Mining frequent phrases from social media

Funding Details
Natural Sciences and Engineering Research Council of Canada
  • Grant type: Engage Grants Program
  • Year: 2015/16
  • Total Funding: $25,000
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Project Summary

One of the main aspects of a mobile keyboard application is to predict the most possible intended next word as a user types a sequence of either words or letters. This prediction has to be performed accurately. An accurate prediction suggests words, which a user intends to choose as the next word. In fact, a prediction is accurate if the users choose the next word from the suggested list. Language modeling is the de facto approach for supporting this type of language prediction. In this research project, we are interested in designing a highly accurate language models for a mobile Keyboard platform, based on the state of the art techniques in Natural Language Processing and Information Retrieval. We will build a training corpus by adding new vocabularies, which are not seen in a Standard English corpus to facilitate typing in social networks environment such as Twitter.

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