A Constraint-based Approach for Multispace Clustering Ruggero G. Pensa and Mirco Nanni Pisa KDD Laboratory, ISTI-CNR, IPisa, Italy {ruggero.pensa,mirco.nanni}@isti.cnr.it

Source URL: www.ke.tu-darmstadt.de

• Cluster analysis
• Hierarchical clustering
• Network analysis
• Document clustering
• K-means clustering
• Constrained clustering
• Data stream clustering
• Consensus clustering

ISSN No: International Journal & Magazine of Engineering, Technology, Management and Research A Peer Reviewed Open Access International Journal

Source URL: www.ijmetmr.com

• Natural language processing
• Computational linguistics
• Internet search engines
• Document clustering
• Cluster analysis
• Hierarchical clustering
• Word-sense induction
• K-means clustering
• Search engine technology
• Relevance
• Information retrieval
• Stemming

SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering Han Zhao† , Pascal Poupart† , Yongfeng Zhang§ and Martin Lysy‡ † David R. Cheriton School of Computer Science, University of Waterloo, Canada D

Source URL: yongfeng.me

• Multivariate statistics
• Linear algebra
• Matrix theory
• Non-negative matrix factorization
• Cluster analysis
• Spectral clustering
• K-means clustering
• Document clustering
• Pattern recognition
• Expectationmaximization algorithm
• Determining the number of clusters in a data set
• Hierarchical clustering

Extracting Multi-document Summaries with a Double Clustering Approach Sara Botelho Silveira and Ant´ onio Branco University of Lisbon, Portugal Edif´ıcio C6, Departamento de Inform´

Source URL: www.di.fc.ul.pt

• Natural language processing
• Computational linguistics
• Data mining
• Automatic summarization
• Multi-document summarization
• Sentence
• Search engine indexing
• Phrase
• Keyword clustering
• ROUGE

PDF Document

Source URL: www.di.fc.ul.pt

• Data mining
• Natural language processing
• Computational linguistics
• Automatic summarization
• Cluster analysis
• Document clustering
• Text mining
• Cassiopeia
• Hierarchical clustering

Collaboration: Towards Automated Study Guides for MOOCs Jose Hernandez Stanford University Andrew Lamb

Source URL: ilpubs.stanford.edu

• Natural language processing
• Data mining
• Statistical natural language processing
• Computational linguistics
• Document clustering
• Keyword clustering
• Cluster analysis
• Hierarchical clustering
• Topic model
• Keyword extraction
• Full text search
• Massive open online course

LNAIUsing a Double Clustering Approach to Build Extractive Multi-document Summaries

Source URL: www.di.fc.ul.pt

Interpeting Outliers from Clustering Algorithms render(“interpret_outliers.md”, “pdf_document”) By Gaurav Sood Assume that the data from the dominant data generating process are structured so that they occupy a f

Source URL: gbytes.gsood.com

• Statistics
• Data analysis
• Outlier
• Statistical analysis
• Cluster analysis

High Quality, Efficient Hierarchical Document Clustering using Closed Interesting Itemsets Hassan H. Malik and John R. Kender Department of Computer Science Columbia University New York, NY 10027

Source URL: www.cs.columbia.edu

A Probabilistic Model for Online Document Clustering with Application to Novelty Detection Jian Zhang School of Computer Science Cargenie Mellon University

Source URL: mlg.eng.cam.ac.uk