Abstract
Patent is one of the most valuable intelligent properties. It not only protects inventions and ideas but also is an economic source of enterprises. Since that, it is important for enterprises to detect patent infringement to avoid any legal and economic risks. Patent prior art search task is mainly to identify prior patents that are relevant to a patent application. Thus, a system for retrieving patent prior art is expected to obtain the set of patents which are the most relevant to a target patent. Beyond the existing achievements including patent claim structure in prior retrieval, this research enhances the time efficiency and accuracy of the patient prior retrieval task by using cloud computing and semantic term expansion. The major contribute of this research is to enhance the prior art retrieval system in terms of time efficiency and accuracy, by which enterprises or patent analyzers are operationally viable to identify the most relevant prior patents in filing or approving a new patent