A deep learning framework for book search

In this paper, we propose a novel framework using the word2vec model, a deep learning method, integrated with a book ontology in order to enhance semantically searching books. The idea starts from constructing a book ontology for reasoning book information efficiently. A deep learning method, namely the word2vec model, is then utilized to represent vectors of words occurring on book descriptions. These vectors would help finding most relevant books given a query string. The integration of the word2vec model and the book ontology is able to achieve high performance in searching books. A database of Amazon books is taken into account examining the proposed method, compared with an advanced keyword matching method. The experimental results show that the proposed method can produce more accurate searching results.