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Results 1 - 10
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2,521
Data Mining: An Overview from Database Perspective
- IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
, 1996
"... Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields have sh ..."
Abstract
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Cited by 532 (26 self)
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Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields have
Formal Ontology and Information Systems
, 1998
"... Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We sh ..."
Abstract
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Cited by 897 (11 self)
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Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We
Local grayvalue invariants for image retrieval
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficie ..."
Abstract
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Cited by 548 (27 self)
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for efficient retrieval from a database of more than 1,000 images. Experimental results show correct retrieval in the case of partial visibility, similarity transformations, extraneous features, and small perspective deformations. Index Terms—Image retrieval, image indexing, graylevel invariants, matching
An affine invariant interest point detector
- In Proceedings of the 7th European Conference on Computer Vision
, 2002
"... Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape of ..."
Abstract
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Cited by 1467 (55 self)
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comparison of our detector with existing ones shows a significant improvement in the presence of large affine deformations. Experimental results for wide baseline matching show an excellent performance in the presence of large perspective transformations including significant scale changes. Results
Database Mining: A Performance Perspective
- IEEE Transactions on Knowledge and Data Engineering
, 1993
"... We present our perspective of database mining as the confluence of machine learning techniques and the performance emphasis of database technology. We describe three classes of database mining problems involving classification, associations, and sequences, and argue that these problems can be unifor ..."
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Cited by 345 (13 self)
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We present our perspective of database mining as the confluence of machine learning techniques and the performance emphasis of database technology. We describe three classes of database mining problems involving classification, associations, and sequences, and argue that these problems can
Triangulation of Bayesian Networks: a Relational Database Perspective
"... In this paper, we study the problem of triangulation of Bayesian networks from a relational database perspective. We show that the problem of triangulating a Bayesian network is equivalent to the problem of identifying a maximal subset of conflict free conditional independencies. ..."
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Cited by 3 (1 self)
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In this paper, we study the problem of triangulation of Bayesian networks from a relational database perspective. We show that the problem of triangulating a Bayesian network is equivalent to the problem of identifying a maximal subset of conflict free conditional independencies.
Data Mining: A Database Perspective.
- in Proc. Int. Conf. Data Mining
, 1998
"... Data mining on large databases has been a major concern in research community, due to the difficulty of analyzing huge volumes of data using only traditional OLAP tools. This sort of process implies a lot of computational power, memory and disk I/O, which can only be provided by parallel computers. ..."
Abstract
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Cited by 6 (0 self)
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Data mining on large databases has been a major concern in research community, due to the difficulty of analyzing huge volumes of data using only traditional OLAP tools. This sort of process implies a lot of computational power, memory and disk I/O, which can only be provided by parallel computers
Querying rdf data from a graph database perspective
- In Proceedings of the Second European Semantic Web Conference
, 2005
"... Abstract. This paper studies the RDF model from a database perspective. From this point of view it is compared with other database models, particularly with graph database models, which are very close in motivations and use cases to RDF. We concentrate on query languages, analyze current RDF trends, ..."
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Cited by 54 (5 self)
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Abstract. This paper studies the RDF model from a database perspective. From this point of view it is compared with other database models, particularly with graph database models, which are very close in motivations and use cases to RDF. We concentrate on query languages, analyze current RDF trends
Survey of clustering data mining techniques
, 2002
"... Accrue Software, Inc. Clustering is a division of data into groups of similar objects. Representing the data by fewer clusters necessarily loses certain fine details, but achieves simplification. It models data by its clusters. Data modeling puts clustering in a historical perspective rooted in math ..."
Abstract
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Cited by 408 (0 self)
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Accrue Software, Inc. Clustering is a division of data into groups of similar objects. Representing the data by fewer clusters necessarily loses certain fine details, but achieves simplification. It models data by its clusters. Data modeling puts clustering in a historical perspective rooted
When Is "Nearest Neighbor" Meaningful?
- In Int. Conf. on Database Theory
, 1999
"... . We explore the effect of dimensionality on the "nearest neighbor " problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance ..."
Abstract
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Cited by 408 (2 self)
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the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never
Results 1 - 10
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2,521
