Research On Key Technologies Of Patent-Value Mining Based On Hadoop

With the rapid expansion in the field of scientific and technological development and scientific research, new research results and innovations continue to emerge, mainly in the research literature. With the research on patents and reference relationship between patents and papers, we can better predict the development of technology, which has an important guiding significance on the development of the industrial sector. Patent searching becomes especially important. Assessing the patent, we need to analyze based on patent contents and use the existing text analysis technology to resolve patent research areas and key elements as the necessary research work.This paper researches on the status and background of patent. Because of the large number of patents, the analysis can be realized by MapReduce in the Hadoop framework to improve efficiency. Then analyze the text clustering architecture, including preprocessing text, text extraction, text similarity computation and do some improvements. Researching on text clustering algorithm is mainly Hierarchical Clustering algorithm and segmentation algorithm.This paper proposes an improved method for text similarity calculation, mainly to cover the feature words in the text, and this method adapts to solve the situation that a high degree of similarity is due to some high-weight words but low coverage of the text. Taking into account the special nature of patent, this paper uses patent title and patent abstract as an original text through above steps to the clustering analysis. Analyzing the experimental results, we can see now the disputes raised by patent are increasing largely, and the transfer of patent becomes more and more common, and enterprises gradually recognize the role of patents.Lastly, initial implementation of patent map can easily provide us with certain areas of the patent situation, and lead us to a thorough understanding of the technology-related patents to analyze patent value.