Who Cited It

From Frequency to Meaning: Vector Space Models of Semantics

2010 · Journal of Artificial Intelligence Research · 2,902 citations · 9 from inside this corpus

Peter D. Turney, Patrick Pantel low

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field.

From Frequency to Meaning: Vector Space Models of Semantics (2010)From Frequency to Meaning: Ve…Latent dirichlet allocation (2003)Latent dirichlet allocationLearning the parts of objects by non-negative matrix factorization (1999)Learning the parts of objects…Data clustering (1999)Data clusteringIndexing by latent semantic analysis (1990)Indexing by latent semantic a…Introduction to information retrieval (2009)Introduction to information r…WordNet: An electronic lexical database . Ed. by Christiane Fellbaum. Cambridge, MA: MIT … (2000)WordNet: An electronic lexica…Modern Information Retrieval (1999)Modern Information RetrievalFoundations of statistical natural language processing (1999)Foundations of statistical na…Term-weighting approaches in automatic text retrieval (1988)Term-weighting approaches in …An algorithm for suffix stripping (1980)Machine learning in automated text categorization (2002)Machine learning in automated…Thumbs up? (2002)Thumbs up?A solution to Plato's problem: The latent semantic analysis theory of acquisition, induct… (1997)A solution to Plato's problem…A unified architecture for natural language processing (2008)A unified architecture for na…Structure‐Mapping: A Theoretical Framework for Analogy* (1983)Structure‐Mapping: A Theoreti…A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL (1972)A STATISTICAL INTERPRETATION …Word association norms, mutual information, and lexicography (1990)Word association norms, mutua…An extensive empirical study of feature selection metrics for text classification (2003)An extensive empirical study …The SMART Retrieval System—Experiments in Automatic Document Processing (1971)The SMART Retrieval System—Ex…Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy (1997)Semantic Similarity Based on …Attention, similarity, and the identification-categorization relationship. (1986)Attention, similarity, and th…Thumbs up? Sentiment Classification using Machine Learning Techniques (2002)Thumbs up? Sentiment Classifi…Using Information Content to Evaluate Semantic Similarity in a Taxonomy (1995)Using Information Content to …An Evaluation of Statistical Approaches to Text Categorization (1999)An Evaluation of Statistical …Kernel principal component analysis (1997)Producing high-dimensional semantic spaces from lexical co-occurrence (1996)Producing high-dimensional se…Using Information Content to Evaluate Semantic Similarity in a Taxonomy (1995)Using Information Content to …Distributed Representations of Words and Phrases and their Compositionality (2013)Distributed Representations o…Enriching Word Vectors with Subword Information (2017)Enriching Word Vectors with S…Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank (2013)Recursive Deep Models for Sem…Distributed Representations of Sentences and Documents (2014)Distributed Representations o…Learning Word Vectors for Sentiment Analysis (2011)Learning Word Vectors for Sen…Recent Trends in Deep Learning Based Natural Language Processing [Review Article] (2018)Recent Trends in Deep Learnin…Word Representations: A Simple and General Method for Semi-Supervised Learning (2010)Word Representations: A Simpl…Neural Word Embedding as Implicit Matrix Factorization (2014)Neural Word Embedding as Impl…Don't count, predict! A systematic comparison of context-counting vs. context-predicting … (2014)Don't count, predict! A syste…
36 of 45 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Latent dirichlet allocation200327,078
Learning the parts of objects by non-negative matrix factorization199914,223
Data clustering199913,263
Indexing by latent semantic analysis199012,850
Introduction to information retrieval200912,588
WordNet: An electronic lexical database . Ed. by Christiane Fellbaum. Cambridge, MA: MIT …200011,687
Modern Information Retrieval199911,572
Foundations of statistical natural language processing19999,997
Term-weighting approaches in automatic text retrieval19889,714
An algorithm for suffix stripping19808,157
Machine learning in automated text categorization20027,945
Thumbs up?20027,057
A solution to Plato's problem: The latent semantic analysis theory of acquisition, induct…19976,147
A unified architecture for natural language processing20085,207
Structure‐Mapping: A Theoretical Framework for Analogy*19835,087
A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL19724,514
Word association norms, mutual information, and lexicography19903,680
An extensive empirical study of feature selection metrics for text classification20032,390
The SMART Retrieval System—Experiments in Automatic Document Processing19712,276
Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy19972,230
Attention, similarity, and the identification-categorization relationship.19862,227
Thumbs up? Sentiment Classification using Machine Learning Techniques20022,215
Using Information Content to Evaluate Semantic Similarity in a Taxonomy19952,155
An Evaluation of Statistical Approaches to Text Categorization19991,963
Kernel principal component analysis19971,950
Producing high-dimensional semantic spaces from lexical co-occurrence19961,849
Using Information Content to Evaluate Semantic Similarity in a Taxonomy19951,766

What cites it, inside the corpus

PaperYearCited
Distributed Representations of Words and Phrases and their Compositionality201318,054
Enriching Word Vectors with Subword Information20179,900
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank20136,849
Distributed Representations of Sentences and Documents20145,121
Learning Word Vectors for Sentiment Analysis20113,294
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]20182,907
Word Representations: A Simple and General Method for Semi-Supervised Learning20101,941
Neural Word Embedding as Implicit Matrix Factorization20141,591
Don't count, predict! A systematic comparison of context-counting vs. context-predicting …20141,388

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Topics

Topic ModelingComputer Science
Natural Language Processing TechniquesComputer Science
Advanced Text Analysis TechniquesComputer Science

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