Answers.Body: <p>If I understand you correctly, you should check out <strong>Word2Vec</strong>. From <a href="https://en.wikipedia.org/wiki/Word2vec" rel="nofollow">Wikipedia</a>: </p>
  
  <blockquote>
    <p>Word2vec is a group of related models that are used to produce word
    embeddings. These models are shallow, two-layer neural networks that
    are trained to reconstruct linguistic contexts of words. Word2vec
    takes as its input a large corpus of text and produces a
    high-dimensional space (typically of several hundred dimensions), with
    each unique word in the corpus being assigned a corresponding vector
    in the space. Word vectors are positioned in the vector space such
    that words that share common contexts in the corpus are located in
    close proximity to one another in the space.</p>
  </blockquote>
  
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Answers.CreationDate: 2016-08-26T23:10:09.577Z
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Answers.UserDisplayName: Doxosophoi
Answers.Body: <p>I would think you could use a <a href="https://en.wikipedia.org/wiki/Graph_database" rel="nofollow">graph database</a>, perhaps <a href="https://neo4j.com/" rel="nofollow">Neo4J</a> or <a href="http://titan.thinkaurelius.com/" rel="nofollow">Titan</a> or something of that nature.  Or, if you want a simple file format, you could use one of the many formats that exist for representing graphs.  You can find a list and overview of some of them <a href="https://gephi.org/users/supported-graph-formats/" rel="nofollow">here</a>.</p>
  
  <p>Another option would be to store them in <a href="https://en.wikipedia.org/wiki/Resource_Description_Framework" rel="nofollow">RDF</a> using a <a href="https://en.wikipedia.org/wiki/Triplestore" rel="nofollow">triplestore</a> like <a href="https://jena.apache.org/" rel="nofollow">Jena</a>. </p>
  
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Answers.CreationDate: 2016-08-26T18:58:53.653Z
Answers.LastActivityDate: 2016-08-26T18:58:53.653Z
Answers.UserDisplayName: mindcrime
Body: <p>I'm investigating the possibility of storing the semantic-lexical connections (such as the relationships to the other words such as phrases and other dependencies, its strength, part of speech, language, etc.) in order to provide analysis of the input text.</p>
  
  <p>I assume this has been already done. If so, to avoid reinventing the wheel, is there any efficient method to store and manage such data in some common format which has been already researched and tested?</p>
  
Tags: <algorithm><models><research><storage><lexical-recognition>
Title: How to store datasets of lexical connections?
UserDisplayName: kenorb
ThreadText: # How to store datasets of lexical connections?
  
  (Asked by: username_0 on 2016-08-03)
  
  I'm investigating the possibility of storing the semantic-lexical connections (such as the relationships to the other words such as phrases and other dependencies, its strength, part of speech, language, etc.) in order to provide analysis of the input text.
  
  I assume this has been already done. If so, to avoid reinventing the wheel, is there any efficient method to store and manage such data in some common format which has been already researched and tested?
  
  **Tags:** algorithm, models, research, storage, lexical-recognition
  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2016-08-26. Score: 1
  
  If I understand you correctly, you should check out **Word2Vec**. From [Wikipedia](https://en.wikipedia.org/wiki/Word2vec):
  
  > Word2vec is a group of related models that are used to produce word
  > embeddings. These models are shallow, two-layer neural networks that
  > are trained to reconstruct linguistic contexts of words. Word2vec
  > takes as its input a large corpus of text and produces a
  > high-dimensional space (typically of several hundred dimensions), with
  > each unique word in the corpus being assigned a corresponding vector
  > in the space. Word vectors are positioned in the vector space such
  > that words that share common contexts in the corpus are located in
  > close proximity to one another in the space.
  
  
  ---
  
  ### Answer by username_2 on 2016-08-26. Score: 1
  
  I would think you could use a [graph database](https://en.wikipedia.org/wiki/Graph_database), perhaps [Neo4J](https://neo4j.com/) or [Titan](http://titan.thinkaurelius.com/) or something of that nature. Or, if you want a simple file format, you could use one of the many formats that exist for representing graphs. You can find a list and overview of some of them [here](https://gephi.org/users/supported-graph-formats/).
  
  Another option would be to store them in [RDF](https://en.wikipedia.org/wiki/Resource_Description_Framework) using a [triplestore](https://en.wikipedia.org/wiki/Triplestore) like [Jena](https://jena.apache.org/).
  
  
  ---
  
  