Web Text Clustering and Evaluation Algorithm Based on Fuzzy Set

2013 ◽  
Vol 7 (1) ◽  
pp. 11-18
Author(s):  
Yun Peng ◽  
Hongxin Wan
Keyword(s):  
Fuzzy Set ◽  
Text Clustering ◽  
Evaluation Algorithm

Fuzzy Set Based Clustering Algorithm of Web Text

2014 ◽  
Vol 678 ◽  
pp. 19-22
Author(s):  
Hong Xin Wan ◽  
Yun Peng
Keyword(s):  
Key Words ◽  
Fuzzy Set ◽  
Clustering Algorithm ◽  
Text Clustering ◽  
Classification Methods ◽  
Comparative Experiment ◽  
Fuzzy Algorithm ◽  
Pattern Clustering ◽  
The Web ◽  
Computing Accuracy

Web text exists non-certain and non-structure contents ,and it is difficult to cluster the text by normal classification methods. We propose a web text clustering algorithm based on fuzzy set to increase the computing accuracy with the web text. After abstracting the key words of the text, we can look it as attributes and design the fuzzy algorithm to decide the membership of the words. The algorithm can improve the algorithm complexity of time and space, increase the robustness comparing to the normal algorithm. To test the accuracy and efficiency of the algorithm, we take the comparative experiment between pattern clustering and our algorithm. The experiment shows that our method has a better result.

A Fuzzy Algorithm of Customers Evaluation Based on Attributes Reduction

2013 ◽  
Vol 278-280 ◽  
pp. 1287-1291 ◽  
Author(s):  
Hong Xin Wan ◽  
Yun Peng
Keyword(s):  
Fuzzy Set ◽  
Clustering Analysis ◽  
Incomplete Data ◽  
Traditional Method ◽  
Uncertain Data ◽  
Fuzzy Algorithm ◽  
Customer Evaluation ◽  
Evaluation Algorithm ◽  
Clustering Data ◽  
Data Objects

A fuzzy algorithm of customers evaluation based on attributes reduction is presented. The evaluation from the data objects based on key attributes can reduce the data size and algorithm complexity. After Clustering analysis of customers, then the evaluation analysis will process to the clustering data. There are a lot of uncertain data of customer cluster, so the traditional method of classification and evaluation to the incomplete data is very difficult. Superposition evaluation algorithm based on fuzzy set can improve the reliability and accuracy of e-commerce customer evaluation. Evaluation of the e-commerce customer also can improve efficiency, service quality and profitability of e-commerce businesses.

A Fuzzy Set AHP-Based DFM Tool under Concurrent Engineering Environment

2007 ◽  
Vol 10-12 ◽  
pp. 145-149 ◽  
Author(s):  
H.G. Liu ◽  
Rong Mo ◽  
Qing Ming Fan ◽  
Zhi Yong Chang ◽  
Y. Zhao
Keyword(s):  
Fuzzy Set ◽  
Concurrent Engineering ◽  
Evaluation System ◽  
Smooth Transition ◽  
Analytic Hierarchy ◽  
Design And Manufacturing ◽  
Evaluation Algorithm ◽  
Engineering Environment ◽  
Engineering Effort ◽  
Manufacturability Evaluation

In the light of growing global competition, organizations around the world today are constantly under pressure to produce high-quality products at an economical price. The integration of design and manufacturing activities into one common engineering effort has been recognized as a key strategy for survival and growth. Design for manufacturability (DFM) is an approach to design that fosters the simultaneous involvement of product design and process design. The implementation of the DFM approach requires the collaboration of both the design and manufacturing functions within an organization. At present, For some reasons DFM approach is ineffectively including lack of interdisciplinary expertise of designers; inflexibility in organizational structure, which hinders interaction between design and manufacturing functions. Design for manufacture is the practice of designing products with manufacturing in mind. Early consideration of manufacturing issues can shorten product development cycle time, minimi overall development cost and ensure a smooth transition into production. In this paper, part manufacturability under Concurrent Engineering (CE) environment was analyzed in detail. An evaluation system of DFM was proposed according to CE ideas. A fuzzy set-based manufacturability evaluation algorithm is formulated to generate relative manufacturability indices to provide product designers with a better understanding of the relative ease or difficulty of machining the features in their designs. An analytic hierarchy process (AHP) method is introduced to assign weighting factors to features to reflect their functional importance. Results from the case studies show the method available and practicable.

A Fuzzy Clustering Algorithm of Web Customers Based on Attributes Reduction

2014 ◽  
Vol 989-994 ◽  
pp. 1775-1778
Author(s):  
Hong Xin Wan ◽  
Yun Peng
Keyword(s):  
Rough Set ◽  
Fuzzy Set ◽  
Incomplete Data ◽  
Traditional Method ◽  
Clustering Algorithm ◽  
Uncertain Data ◽  
Attribute Reduction ◽  
Fuzzy Clustering Algorithm ◽  
Evaluation Algorithm ◽  
Data Objects

The evaluation algorithm is based on the attributes of data objects. There is a certain correlation between attributes, and attributes are divided into key attributes and secondary attributes. This paper proposes an algorithm of attribute reduction based on rough set and the clustering algorithm based on fuzzy set. The algorithm of attributes reduction based on rough set is described in detail first. There are a lot of uncertain data of customer clustering, so traditional method of classification to the incomplete data will be very complex. Clustering algorithm based on fuzzy set can improve the reliability and accuracy of web customers.

Rough and Fuzzy Set Based Classification Algorithm on Computer Practice Teaching Evaluation

2014 ◽  
Vol 678 ◽  
pp. 43-46
Author(s):  
Hong Xin Wan ◽  
Yun Peng
Keyword(s):  
Rough Set ◽  
Fuzzy Set ◽  
Evaluation System ◽  
Clustering Algorithm ◽  
Teaching Evaluation ◽  
Key Factors ◽  
Clustering Method ◽  
Practice Teaching ◽  
Evaluation Algorithm ◽  
Computer Teaching

Computer teaching should emphasize the engineering practicality, creativity, and pay more attention to the project and its application. It is important to evaluate the teaching effect. An evaluation system and corresponding algorithm are presented in this paper. There is a certain correlation between some evaluation factors, and the factors can be divided into key factors and secondary factors by rough set. The evaluation algorithm based on the key factors can reduce redundant factors and improve the efficiency. We designed a clustering algorithm based on fuzzy set on evaluation entities, which can reduce the dada size and improve the accuracy of the algorithm. Through the example analysis the algorithm of factors reduction based on rough set and clustering method based on fuzzy set are described in detail.

Is Psychology a Science or a Fuzzy Set?

1978 ◽  
Vol 23 (5) ◽  
pp. 319-320
Author(s):  
LEWIS WOLFGANG BRANDT
Keyword(s):  
Fuzzy Set

Methodology of ECG Interpretation in the Padova Program

1990 ◽  
Vol 29 (04) ◽  
pp. 386-392 ◽  
Author(s):  
R. Degani ◽  
G. Bortolan
Keyword(s):  
Decision Making ◽  
Medical School ◽  
Fuzzy Set ◽  
Medical Knowledge ◽  
Main Aspect ◽  
Measurement Evaluation ◽  
Possibility Distributions ◽  
Linguistic Decision Making ◽  
The University ◽  
Ecg Interpretation

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.

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