Sentiment analysis and transfer learning using recurrent neural networks : an investigation of the power of transfer learning

University essay from Linköpings universitet/Interaktiva och kognitiva system

Abstract: In the field of data mining, transfer learning is the method of transferring knowledge from one domain into another. Using reviews from, a Swedish price comparison site, and this work investigate how the similarities between domains affect the results of transfer learning when using recurrent neural networks. We test several different domains with different characteristics, e.g. size and lexical similarity. In this work only relatively similar domains were used, the same target function was sought and all reviews were in Swedish. Regardless, the results are conclusive; transfer learning is often beneficial, but is highly dependent on the features of the domains and how they compare with each other’s.

  AT THIS PAGE YOU CAN DOWNLOAD THE WHOLE ESSAY. (follow the link to the next page)