Text Auto-complete feature suggests a stream of words which complete a user's text as the user types each character. Such a feature is used in search engines, email programs, source code editors, database query tools etc. Earlier people have used traditional language models for this problem. But for better performance, a Neural network-based language model is needed. Here, an encoder-decoder based sequence-to-sequence language model has been used for performing text generation and the empirical results show that the model effectively suggests the incomplete sentences.


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    Title :

    E-mail autocomplete function using RNN Encoder-decoder sequence-to-sequence model


    Contributors:


    Publication date :

    2021-12-02


    Size :

    908576 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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