In a broader sense, this model attempts to map a long text (i.e., paper abstract) with representative short text chunks (i.e., keyphrases), which can potentially be applied to improve information retrieval performance by generating high-quality index terms, as well as assisting user browsing by summarizing long documents into short, readable phrases.
far, we have tested our model with scientific publications and news articles, and have demonstrated that our model has the ability to capture universal language patterns and extract key information from unfamiliar texts.