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Multiview Partitioning via Tensor Methods
2013
IEEE Transactions on Knowledge and Data Engineering
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We show that the solutions for both formulations can be computed by tensor decompositions. We evaluated our methods on synthetic data and two real-world data sets in comparison with baseline methods. ...
Index Terms-Multi-view clustering, tensor decomposition, spectral clustering, multi-linear singular value decomposition, higher-order orthogonal iteration X. Liu is with the ...
De Lathauwer for deriving the version of HOOI with a single vector in one mode and for the theorem and proof in the Supplementary material 6. This work was supported by (1) ...
doi:10.1109/tkde.2012.95
fatcat:c3fzmbheh5fcphw33lciyyjavm
Mining latent entity structures from massive unstructured and interconnected data
2014
Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14
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The framework enables recursive construction of phrase-represented and entity-enriched topic hierarchy from text-attached information networks. ...
The method can utilize heterogeneous attributes and links to capture all kinds of semantic signals, including constraints and dependencies, to recover the hierarchical relationship with the best known ...
The text-attached heterogeneous information network will be the input from which we mine latent entity structures. ...
doi:10.1145/2588555.2588890
dblp:conf/sigmod/HanW14
fatcat:js7d3r5yd5gbfgnhjgwsfmco2i
Discipline Hotspots Mining Based on Hierarchical Dirichlet Topic Clustering and Co-word Network
2016
Journal of Software
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We apply the aforementioned theory and method to the process of big text data knowledge discovery and design the solution for analyzing the co-word network and research topics. ...
The proposed scheme is composed of the topic extraction with hierarchical Dirichlet process, topic classify with subject-content words, and discipline hotspot analysis with co-word network with weak co-occurrence ...
Topic model has been a very good application and development in the field of text mining, such as text categorization, topic search and topic evolution etc. ...
doi:10.17706/jsw.11.11.1089-1101
fatcat:lloi4atf4zgvtlv3ajxbptb324
Hybrid intelligent framework for automated medical learning
2021
Expert systems
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The distributed deep learning is used for efficient learning of the different agents in the system, where the knowledge graph is used for dealing with heterogeneous medical data. ...
Three case studies are discussed in this research, the first case study is related to process mining, and more precisely on the ability of HAML to detect relevant patterns from event medical data. ...
His research interests include wireless sensor networks, IoT, Bioinformatics and Biomedical, Cloud computing, Soft computing, Image processing, Artificial intelligence, Data mining, Optimization, and Meta-heuristics ...
doi:10.1111/exsy.12737
fatcat:alshb2hrejak3nhpcqgtbxyphq
Text Classification Techniques: A Literature Review
2018
Interdisciplinary Journal of Information, Knowledge, and Management
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However, in spite of the growth and spread of AI in all fields of research, its role with respect to text mining is not well understood yet. ...
The automation of text classification process is required, with the increasing amount of data and need for accuracy. ...
However, in spite of the growth and spread of AI in all fields of research, its role with respect to text mining is not well understood yet. ...
doi:10.28945/4066
fatcat:6dio5bpajjf77lkrs7xdtciveu
Revision graph extraction in Wikipedia based on supergram decomposition
2013
Proceedings of the 9th International Symposium on Open Collaboration - WikiSym '13
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In this paper, we propose a revision graph extraction method based on supergram decomposition in the document collection of nearduplicates. ...
Towards this core principle, plenty of efforts have been put into collaborative contribution and editing. ...
ACKNOWLEDGEMENT This research was in part supported by "Ambient SoC Global Program of Waseda University" of the Ministry of Education, Culture, Sports, Science and Technology, Japan and JSPS KAKENHI Grant ...
doi:10.1145/2491055.2491065
dblp:conf/wikis/WuI13
fatcat:ps5w7uoppfdlvp4dnxzd4ocxjq
A Probe on Document Clustering Methodologies and its Performance Metrics
2019
International journal of recent technology and engineering
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This assessment gives an implication about the different methods(Vector Space Model, Latent Sematic Indexing, Latent Dirichlet Allocation, Singular Value Decomposition, Doc2Vec Model, Graph model), distance ...
This work is theoretical in nature and aims to corner the overall procedure of document clustering. ...
to Improve the Text Document Clustering C Techniques [4] Determining the Number of Clusters using Neural Network and Max Stable Set Problem [3] DThe contribution of the lexical component in hybrid clustering ...
doi:10.35940/ijrte.b2624.078219
fatcat:ymdvldvednhyzla7jpttza5hma
Novel Class Detection and Feature via a Tiered Ensemble Approach for Stream Mining
2012
2012 IEEE 24th International Conference on Tools with Artificial Intelligence
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Static data mining assumptions with regard to features and labels often fail the streaming context. Features evolve, concepts drift, and novel classes are introduced. ...
