scholarly journals Random walk-based similarity measure method for patterns in complex object

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 154-159 ◽  
Author(s):  
Shihu Liu ◽  
Xiaozhou Chen
Keyword(s):  
Random Walk ◽  
Similarity Measure ◽  
Measurement Method ◽  
Calculation Procedure ◽  
Similarity Measurement ◽  
Complex Object ◽  
Complex Objects ◽  
Relational Information ◽  
Object A ◽  
Attribute Information

Abstract This paper discusses the similarity of the patterns in complex objects. The complex object is composed both of the attribute information of patterns and the relational information between patterns. Bearing in mind the specificity of complex object, a random walk-based similarity measurement method for patterns is constructed. In this method, the reachability of any two patterns with respect to the relational information is fully studied, and in the case of similarity of patterns with respect to the relational information can be calculated. On this bases, an integrated similarity measurement method is proposed, and algorithms 1 and 2 show the performed calculation procedure. One can find that this method makes full use of the attribute information and relational information. Finally, a synthetic example shows that our proposed similarity measurement method is validated.

scholarly journals Fuzzy Collaborative Clustering-Based Ranking Approach for Complex Objects

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Shihu Liu ◽  
Xiaozhou Chen ◽  
Tauqir Ahmed Moughal ◽  
Fusheng Yu
Keyword(s):  
Ranking Algorithm ◽  
Ranking Methods ◽  
Complex Objects ◽  
Ranking Problem ◽  
Relational Information ◽  
Individual Attribute ◽  
Collaborative Clustering ◽  
Attribute Information ◽  
Before And After ◽  
The Difference

This paper makes a discussion on the ranking problem of complex objects where each object is composed of some patterns described by individual attribute information as well as the relational information between patterns. This paper presents a fuzzy collaborative clustering-based ranking approach for this kind of ranking problem. In this approach, a referential object is employed to guide the ranking process. To achieve the final ranking result, fuzzy collaborative clustering is carried on the patterns in the referential object by using the collaborative information obtained from each ranked object. Since the collaborative information of ranking objects is represented by cluster centers and/or partition matrices, we give two forms of the proposed approach. With the aid of fuzzy collaborative clustering, the ranking results can be obtained by comparing the difference of the referential object before and after collaboration with respect to ranking objects. One can find that this proposed ranking approach is totally different from the previous ranking methods because of its completely collaborative clustering mechanism. Moreover, some synthetic examples show that our proposed ranking algorithm is valid.

Hierarchical composition in complex object drawing

2019 ◽  
Author(s):  
Michiru Makuuchi
Keyword(s):  
Hierarchical Structure ◽  
Homo Sapiens ◽  
Hierarchical Structures ◽  
Target Object ◽  
Point Of View ◽  
Complex Object ◽  
Complex Objects ◽  
Cognitive Domains ◽  
Adult Participants ◽  
Symbolic Cognition

Symbolic behaviours such as language, music, drawing, dance, etc. are unique to humans and are found universally in every culture on earth1. These behaviours operate in different cognitive domains, but they are commonly characterised as linear sequences of symbols2,3. One of the most prominent features of language is hierarchical structure4, which is also found in music5,6 and mathematics7. Current research attempts to address whether hierarchical structure exists in drawing. When we draw complex objects, such as a face, we draw part by part in a hierarchical manner guided by visual semantic knowledge8. More specifically, we predicted how hierarchical structure emerges in drawing as follows. Although the drawing order of the constituent parts composing the target object is different amongst individuals, some parts will be drawn in succession consistently, thereby forming chunks. These chunks of parts would then be further integrated with other chunks into superordinate chunks, while showing differential affinity amongst chunks. The integration of chunks to an even higher chunk level repeats until finally reaching the full object. We analysed the order of drawing strokes of twenty-two complex objects by twenty-five young healthy adult participants with a cluster analysis9 and demonstrated reasonable hierarchical structures. The results suggest that drawing involves a linear production of symbols with a hierarchical structure. From an evolutionary point of view, we argue that ancient engravings and paintings manifest Homo sapiens’ capability for hierarchical symbolic cognition.

scholarly journals Knowledge Service Technology for Supporting Intelligent Product Design

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haiqiao Wang ◽  
Ruikun Niu
Keyword(s):  
Decision Making ◽  
Intelligent Design ◽  
Measurement Method ◽  
Numerical Control ◽  
Similarity Measurement ◽  
Case Based Reasoning ◽  
Knowledge Service ◽  
Knowledge Based ◽  
Weight Coefficients ◽  
Case Based

In this paper, a knowledge service method that supports the intelligent design of products is investigated. The proposed method provides the solutions to computational problems and reasoning and decision-making problems in the field of intelligent design. The requirement analysis of a knowledge-based intelligent design system integrates design knowledge into case-based reasoning activities through scheme analysis, scheme evaluation, and scheme adjustment, thus achieving knowledge-based intelligent reasoning and decision-making. During the similarity matching, a new hybrid similarity measurement method is proposed to calculate the similarity of crisp and fuzzy sets. This method integrates the fuzzy set similarity theory based on the traditional similarity measurement method. A method of attribute level classification is proposed to assign weight coefficients. The attributes are divided into the primary matching and auxiliary matching levels according to the decisiveness of case matching, and the set of weight coefficients is continuously and dynamically updated through case-based reasoning learning. Then, the weighted global similarity measure is used to obtain the set of similar cases from the case database. Finally, a design example of a computer numerical control tool holder product is studied to present the practicability and effectiveness of the proposed method.

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