This paper describes a graph-matching technique for recognising line-pattern shapes in large image databases. We use a Bayesian matching algorithm that draws on edge-consistency and node attribute similarity. This information is used to determine the a posteriori probability of a query graph for each of the candidate matches in the data-base. The node featurevectors are constructed by computing...

A new method for solving intuitionistic fuzzy multi-attribute decision making problem is proposed, in which the information of attribute weights is incompletely known. Considering much information about hesitancy and vagueness inherited to intuitionistic fuzzy sets, a new class of distance for describing the deviation degrees between intuitionistic fuzzy sets is introduced. Furthermore, the mea...

The increasing popularity of graph data in various domains has lead to a renewed interest in developing efficient graph matching techniques, especially for processing large graphs. In this paper, we study the problem of approximate graph matching in a large attributed graph. Given a large attributed graph and a query graph, we compute a subgraph of the large graph that best matches the query gr...

In this paper, for the low similarity computation accuracy of concept in the field of agriculture ontology mapping, formal concept analysis theory and rough set theory are introduced to similarity computation. Jointly considering attribute hierarchies in concept lattice, the semantic hierarchy of the concepts are weighted differently, and the theory and methods of similarity calculation of roug...

Representing and consequently processing fuzzy data in standard and binary databases is problematic. The problem is further amplified in binary databases where continuous data is represented by means of discrete ‘1’ and ‘0’ bits. As regards classification, the problem becomes even more acute. In these cases, we may want to group objects based on some fuzzy attributes, but unfortunately, an appr...

This paper describes a graph-matching technique for recognising line-pattern shapes in large image databases. The methodological contribution of the paper is to develop a Bayesian matching algorithm that uses edge-consistency and node attribute similarity. This information is used to determine the a posteriori probability of a query graph for each of the candidate matches in the database. The n...

The research paper proposes the relevance of a distance-based approach for change mining and suggests a technique for distance-based change mining. Change mining gives an insight to the retailers on the changing purchase behavior of the shoppers. The research makes an attempt to account for the distance between the attribute-values within a feature of the customer-profile while measuring the si...

We introduce attribute and relational representations of mosaic image models with directed relationships between regions. Attribute asymmetric based on stacking, ranking integral descriptions are considered. propose some morphological shape similarity measures models. show that using the same oriented model, various operators can be constructed, in particular, Serra- or Pyt’ev type. Some constr...

We present a preliminary study on the problem of finding products similar to a product given as input, based solely on their attributes. We assume that we are given a set of products from a same category of a same on-line store, were each product is described in a catalog by a number of attributes (e.g., general characteristics, technical specifications, etc.). This problem, which at a first gl...