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RankClus
2009
Proceedings of the 12th International Conference on Extending Database Technology Advances in Database Technology - EDBT '09
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A novel clustering framework called RankClus is proposed that directly generates clusters integrated with ranking. ...
In this paper, we address the problem of generating clusters for a specified type of objects, as well as ranking information for all types of objects based on these clusters in a multityped (i.e., heterogeneous ...
RankClus aims at finding higher quality and more informative clusters for target objects with rank information integrated in an information network. Second, facet ranking is a two-stage methodology. ...
doi:10.1145/1516360.1516426
dblp:conf/edbt/SunHZYCW09
fatcat:zunt5gcr5zdwzbtvj7qjttmmeu
Fast and Parallel RankClus Algorithm based on Dynamic Rank Score Tracking
2020
Journal of Information Processing
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The RankClus framework accurately performs clustering for bi-type information networks using ranking-based graph clustering techniques. ...
However, this integration incurs a high computational cost to handle large bi-type information networks since RankClus repeatedly computes the ranking algorithm for all nodes and edges until the clustering ...
Specifically, RankClus integrates a clustering procedure with a node ranking technique such as PageRank [4] or HITS [10] to characterize target-type nodes by attribute-type nodes. ...
doi:10.2197/ipsjjip.28.453
fatcat:u536ieu6j5dzbcxpbry26h3mqy
Mining heterogeneous information networks
2012
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12
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Ji et al., KDD'11]: Integration of ranking and classification in heterogeneous network analysis Three types of relations Paper-conf., paper-author, paper-term Algorithms for comparison Learning with ...
Exploring Rich Semantics of Structured Heterogeneous Networks
RankClus: Ranking-Based Clustering in InfoNet
PathSim: A New Metric for Finding Similar Objects in
Heterogeneous Networks
...
Topological features encoded in meta-paths Surprisingly rich knowledge can be mined from such structured heterogeneous info. networks Clustering, ranking, classification, data cleaning, trust analysis ...
doi:10.1145/2339530.2339533
dblp:conf/kdd/Han12
fatcat:2kycyso37fgu5f5a2tai52bhem
Mining knowledge from databases
2010
Proceedings of the 2010 international conference on Management of data - SIGMOD '10
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This tutorial presents an organized picture on how to turn a database into one or a set of organized heterogeneous information networks, how information networks can be used for data cleaning, data consolidation ...
In this tutorial, we introduce database-oriented information network analysis methods and demonstrate how information networks can be used to improve data quality and consistency, facilitate data integration ...
with user-guidance (c) RankClus and NetClus: Integration of clustering and ranking analysis 5. ...
doi:10.1145/1807167.1807333
dblp:conf/sigmod/HanSYY10
fatcat:y3ozzuynxfb3rdtrbf3jldjkci
BibNetMiner
2008
Proceedings of the 2008 ACM SIGMOD international conference on Management of data - SIGMOD '08
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provides a fertile land for information network analysis. ...
Since the dataset is large and the network is heterogeneous, such a study will benefit the research on the analysis of massive heterogeneous information networks. ...
In this demo, we propose a novel clustering framework called RankClus to integrate clustering with ranking, which applies conditional ranking relative to clusters to improve ranking quality, and uses accumulative ...
doi:10.1145/1376616.1376770
dblp:conf/sigmod/SunWYCHYZ08
fatcat:pmqamjq3pfgjhnh2wy4y47thsq
NewsNetExplorer
2014
Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14
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and topical structures and rich-text, such as cell summary, single dimension analysis, and promotion analysis, (ii) a set of network-based operations, such as similarity search and ranking-based clustering ...
Much knowledge can be derived and explored with such an information network if we systematically develop effective and scalable data-intensive information network analysis technologies. ...
In this demo, we will show how a quality NewsNet can be constructed by integration of NLP, phrase mining, and information network analysis methods, and how OLAP and heterogenous network mining can be successfully ...
doi:10.1145/2588555.2594537
dblp:conf/sigmod/TaoBHJWNELRS14
fatcat:iqzfctmbvvba7d3gxrirds4ahu
Research-insight
2013
Proceedings of the 2013 international conference on Management of data - SIGMOD '13
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We show that nontrivial research insight can be obtained from such analysis, including (1) ranking, clustering, classification and similarity search of researchers, terms and venues for research subfields ...
A database contains rich, inter-related, multi-typed data and information, forming one or a set of gigantic, interconnected, heterogeneous information networks. ...
However, for link-based clustering of heterogeneous information networks, we need to explore links across heterogeneous types of data. ...
doi:10.1145/2463676.2463689
dblp:conf/sigmod/TaoYLBCHKSWWW13
fatcat:emvwoxwvurce3mwqs6mmmrgauu
iNextCube
2009
Proceedings of the VLDB Endowment
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Based on our previous studies on TextCube [1], TopicCube [2], and information network analysis, such as RankClus [3] and NetClus [4], we construct iNextCube, an information-Network-enhanced text Cube. ...
