Add to ORKGA method of representing a group of data items comprises, for each of a plurality of data items in the group, determining the similarity between said data item and each of a plurality of other data items in the group, assigning a rank to each pair on the basis of similarity, wherein the ranked similarity values for each of said plurality of data items are associated to reflect the overall relative similarities of data items in the group
International audienceWe propose a meta-heuristic algorithm for clustering objects that are describe...
Dataset interlinking is a great important problem in Linked Data. We consider this problem from the ...
We propose a partial ordering that approximates a ranking of the items in a database according to t...
A method of representing a group of data items comprises, for each of a plurality of data items in t...
A method of similarity clusters detection in large visual databases is described in this work. Simil...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
In this paper we employ human judgments of image similarity to improve the organization of an image ...
This report develops and demonstrates algorithms for representing and displaying similarity data usi...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
edu.tw In this paper, a multiple-instance image retrieval system incorporating a general spatial sim...
In this paper, we present a methodology on how to measure the visual similarity between a query imag...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
This work introduces a new class of group similarity where different measures are parameterized with...
A very natural approach to categorization is similarity-based clustering. We propose a visual repres...
The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large numbe...
International audienceWe propose a meta-heuristic algorithm for clustering objects that are describe...
Dataset interlinking is a great important problem in Linked Data. We consider this problem from the ...
We propose a partial ordering that approximates a ranking of the items in a database according to t...
A method of representing a group of data items comprises, for each of a plurality of data items in t...
A method of similarity clusters detection in large visual databases is described in this work. Simil...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
In this paper we employ human judgments of image similarity to improve the organization of an image ...
This report develops and demonstrates algorithms for representing and displaying similarity data usi...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
edu.tw In this paper, a multiple-instance image retrieval system incorporating a general spatial sim...
In this paper, we present a methodology on how to measure the visual similarity between a query imag...
In this paper our goal is to employ human judgments of image similarity to improve the organization ...
This work introduces a new class of group similarity where different measures are parameterized with...
A very natural approach to categorization is similarity-based clustering. We propose a visual repres...
The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large numbe...
International audienceWe propose a meta-heuristic algorithm for clustering objects that are describe...
Dataset interlinking is a great important problem in Linked Data. We consider this problem from the ...
We propose a partial ordering that approximates a ranking of the items in a database according to t...