A Statistical Text Mining Method for Patent Analysis

Most text data from diverse document databases are unsuitable for analytical methods based on statistics and machine learning algorithms. Patent documents are also compiled into text datasets. Similar to other document datasets, we therefore need to transform patent documents into structured data for a statistical analysis. This transformation is performed using the preprocessing of text mining techniques. We can analyze the patent documents after their preprocessing. For a patent analysis, two phases, preprocessing and analysis, are required. In this paper, we try to combine the two phases into one. We propose a statistical text mining method to improve the performance of a patent data analysis. Our proposed method carries out text mining and a statistical analysis at the same time. To show the contribution of our study, we illustrate how it can be applied in a real domain using a target technology.