100 Result(s)
within
English
Computer Science
Information Storage and Retrieval
**u Tao
Article
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Article
Diachronic Analysis of Fuzzy Objects
This paper presents a method to monitor the behavior of fuzzy spatial objects through time. The method consists of two steps. Firstly the spatial extents of objects are determined at several sequential epochs....
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Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these techniques, including reliance on ...
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Semisupervised learning from different information sources
This paper studies the use of a semisupervised learning algorithm from different information sources. We first offer a theoretical explanation as to why minimising the disagreement between individual models co...
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Optimizing complex queries based on similarities of subqueries
As database technology is applied to more and more application domains, user queries are becoming increasingly complex (e.g. involving a large number of joins and a complex query structure). Query optimizers i...
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A Mathematical Morphology Based Scale Space Method for the Mining of Linear Features in Geographic Data
This paper presents a spatial data mining method MCAMMO and its extension L_MCAMMO designed for discovering linear and near linear features in spatial databases. L_MCAMMO can be divided into two basic steps: f...
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Spatial Query Estimation without the Local Uniformity Assumption
Existing estimation approaches for spatial databases often rely on the assumption that data distribution in a small region is uniform, which seldom holds in practice. Moreover, their applicability is limited t...
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Using discriminant analysis for multi-class classification: an experimental investigation
Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the elegant theory behind large-margin hyp...
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Multi-level Topological Relations Between Spatial Regions Based Upon Topological Invariants
Topological relations have played important roles in spatial query, analysis and reasoning. In a two-dimensional space (IR2), most existing topological models can distinguish the eight basic topological relations...
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Supervised tensor learning
Tensor representation is helpful to reduce the small sample size problem in discriminative subspace selection. As pointed by this paper, this is mainly because the structure information of objects in computer ...
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Higher Order Vagueness in Geographical Information: Empirical Geographical Population of Type n Fuzzy Sets
Fuzzy set theory has been suggested as a means for representing vague spatial phenomena, and is widely known for directly addressing some of the issues of vagueness such as the sorites paradox. Higher order vague...
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Hierarchical document classification using automatically generated hierarchy
Automated text categorization has witnessed a booming interest with the exponential growth of information and the ever-increasing needs for organizations. The underlying hierarchical structure identifies the r...
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An integrated system for building enterprise taxonomies
Although considerable research has been conducted in the field of hierarchical text categorization, little has been done on automatically collecting labeled corpus for building hierarchical taxonomies. In this...
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Guest editorial: special issue on temporal data mining: theory, algorithms and applications
This special issue provides a leading forum for timely, in-depth presentation of recent advances in algorithms, theories and applications in temporal data mining. The selected papers underwent a rigorous refer...
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SVM based adaptive learning method for text classification from positive and unlabeled documents
Automatic text classification is one of the most important tools in Information Retrieval. This paper presents a novel text classifier using positive and unlabeled examples. The primary challenge of this probl...
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Clustering based on matrix approximation: a unifying view
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. Recently, a number of methods have b...
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DECODE: a new method for discovering clusters of different densities in spatial data
When clusters with different densities and noise lie in a spatial point set, the major obstacle to classifying these data is the determination of the thresholds for classification, which may form a series of b...
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A new approach to discover interlacing data structures in high-dimensional space
The discovery of structures hidden in high-dimensional data space is of great significance for understanding and further processing of the data. Real world datasets are often composed of multiple low dimension...
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Binary matrix factorization for analyzing gene expression data
The advent of microarray technology enables us to monitor an entire genome in a single chip using a systematic approach. Clustering, as a widely used data mining approach, has been used to discover phenotypes ...
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Patent activity on water pollution and treatment in China—a scientometric perspective
This research intends to investigate the patent activity on water pollution and treatment in China (1985–2007), and then compares the results with patents data about Triadic patents, South Korea, Brazil and In...
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A general approximation framework for direct optimization of information retrieval measures
Recently direct optimization of information retrieval (IR) measures has become a new trend in learning to rank. In this paper, we propose a general framework for direct optimization of IR measures, which enjoy...
