15 Result(s)
within
Baihua **ao
Data Mining and Knowledge Discovery
Information Storage and Retrieval
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Article
Multi-view metro station clustering based on passenger flows: a functional data-edged network community detection approach
This paper aims at metro station clustering based on passenger flow data. Compared with existing clustering methods that only use boarding or alighting data of each station separately, we focus on higher granu...
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Chapter and Conference Paper
Efficient Algorithms for Solving Aggregate Keyword Routing Problems
With the emergence of smart phones and the popularity of GPS, the number of point of interest (POIs) is growing rapidly and spatial keyword search based on POIs has attracted significant attention. In this paper,...
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Reference Work Entry In depth
Air Indexes for Spatial Databases
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Chapter and Conference Paper
Distributed k-Nearest Neighbor Queries in Metric Spaces
Metric k nearest neighbor (MkNN) queries have applications in many areas such as multimedia retrieval, computational biology, and location-based services. With the growing volumes of data, a distributed method is...
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Living Reference Work Entry In depth
Air Indexes for Spatial Databases
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Article
High utility K-anonymization for social network publishing
Privacy and utility are two main desiderata of good sensitive information publishing schemes. For publishing social networks, many existing algorithms rely on
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Chapter and Conference Paper
An Automaton-Based Index Scheme for On-Demand XML Data Broadcast
XML data broadcast is an efficient way to deliver semi-structured information in wireless mobile environment. In the literature, many approaches have been proposed to improve the performance of XML data broadc...
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Chapter and Conference Paper
Challenges in Managing and Mining Large, Heterogeneous Data
Success in various application domains including sensor networks, social networks, and multimedia, has ushered in a new era of information explosion. Despite the diversity of these domains, data acquired by ap...
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Chapter and Conference Paper
An Incremental Approach to Closest Pair Queries in Spatial Networks Using Best-First Search
This paper addresses the problem of k Closest Pairs (kCP) query in spatial network databases. A Best-First search approach namely BFCP (Best-First Closest Pair) is proposed. Given two data sets of objects in a...
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Chapter and Conference Paper
Utility-Oriented K-Anonymization on Social Networks
“Identity disclosure” problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is...
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Article
Accelerating sequence searching: dimensionality reduction method
Similarity search over long sequence dataset becomes increasingly popular in many emerging applications, such as text retrieval, genetic sequences exploring, etc. In this paper, a novel index structure, namely Se...
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Chapter and Conference Paper
Workshop Organizers’ Message
The DASFAA PhD workshop will be held in Brisbane, Australia on 22 April, 2009, in conjunction with the DASFAA 2009 conference. The workshop is the first in its series and aims to bring together PhD students wo...
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Chapter and Conference Paper
Squeezing Long Sequence Data for Efficient Similarity Search
Similarity search over long sequence dataset becomes increasingly popular in many emerging applications. In this paper, a novel index structure, namely Sequence Embedding Multiset tree(SEM-tree), has been propose...
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Chapter and Conference Paper
Searching Correlated Objects in a Long Sequence
Sequence, widely appearing in various applications (e.g. event logs, text documents, etc) is an ordered list of objects. Exploring correlated objects in a sequence can provide useful knowledge among the objects, ...
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Chapter and Conference Paper
CLAIM: An Efficient Method for Relaxed Frequent Closed Itemsets Mining over Stream Data
Recently, frequent itemsets mining over data streams attracted much attention. However, mining closed itemsets from data stream has not been well addressed. The main difficulty lies in its high complexity of m...
