E cient and accurate information retrieval is one of the main issues in multimedia databases. In content-based multimedia retrieval databases, contents or features of the database objects are used for retrieval. To retrieve similar database objects, we often perform a nearest-neighbor search. A nearest-neighbor search is used to retrieve similar database objects with features nearest to the que...

Over the past decade, many fields of discovery have begun to use motion capture data, leading to an exponential growth in the size of motion databases. Querying, indexing and retrieving motion capture data has thus become a crucial problem for the accessibility and usability of such databases. Our aim is to make this approach feasible for virtual agents signing in French Sign Language, taking i...

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) oper...

Graph has become increasingly important in modeling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is desirable to retrieve graphs quickly from a large database via graph-based indices. Different from the existing methods, our approach, called VFM (Vertex to Frequent Feature Mapping), makes use of vertices and decision...

A user who wants to get knowledge from a relational database that needs to know about structured query languages and database schema. Mostly users are not know to those things, so searching knowledge from relational databases is difficult to them. Where a keyword query input is a simple search model that can be issued by writing a list of keywords values, keyword search that place provide a sol...

We have a large database consisting of user proole information together with behavioral patterns. We introduce the concept of proole association rules, which discusses the problem of relating consumer buying behavior to behavioral information. We investigate the problem of online mining of proole association rules in this large database. We show how to use multidimensional indexing structures i...

The results discussed in this paper are relevant to a large database consisting of consumer profile information together with behavioral (transaction) patterns. The focus of this paper is on the problem of onhne mining of profile association rules in this large database. The profile association rule problem is closely related to the quantitative association rule problem. We show how to use mult...

In this paper we describe indexing techniques based on domain knowledge made available in the form of ontologies. In high level interfaces like those used in many data warehousing applications, it is advantageous to use terminology familiar to the enduser of the system. This terminology is very often different from the one incorporated in the underlying database. Much of the terminology (i.e. c...

The use of the second order statistical measures has became popular in the image database indexing and retrieval. Unlike the common approach, image histogram, second order statistics like image correlogram and autocorrelogram consider also the spatial organization of the image colors or gray levels. Recently, correlograms and autocorrelograms have been widely used in the image database indexing...

Managing the ever rapidly increasing image data is a very challenging task, which can be roughly divided into user side and computer side issues. Although fundamental problems on the computer side of the challenge, such as image content representation, similarity matching and intelligent retrieval have received extensive research effort, equally important and difficult issues on the user side, ...