This article has analyzed characteristic and coding method of the product information,absorb the idea of the product classify attribute and use it for reference,bring forward the coding and method of the product classify attribute under the CIMS environment,it is provided with agile conformation competence and comprehensive practicability very much;
base on the principle and method,an application example is given in the paper. By the unitive product classify attribute coding and information relationship technology,realize the efficient integration of the product information.
This paper propose s two distance definitions for attribute-mixed dataset,and generalizes dissimilarity to multi-function of distance and cluster size,the new distance and dissimilarity definitions make existed clustering algorithms for numerical attribute or categorical attribute can be used to attribute-mixed dataset.
Considering the size of quantitative attribute values and categorical attribute values in databases, the paper presents two quantitative association rules mining methods considering privacy-preserving respectively, one bases on boolean association rules, the other bases on partially transform measure.
ROCK,proposed by Sudipno Guha et al in 1999,is a well known,robust,categorical attribute oriented clustering algorithm. The main contribution of ROCK is the introduction of a novel concept called "common neighbors"(links) as similarity measure between a pair of data points. Compared with traditional distance-based approaches,links capture global information over the whole data set rather than local information between two data points.
The measure of similarity is the key to solve clustering problem. Aiming to the shortage of traditional method, Information entropy theory is introduced to solve intrusion detection clustering problem that includes categorical attributes.
This paper discusses how to deal with the clustering problem with categorical attributes by means of the theory of similarity coefficients and the theory of entropy, and emphatically studies the equivalence of the two similarity measures in resolving the clustering problem for intrusion detection.
last, we compare the system use thesaurus which contains category attributes with the system use thesaurus which neglects category attributes, the experiment demonstrates that category attributes and classification contributes to the efficiency of Chinese input method.
These implementations use rudimentary metadata representing measurement-theoretical and category attribute information to support error checking of data derivations common in research and reference using social science data.
Let dt be a terminal attribute, dp a property attribute, and dc a category attribute of a common dimension.
This data includes least count for numeric attributes and category attribute trees and the auxiliary data required for key derivation.
In this paper, we formulate the problem of summarization of a data set of transactions with categorical attributes as an optimization problem involving two objective functions - compaction gain and information loss.
The k-prototypes algorithm, through the definition of a combined dissimilarity measure, further integrates the k-means and k-modes algorithms to allow for clustering objects described by mixed numeric and categorical attributes.
Categorical attributes are typically ignored or incorrectly modeled by existing approaches, resulting in a significant loss of information.
We report on a new, efficient encoding for the data cube, which results in a drastic speed-up of OLAP queries that aggregate along any combination of dimensions over numerical and categorical attributes.
Identifier attributes-very high-dimensional categorical attributes such as particular product ids or people's names-rarely are incorporated in statistical modeling.