138 Result(s)
within
Chapter
Conference Paper
**mo Wang
Popular Science
Computer Communication Networks
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
SeCED-FS: A New Approach for the Classification and Discovery of Significant Regions in Medical Images
A novel diagnosis method named SeCED-FS is proposed in this paper. The method combines the clusterer ensemble and feature selection technique to improve the diagnosis performance. At first, selective clusterer...
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Chapter and Conference Paper
Efficient Difference NN Queries for Moving Objects
Group Nearest Neighbor query is a relatively prevalent application in spatial databases and overlay network. Unlike the traditional KNN queries, GNN queries maintain several query points and allow aggregate op...
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Chapter and Conference Paper
Study on Efficiency and Effectiveness of KSORD
KSORD(Keyword Search Over Relational Databases) is an easy and effective way for casual users or Web users to access relational databases. In recent years, much research on KSORD has been done, and many protot...
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Chapter and Conference Paper
Continuous Approximate Window Queries in Wireless Sensor Networks
Wireless sensor networks are demonstrating the valuable potential in a variety of settings, e.g. data analysis and statistics. How to minimize energy consumption and prolong network lifetime become one of the ...
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Chapter and Conference Paper
Generation and Matching of Ontology Data for the Semantic Web in a Peer-to-Peer Framework
The abundance of ontology data is very crucial to the emerging semantic web. This paper proposes a framework that supports the generation of ontology data in a ptop environment. It not only enables users to co...
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Chapter and Conference Paper
Effective Density Queries for Moving Objects in Road Networks
Recent research has focused on density queries for moving objects in highly dynamic scenarios. An area is dense if the number of moving objects it contains is above some threshold. Monitoring dense areas has a...
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Chapter and Conference Paper
A PLSA-Based Approach for Building User Profile and Implementing Personalized Recommendation
This paper proposes a method based on Probability Latent Semantic Analysis (PLSA) to analyze web pages that are of interest to the user and the user query co-occurrence relationship, and utilize the latent fac...
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Chapter and Conference Paper
Active Rules Termination Analysis Through Conditional Formula Containing Updatable Variable
While active rules have been applied in many areas including active databases, XML documentation and Semantic Web, current methods remain largely uncertain of how to terminate active behaviors. Some existing m...
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Chapter and Conference Paper
An XML Publish/Subscribe Algorithm Implemented by Relational Operators
An XML publish/subscribe algorithm needs to store large numbers of XPath or XQuery subscriptions and match subscriptions with published XML documents. Since the number of the subscriptions may be very large, t...
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Chapter and Conference Paper
SAM: An Efficient Algorithm for F&B-Index Construction
Using index to process structural queries on XML data is a natural way. F&B-Index has been proven to be the smallest index which covers all branching path queries. One disadvantage which prevents the wide usag...
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Chapter and Conference Paper
IMCS: Incremental Mining of Closed Sequential Patterns
Recently, mining compact frequent patterns (for example closed patterns and compressed patterns) has received much attention from data mining researchers. These studies try to address the interpretability and ...
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Chapter and Conference Paper
Combining Smooth Graphs with Semi-supervised Learning
The key points of the semi-supervised learning problem are the label smoothness and cluster assumptions. In graph-based semi-supervised learning, graph representations of the data are so important that differe...
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Chapter and Conference Paper
Spectral Edit Distance Method for Image Clustering
The spectral graph theories have been widely used in the domain of image clustering where editing distances between graphs are critical. This paper presents a method for spectral edit distance between the grap...
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Chapter and Conference Paper
Protecting and Recovering Database Systems Continuously
Data protection is widely deployed in database systems, but the current technologies (e.g. backup, snapshot, mirroring and replication) can not restore database systems to any point in time. This means that da...
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Chapter and Conference Paper
Mining Time-Shifting Co-regulation Patterns from Gene Expression Data
Previous work for finding patterns only focuses on grou** objects under the same subset of dimensions. Thus, an important bio-interesting pattern, i.e. time-shifting, will be ignored during the analysis of t...
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Chapter and Conference Paper
Cross-Layer Distributed Diversity for Heterogeneous Wireless Networks
In this paper, we introduce a cross-layer diversity framework for multi-air interface wireless communication devices. As an initial step, we focus on devices, of the cellular phones type, that have both long-r...
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Chapter and Conference Paper
Novel NonGaussianity Measure Based BSS Algorithm for Dependent Signals
The purpose of this paper is to develop novel Blind Source Separation (BSS) algorithms from linear mixtures of them, which enable to separate dependent source signals. Most of the proposed algorithms for solvi...
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Chapter and Conference Paper
Towards High Performance and High Availability Clusters of Archived Stream
Some burgeoning web applications, such as web search engines, need to track, store and analyze massive real-time users’ access logs with high availability of 24*7. The traditional high availability approaches ...
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Chapter and Conference Paper
Energy-Efficient Skyline Queries over Sensor Network Using Mapped Skyline Filters
In recent years, wireless sensor network has been widely used in military and civil applications. For many wireless sensor applications, the skyline query is a very important operator for retrieving data accor...
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Chapter and Conference Paper
APCAS: An Approximate Approach to Adaptively Segment Time Series Stream
We study the problem of segmenting time series stream. Existing segmenting methods for time series mainly focus on the static data, and may be infeasible under the circumstance of time series stream. We propos...