Traditional static data mining algorithms futile in a streaming context (and often in a distributed sensor network) due to their need to iterate over the entire data set locally. ...
We plan to continue development on HSMiner, with improvements to the Sieve approach, further mitigating error by dynamically maintaining inter-tier weights as the stream progresses, and testing alternative ...
doi:10.1109/ictai.2012.168
dblp:conf/ictai/ParkerMK12
fatcat:v4o633okindr5fwpfjjqrfwp44
Network representation learning: models, methods and applications
2019
SN Applied Sciences
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With the rise of large-scale social networks, network mining has become an important sub-domain of data mining. ...
Definition 4 A heterogeneous network is a network G = (V , E) , where each node v i ∈ V and each edge e i ∈ E , are associated with mapping functions F(v) ∶ V → T v and f (e) ∶ E → T e , where T v and ...
Acknowledgements The authors would like to thank the management and staff of Department of Computer Applications, CUSAT, India and NSS College of Engineering, Palakkad, India for providing enough materials ...
doi:10.1007/s42452-019-1044-9
fatcat:zvlbj4qozzfw3dxoyevb6wgska
A New Data Mining System for Ontology Learning Using Dynamic Time Warping Alignment as a Case
2013
Procedia Computer Science
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In most approaches, the text representation is only based on the information contained in term weighting and does therefore not process the semantic contained in the sequence in which the words appear. ...
In order to identify the correspondence between the ontological artifacts and candidate changes, we used an alignment process. ...
On one hand, the model cannot explain the intrinsic relations in the text with a very small projection space. ...
doi:10.1016/j.procs.2013.09.012
fatcat:gdtgergsvvaqtp6keiqhblrc6q
Expert Discovery: A web mining approach
2013
Journal of Artificial Intelligence and Data Mining
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We have proposed multifaceted web mining heuristic that resulted into the design and development of a tool using data from Growbag, dblpXML with Authors home pages resource to find people of desired expertise ...
Expert with domain knowledge in any field is crucial for consulting in industry, academia and scientific community. ...
in large text sources. ...
doi:10.22044/jadm.2013.116
doaj:b9bf03b34f5c41ef8b00823e29f81c04
fatcat:rsx4a6efezcj7o7tuuv6mdjmbi
Social Network Analysis: A Survey on Measure, Structure, Language Information Analysis, Privacy, and Applications
2022
ACM Transactions on Asian and Low-Resource Language Information Processing
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This detailed study has started with the basics of network representation, structure, and measures. Our primary focus is on SNA applications with state-of-the-art techniques. ...
Social network analysis (SNA) is a paramount technique supporting understanding social relationships and networks. ...
This modeling is mostly used in text and web mining to uncover semantics in text. ...
doi:10.1145/3539732
fatcat:t4q2qkf3obcmplnzkwzvfq5ga4
Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering
2021
Electronics
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The main keywords that have been considered in this paper are text, clustering, meta-heuristic, optimization, and algorithm. ...
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. ...
[7] , text document categorization [8] , wireless sensor networks [9] , web mining [10] , sentiment Analysis [11] , Big data clustering [12] , and others. ...
doi:10.3390/electronics10020101
fatcat:fb3sopje4fegphs5b6g673ipqa
Generalized component analysis for text with heterogeneous attributes
2007
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '07
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We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. ...
Our model generalizes techniques such as principal component analysis to heterogeneous data types. ...
INTRODUCTION Many tasks in data mining involve the processing of high dimensional data with heterogeneous attributes. ...
doi:10.1145/1281192.1281277
dblp:conf/kdd/WangPM07
fatcat:dezhpkz6qzhpxlftv7p3fjpu6q
Web-Scale Multimedia Information Networks
2012
Proceedings of the IEEE
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in MINets which is consistent with human cognition. ...
| The abundance of multimedia data on the Web presents both challenges (how to annotate, search, and mine) and opportunities (crawling the Web to create large structured multimedia data bases which can ...
MULTIMEDIA INFORMATION NETWORKS: CONSTRUCTION AND UTILIZATION MINet is a heterogeneous network that involves crossmedia objects of images/videos, speech, and text as well as their high-level knowledge ...
doi:10.1109/jproc.2012.2201909
fatcat:4hcia4agvbaija2kx5ynj2esse
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