Answers.Body: <p>Paraphrase generation would be made by an <a href="https://rare-technologies.com/text-summarization-in-python-extractive-vs-abstractive-techniques-revisited/#abstractive_text" rel="nofollow noreferrer">abstractive text summarization tool</a> like Tensorflow as described in <a href="https://research.googleblog.com/2016/08/text-summarization-with-tensorflow.html?m=1" rel="nofollow noreferrer">Google's blog</a>. </p>
  
  <p>Abstractive tool summarizes the text but also it adds extra words to make text more human like.</p>
  
  <p>About the second problem scenario I would say the answer depends quite much what you mean by the conclusions and how you think the conclusions would be made. I strongly believe this falls in the category of <a href="https://en.m.wikipedia.org/wiki/Artificial_general_intelligence" rel="nofollow noreferrer">artificial general intelligence</a>, which is emerging area of AI, supported by association <a href="http://www.agi-society.org" rel="nofollow noreferrer">AGI</a>, where the focus is on strong artificial intelligence and more human like features of AI. </p>
  
  <p>Judging about conclusions at least needs a vast knowledge base of the semantics of different words and pieces of text in general combined to possible conclusions and their legitimate implications. </p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-03T19:00:00.473Z
Answers.LastActivityDate: 2018-01-03T19:25:03.207Z
Answers.LastEditDate: 2018-01-03T19:25:03.207Z
Answers.UserDisplayName: mico
Body: <p>I was wondering any examples of the following;</p>
  
  <ul>
  <li><p>para generation: For eg, given X similar paragraphs,  are you able to build a model to learn the style and generate a new para that is a paraphrase of the X paras. Similar in meaning but diff wording.</p></li>
  <li><p>drawing conclusions from X given articles. He has a list of conclusions, check the X articles can provide evidence to the conclusions. Eg, given conclusion “city is not safe”, look for evidence such as “murders” and “thefts”.</p></li>
  </ul>
  
  <p>Glady Appreciate,
  Betty</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-03T17:27:59.800Z
Comments.Text: Welcome to AI!  Could you please clarify your terms?  When you say "para" , are you meaning "paragraph" or "paraphrase" or something else entirely?  I'm assuming the "diff" is intended, to connote line-oriented comparison function.  Apologies if my questions stem from ignorance of terms of art being utilized.)
Comments.UserDisplayName: DukeZhou
Tags: <machine-learning>
Title: Para Generation and Drawing Conclusion from X give Articles
UserDisplayName: user9167161
ThreadText: # Para Generation and Drawing Conclusion from X give Articles
  
  (Asked by: username_0 on 2018-01-03)
  
  I was wondering any examples of the following;
  
  * para generation: For eg, given X similar paragraphs, are you able to build a model to learn the style and generate a new para that is a paraphrase of the X paras. Similar in meaning but diff wording.
  * drawing conclusions from X given articles. He has a list of conclusions, check the X articles can provide evidence to the conclusions. Eg, given conclusion “city is not safe”, look for evidence such as “murders” and “thefts”.
  
  Glady Appreciate,
  Betty
  
  **Tags:** machine-learning
  > **Comments:**
  > **username_1**: Welcome to AI!  Could you please clarify your terms?  When you say "para" , are you meaning "paragraph" or "paraphrase" or something else entirely?  I'm assuming the "diff" is intended, to connote line-oriented comparison function.  Apologies if my questions stem from ignorance of terms of art being utilized.)  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2018-01-03. Score: 1
  
  Paraphrase generation would be made by an [abstractive text summarization tool](https://rare-technologies.com/text-summarization-in-python-extractive-vs-abstractive-techniques-revisited/#abstractive_text) like Tensorflow as described in [Google's blog](https://research.googleblog.com/2016/08/text-summarization-with-tensorflow.html?m=1).
  
  Abstractive tool summarizes the text but also it adds extra words to make text more human like.
  
  About the second problem scenario I would say the answer depends quite much what you mean by the conclusions and how you think the conclusions would be made. I strongly believe this falls in the category of [artificial general intelligence](https://en.m.wikipedia.org/wiki/Artificial_general_intelligence), which is emerging area of AI, supported by association [AGI](http://www.agi-society.org), where the focus is on strong artificial intelligence and more human like features of AI.
  
  Judging about conclusions at least needs a vast knowledge base of the semantics of different words and pieces of text in general combined to possible conclusions and their legitimate implications.
  
  
  ---
  
  