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64
Clustering Large Attributed Graphs: An Efficient Incremental Approach
 2010 IEEE International Conference on Data Mining
, 2010
"... Abstract—In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectiveness in analyzing and visualizing large networks. The goal of graph clustering is to partition vertices in a larg ..."
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Cited by 20 (7 self)
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an efficient algorithm IncCluster to incrementally update the random walk distances given the edge weight increments. Complexity analysis is provided to estimate how much runtime cost IncCluster can save. Experimental results demonstrate that IncCluster achieves significant speedup over SACluster on large
An Incremental Algorithm for a Generalization of the ShortestPath Problem
, 1992
"... The grammar problem, a generalization of the singlesource shortestpath problem introduced by Knuth, is to compute the minimumcost derivation of a terminal string from each nonterminal of a given contextfree grammar, with the cost of a derivation being suitably defined. This problem also subsume ..."
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Cited by 139 (1 self)
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incremental algorithm for the singlesource shortestpath problem with positive edge lengths. The aspect of our work that distinguishes it from other work on the dynamic shortestpath problem is its ability to handle "multiple heterogeneous modifications": between updates, the input graph is allowed
Incremental concept formation algorithms based on Galois (concept) lattices
, 1995
"... . The Galois (or concept) lattice produced from a binary relation has been proved useful for many applications. Building the Galois lattice can be considered as a conceptual clustering method since it results in a concept hierarchy. This article presents incremental algorithms for updating the Galoi ..."
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Cited by 132 (9 self)
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. The Galois (or concept) lattice produced from a binary relation has been proved useful for many applications. Building the Galois lattice can be considered as a conceptual clustering method since it results in a concept hierarchy. This article presents incremental algorithms for updating
Fast Incremental MinimumCut Based Algorithm for Graph Clustering
"... In this paper we introduce an incremental clustering algorithm for undirected graphs. The algorithm can maintain clusters efficiently in presence of insertion and deletion (updation) of edges and vertices. The algorithm produces clusters that satisfies the quality requirement, given by the bicriteri ..."
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Cited by 2 (0 self)
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In this paper we introduce an incremental clustering algorithm for undirected graphs. The algorithm can maintain clusters efficiently in presence of insertion and deletion (updation) of edges and vertices. The algorithm produces clusters that satisfies the quality requirement, given
Incremental Maintenance for Materialized Views over Semistructured Data
, 1998
"... Semistructured data is not strictly typed like relational or objectoriented data and may be irregular or incomplete. It often arises in practice, e.g., when heterogeneous data sources are integrated or data is taken from the World Wide Web. Views over semistructured data can be used to filter the d ..."
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Cited by 84 (10 self)
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the data and to restructure (or provide structure to) it. To achieve fast query response time, these views are often materialized. This paper studies incremental maintenance techniques for materialized views over semistructured data. We use the graphbased data model OEM and the query language Lorel
IPSepCoLa: An incremental procedure for separation constraint layout of graphs
 IEEE Trans. Visualization and Computer Graphics
, 2006
"... Abstract—We extend the popular forcedirected approach to network (or graph) layout to allow separation constraints, which enforce a minimum horizontal or vertical separation between selected pairs of nodes. This simple class of linear constraints is expressive enough to satisfy a wide variety of ap ..."
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Cited by 44 (19 self)
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programming problem. We give an incremental algorithm based on gradient projection for efficiently solving this problem. The algorithm is considerably faster than using generic constraint optimization techniques and is comparable in speed to unconstrained stress majorization. We demonstrate the utility of our
An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity
"... Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this p ..."
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. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH), to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same
Efficient Eigenupdating for Spectral Graph Clustering
, 2013
"... Partitioning a graph into groups of vertices such that those within each group are more densely connected than vertices assigned to different groups, known as graph clustering, is often used to gain insight intothe organisation of large scale networks and for visualisation purposes. Whereas a large ..."
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thestudyofbiological networkstotheanalysis ofnetworksof scientific references through the exploration of communications networks such as the World Wide Web, it is the main purpose of this paper to introduce a novel, computationally efficient, approach to graph clustering in the evolutionary context. Namely, the method
Efficient phrasebased document indexing for Web document clustering
 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
, 2004
"... Document clustering techniques mostly rely on single term analysis of the document data set, such as the Vector Space Model. To achieve more accurate document clustering, more informative features including phrases and their weights are particularly important in such scenarios. Document clustering ..."
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Cited by 65 (2 self)
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Index Graph, which allows for incremental construction of a phrasebased index of the document set with an emphasis on efficiency, rather than relying on singleterm indexes only. It provides efficient phrase matching that is used to judge the similarity between documents. The model is flexible
Incremental subspace clustering over multiple data streams
 ICDM Conference
, 2007
"... Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects in different subspaces. However, traditional subspace clustering algorithms for static data sets are not readily used ..."
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Cited by 4 (0 self)
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ily used for incremental clustering, and is very expensive for frequent reclustering over dynamically changing stream data. In this paper, we present an efficient incremental subspace clustering algorithm for multiple streams over sliding windows. Our algorithm detects all the δCCClusters, which
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