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We propose in this paper a new, hybrid document embedding approach in orderto address the problem of document similarities with respect to the technicalcontent. To do so, we employ a state-of-the-art graph techniques to firstextract the keyphrases (composite keywords) of documents and, then, use them toscore the sentences. Using the ranked sentences, we propose two approaches toembed documents and show their performances with respect to two baselines. Withdomain expert annotations, we illustrate that the proposed methods can findmore relevant documents and outperform the baselines up to 27% in terms ofNDCG.

Terminology-based Text Embedding for Computing Document Similarities on Technical Content