To enhance the power of data analysis, interesting entities and relationships can be extracted from such databases to derive heterogeneous information networks, which in turn will substantially increase ...
In our system, NetClus, dealing with multi-typed (i.e., ≥ 2 types) information network is used for integrated clustering, ranking, and concept hierarchy formation. ...
doi:10.14778/1687553.1687608
fatcat:ikas64hehzewjk5cgr3i4nwd5q
Mining knowledge from interconnected data
2012
Proceedings of the VLDB Endowment
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Most objects and data in the real world are interconnected, forming complex, heterogeneous but often semi-structured information networks. ...
In this tutorial, we view database and other interconnected data as heterogeneous information networks, and study how to leverage the rich semantic meaning of types of objects and links in the networks ...
Mining Heterogeneous Information Networks Clustering, classification and ranking are basic mining functions for information networks. ...
doi:10.14778/2367502.2367566
fatcat:q2yoxnqkendktob43l6y4p6o3i
Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model
[chapter]
2015
Proceedings of the 2015 SIAM International Conference on Data Mining
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Recent research has shown that clustering and ranking can actually mutually enhance each other, and several techniques have been developed to integrate clustering and ranking together on a heterogeneous ...
Clustering and ranking have been successfully applied independently to homogeneous information networks, containing only one type of objects. ...
For example, RankClus [12] and NetClus [13] integrate clustering and ranking together on heterogeneous networks, and achieve better performance in both tasks. ...
doi:10.1137/1.9781611974010.48
dblp:conf/sdm/ChenDSD15
fatcat:4s53ncuww5a3ti4ju6l7scbd5a
Ranking-based clustering of heterogeneous information networks with star network schema
2009
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09
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A recent study proposed a new algorithm, RankClus, for clustering on bi-typed heterogeneous networks. ...
Further, NetClus generates informative clusters, presenting good ranking and cluster membership information for each attribute object in each net-cluster. ...
In fact, a net-cluster is a sub-network integrating statistical information for objects. ...
doi:10.1145/1557019.1557107
dblp:conf/kdd/SunYH09
fatcat:kihko5xpzzbzzdrsmmokuzlnk4
Mining Knowledge from Data: An Information Network Analysis Approach
2012
2012 IEEE 28th International Conference on Data Engineering
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The topics to be covered include (i) database as an information network, (ii) mining information networks: clustering, classification, ranking, similarity search, and meta path-guided analysis, (iii) construction ...
of quality, informative networks by data mining, (iv) trend and evolution analysis in heterogeneous information networks, and (v) research frontiers. ...
Air Force Office of Scientific Research MURI award FA9550-08-1-0265, and MIAS, a DHS-IDS Center for Multimodal Information Access and Synthesis at UIUC. ...
doi:10.1109/icde.2012.145
dblp:conf/icde/HanSYY12
fatcat:3yobocvu4venromba6dcshtw2e
A Survey of Data Mining Techniques on Information Networks
2018
International Journal of Engineering & Technology
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The Data Mining techniques of both homogeneous and heterogeneous information networks are discussed in detail and a comparative study on each problem category is showcased. ...
An Information Network is the network formed by the interconnectivity of the objects formed due to the interaction between them. ...
The RankClus algorithm runs on a bi typed information network. The ranking functions considered to rank the objects in an information network are simple ranking and authority ranking. ...
doi:10.14419/ijet.v7i2.6.11267
fatcat:zavu7rli4ja2ne3nj6wiz4wxhi
A Tensor CP Decomposition Method for Clustering Heterogeneous Information Networks via Stochastic Gradient Descent Algorithms
2017
Scientific Programming
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Clustering analysis is a basic and essential method for mining heterogeneous information networks, which consist of multiple types of objects and rich semantic relations among different object types. ...
Some recent studies focused on heterogeneous information networks and yielded some research fruits, such as RankClus and NetClus. ...
based clustering algorithm [1] ; it developed the RankClus algorithm that integrated clustering with ranking for clustering bityped networks. ...
doi:10.1155/2017/2803091
fatcat:ltrtxfvoczfjtlxymeocktwhaq
A Survey of Heterogeneous Information Network Analysis
[article]
2015
arXiv
pre-print
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In this paper, we provide a survey of heterogeneous information network analysis. ...
for data mining. ...
Compared with homogeneous networks, heterogeneous networks integrate multi-typed objects, which generates new challenges for clustering tasks. ...
arXiv:1511.04854v1
fatcat:n2k3sulq3fbq3e34lrfrv3uoou
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