A Little Bit of NLP Goes A Long Way: Adding Phrases to the Term-Document Matrix using Finite-State Shallow Parsing https://github.com/slanglab/phrasemachine http://slanglab.cs.umass.edu/phrasemachine/ Abram Handler (UMas

Source URL: brenocon.com

Introduction to Information Retrieval ` `%%%`#_`__~~~false [0.5cm] IIR 18: Latent Semantic Indexing

Source URL: essir.uni-koblenz.de

• Algebra
• Mathematics
• Natural language processing
• Latent semantic analysis
• Machine learning
• Singular value decomposition
• Dimensionality reduction
• Vector space model
• Document-term matrix

Document Analysis Jaehyun Park Ahmed Bou-Rabee EE103 Stanford University

Source URL: stanford.edu

• Natural language processing
• Statistical distance
• Multivariate statistics
• Linear algebra
• Document-term matrix
• Similarity measure
• Microsoft Word
• Word count
• HP2
• Euclidean vector

This article was downloaded by: [University of California Santa Barbara] On: 10 April 2012, At: 10:40 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: Registered office:

Source URL: www.public.asu.edu

• Natural language processing
• Data management
• Vector space model
• Latent semantic analysis
• Geospatial metadata
• Document-term matrix
• Search engine indexing
• Search engine technology
• Index term
• Tfidf
• Book:Information retrieval

The Vector Space Model of Word Meaning Informatics 1 CG: Lecture 13 Reading: An Introduction to Latent Semantic Analysis. Discourse Processes, 25, 259–284.

Source URL: www.inf.ed.ac.uk

• Natural language processing
• Computational linguistics
• Semantics
• Vectors
• Machine learning
• Latent semantic analysis
• Semantic similarity
• Distributional semantics
• Word embedding
• Vector space model
• Document-term matrix
• Euclidean vector

Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change William L. Hamilton, Jure Leskovec, Dan Jurafsky Computer Science Department, Stanford University, Stanford CA, 94305 wleif,jure,

Source URL: web.stanford.edu

• Semantics
• Natural language processing
• Computational linguistics
• Historical linguistics
• Artificial neural networks
• Latent semantic analysis
• Polysemy
• Semantic change
• Semantic similarity
• Distributional semantics
• Language change
• Document-term matrix

Text as Data Zoltan Fazekas zfazekas.github.io 19 November 2015 @cph ssd

Source URL: sebastianbarfort.github.io

• Natural language processing
• N-gram
• Document-term matrix
• Grimmer
• Matrix

R Last Edited: Module name: R 2. Scope: a. This module covers use of the R language for performing the statistical analysis needed for

Source URL: curric.dlib.vt.edu

• Matrix theory
• Linear algebra
• Numerical linear algebra
• Natural language processing
• Singular value decomposition
• Latent semantic analysis
• Matrix
• Eigenvalues and eigenvectors
• Diagonal matrix
• Eigendecomposition of a matrix
• Document-term matrix
• Determinant

Translation Invariant Word Embeddings Matt Gardner∗ Carnegie Mellon University Kejun Huang∗

Source URL: www.talukdar.net

• Algebra
• Mathematics
• Linear algebra
• Natural language processing
• Matrix theory
• Abstract algebra
• Multivariate statistics
• Latent semantic analysis
• Document-term matrix
• Singular value decomposition
• Matrix
• Word embedding

Incremental Models of Natural Language Category Acquisition Trevor Fountain () Mirella Lapata () Institute for Language, Cognition and Computation School of Informatics, Universit

Source URL: texasexpat.net

• Semantics
• Natural language processing
• Computational linguistics
• Statistical natural language processing
• Lexical semantics
• Document-term matrix
• Semantic similarity
• Latent Dirichlet allocation
• Cluster analysis
• Statistics
• Linguistics
• Science