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Computational Linguistics and Information Processing

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==Machine Translation==
In the CLIP lab, we approach research on computational linguistics and information processing from a variety of angles. Some of our ongoing projects focus on the following challenges:


==Summarization ==
* Computational psycholinguistics
* Computational social science
* Cross-language information retrieval
* Data science for finance / social good
* Deep learning
* Pattern discover in graphs / ranking and recommendation
* Human-in-the-loop machine learning
* Machine translation
* Mental health
* Privacy-aware information retrieval
* Speech retrieval
* Urban computing / smart environments


==Parsing and Tagging==
CLIP research has been supported by the following organizations: NSF, DARPA, ARL, IARPA, OFR (Treasury), NIST, IMLS, Google, Yahoo and the World Bank.
 
==Sentiment Analysis==
 
==Bayesian Modeling==
 
{| border="0" cellpadding="5" cellspacing="0" align="center"
|-
! colspan="3" style="background: #ffefef;" | Cross‐language Bayesian models for Web‐scale text analysis using MapReduce
|-
| PI
| Jimmy Lin
|-
| Other Faculty
| Jordan Boyd-Graber, Philip Resnik
|-
| style="border-bottom: 3px solid grey;" | lower left
| style="border-bottom: 3px solid grey;" | lower middle
|-
| colspan="3" align="center" |
{| border="0"
|+ ''A table in a table''
|-
| align="center" width="150" | [[File:Wiki.png]]
| align="center" width="150" | [[File:Wiki.png]]
|-
| align="center" colspan="2" style="border-top: 1px solid red;<!--
  --> border-right: 1px solid red; border-bottom: 2px solid red;<!--
  --> border-left: 1px solid red;" |
Two Wikipedia logos
|}
|}

Latest revision as of 15:41, 23 September 2020

In the CLIP lab, we approach research on computational linguistics and information processing from a variety of angles. Some of our ongoing projects focus on the following challenges:

  • Computational psycholinguistics
  • Computational social science
  • Cross-language information retrieval
  • Data science for finance / social good
  • Deep learning
  • Pattern discover in graphs / ranking and recommendation
  • Human-in-the-loop machine learning
  • Machine translation
  • Mental health
  • Privacy-aware information retrieval
  • Speech retrieval
  • Urban computing / smart environments

CLIP research has been supported by the following organizations: NSF, DARPA, ARL, IARPA, OFR (Treasury), NIST, IMLS, Google, Yahoo and the World Bank.