Collective Entity Resolution in Relational Data INDRAJIT BHATTACHARYA and LISE GETOOR University of Maryland, College Park Many databases contain uncertain and imprecise references to real-world entities. The absence

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ABSTRACT Title of Dissertation: COLLECTIVE ENTITY RESOLUTION IN RELATIONAL DATA

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A Latent Dirichlet Allocation Model for Entity Resolution Indrajit Bhattacharya Lise Getoor University of Maryland

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• Probability
• Statistics
• Sampling
• Survey methodology
• Mixture model
• Gibbs sampling
• Record linkage
• Latent Dirichlet allocation
• Probability distribution
• Prior probability
• Causality

Microsoft Word - Document1

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• Economy
• Insurance
• Security
• Finance
• Gurgaon
• Actuarial science
• Risk
• High-Efficiency Advanced Audio Coding
• Actuarial Society of Malaysia
• Delhi
• Institute of Actuaries of India
• Drona

SENSEVAL-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, Barcelona, Spain, July 2004 Association for Computational Linguistics The University of Maryland SENSEVAL-3 System

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• Linguistics
• Computational linguistics
• Semantics
• Language
• Natural language processing
• Word-sense disambiguation
• Lexical semantics
• SemEval
• WordNet
• Word sense
• Machine translation
• Part-of-speech tagging

Structured Entity Identification and Document Categorization: Two Tasks with One Joint Model Indrajit Bhattacharya Shantanu Godbole

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• Information science
• Information retrieval
• Natural language processing
• Information
• Data mining
• Statistical natural language processing
• Data modeling
• Latent semantic analysis
• Data model
• Text mining
• Database
• Document classification

A Latent Dirichlet Model for Unsupervised Entity Resolution Indrajit Bhattacharya Lise Getoor Department of Computer Science University of Maryland, College Park, MDAbstract

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• Probability
• Statistics
• Probability distributions
• Stochastic processes
• Latent Dirichlet allocation
• Statistical natural language processing
• Mixture model
• Prior probability
• Dirichlet distribution
• Gibbs sampling
• Sampling
• Dirichlet process

A Cluster-Level Semi-Supervision Model for Interactive Clustering Avinava Dubey1 , Indrajit Bhattacharya2? , and Shantanu Godbole1 1 IBM Research - India

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• Cluster analysis
• Statistics
• Computing
• Data analysis
• K-means clustering
• Constrained clustering
• Biclustering
• Computer cluster
• Clustering
• Determining the number of clusters in a data set
• Hierarchical clustering

Exploiting Coherence for the Simultaneous Discovery of Latent Facets and associated Sentiments Himabindu Lakkaraju∗ Chiranjib Bhattacharyya† Indrajit Bhattacharya‡ Srujana Merugu∗ Abstract Facet-based sentiment a

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• Statistical natural language processing
• Artificial intelligence
• Natural language processing
• Statistics
• Psychology
• Affective computing
• Sentiment analysis
• Personality tests
• Topic model
• Text mining
• Probabilistic latent semantic analysis
• Facet

Collective Entity Resolution In Relational Data Indrajit Bhattacharya and Lise Getoor Department of Computer Science University of Maryland, College Park, MD 20742, USA Abstract An important aspect of maintaining informa

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• Computing
• Data management
• Data
• Data modeling
• Database theory
• Entityrelationship model
• Data model
• Record linkage
• Cluster analysis
• Reference table
• Database
• Associative entity