the mapping model. Second, the preference graph is used to analyze the customer’s requirement preference, to determine the preference weight, and to weigh the final weight of the requirement node with the initial weight determined by the fuzzy analytic hierarchy process. Finally, the similarity degree solving model of requirement node and product case attribute parameters is established. By integrating the weights of the above-mentioned nodes, the similarity of the product case is obtained, and a more satisfied case of the customer is obtained. Taking the automated guided vehicle car product as an example, the effectiveness of the proposed method is verified.
Resolving Zeckhauser’s paradox Pawitan, Yudi; Isheden, Gabriel
Theory and decision,
05/2020, Volume:
88, Issue:
4
Journal Article
Peer reviewed
Open access
Zeckhauser’s paradox has puzzled and entertained many rationality enthusiasts for almost half a century. You are forced to play a Russian Roulette with a 6-chamber revolver containing either (A) two ...bullets, or (B) four bullets. Would you pay more to remove the two bullets in (A) than you would to remove one in (B)? Most would say yes, but rational considerations based on the classical utility theory suggest you should not. We discuss a possible solution within the classical framework, by explicitly stating and accounting for more detailed preferences in terms of fewer bullets and smaller debt. To a large extent, the paradox arises due to a surreptitious trespassing of Savage’s Small-World utilities implied by a limited set of preferences to govern a larger world containing potentially conflicting preferences. To avoid logical issues associated with death in the roulette, we also describe a non-fatal game-show version, where you choose one box out of six that could be either empty or contain prize money. Here, the paradox arises when you pay from the prize money, but not when you pay from your own money. In summary, the paradox provides a useful lesson about the normative role of the utility function as a rational guide for our decisions and preferences.
Nowadays, effective and accurate analysis of customer requirements (CRs) is vital in the new product development process, especially in the early design stage, where corresponding changes can be made ...easily into the further development stages. Quality function deployment (QFD), acting as a customer-centric product development tool, is widely utilized in the product planning stage. Despite its "House of Quality" (HoQ) matrix support, it lacks a specific method in analyzing incomplete or imprecise customer preference of CRs. Though many methods have been proposed, they either required much elaborate information (not effective) or relied much on the subjective interpretations by designers (not accurate). Aiming to solve the problem, this paper introduces a novel weighted preference graph (PG) approach to analyze incomplete customer preference information in QFD product planning stage. Both its analysis procedures and fusion of individual perceptions are described. An example of a respiratory mask development is given to validate the process.
The group ranking problem consists of constructing coherent aggregated results from preference data provided by decision makers. Traditionally, the output of a group ranking problem can be classified ...into ranking lists and maximum consensus sequences. In this study, we propose a consensus preference graph approach to represent the coherent aggregated results of users' preferences. The advantages of our approach are that (1) the graph is built based on users' consensuses, (2) the graph can be understood intuitively, and (3) the relationships between items can be easily seen. An algorithm is developed to construct the consensus preference graph from users' total ranking data. Finally, extensive experiments are carried out using synthetic and real data sets. The experimental results indicate that the proposed method is computationally efficient, and can effectively identify consensus graphs.
► This study proposes a new output type of group ranking problem. ► The new output is a consensus preference graph of items. ► The output graph can be understood intuitively and the relationships between items can be easily seen. ► The experimental results show that the proposed method is efficient and effective.
Meeting Scheduling Problem (MSP) arranges meetings between a number of participants. Reaching consensus in arranging a meeting is very diffuclt and time-consuming when the number of participants is ...large. One efficient approach for overcoming this problem is the use of multi-agent systems. In a multi-agent system, agents are deciding on behalf of their users. They must be able to elicite their users’ preferences in an effective way. This paper focuses on the elicitation of users’ preferences. Analytical hierarchy process (AHP) - which is known for its ability to determine preferences - is used in this research. Specifically, an adaptive preference modeling technique based on AHP is developed and implemented in a system and the initial validation results are encouraging.
NLP is a branch of artificial intelligence that en-compasses various tasks related to language, enabling computers to communicate with people in a human-like manner. NLP facilitates functions such as ...text reading, voice comprehension, analysis, and key point identification. Analyzing human language requires employing diverse methodologies within NLP, ranging from statistical and machine learning techniques to rules-based and algorithmic approaches. This research paper highlights a few approaches like LSTM, Seq2Seq models, Neural Machine Translation, Acoustic Modelling, and Connectionist Temporal Classification. The need for a wide range of methodologies arises due to the varying nature of text- and voice-based data and the diverse practical applications of NLP. Although NLP presents challenges, significant progress has been made in recent years. With the continuous development of computers, they are approaching the ability to comprehend basic human language.
We present a formal framework for the processing of preference queries over large data tables, in which user preferences are expressed as comparisons between attribute values (e.g. “I prefer Red to ...Black”).The main contributions of the paper are as follows: (a) a formal framework for the statement of the problem, under no restrictions whatsoever on the preferences expressed by the user, (b) a rewriting algorithm that takes as input a preference query and returns a sequence of ordinary sub-queries whose evaluations construct the answer to the preference query, (c) a general definition of “skyline” and (d) a user-friendly interface supporting preference query formulation and incremental query evaluation with on-the-fly modification.
Locating the “right” piece of information among a wide range of available alternatives is not an easy task, as everyone has experienced at least once during his/her lifetime. In this paper we look at ...some recent issues arising when a database query is extended so as to include user preferences, which ultimately determine whether one alternative is reputed by the user better than another one. In particular, we focus on the case of qualitative preference queries, that strictly include well-known skyline queries, and describe how one can take advantage of the sorting machinery of standard database engines to speed-up evaluation both in centralized and distributed scenarios.
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