Abstract: Vacant Technology Forecasting based on Patent Analysis Using an Ensemble Method and Bayesian Clustering
نویسنده
چکیده
Patent analysis is an important approach to technology forecasting because patents are an important component of developing technology. Also, we use the results of technology forecasting to build the R&D strategies efficiently. In this paper, we consider patent clustering as one of patent analyses. That is, we cluster patent documents in order to forecast the vacant area of a given technology field. This research proposes an ensemble method and Bayesian clustering for patent clustering. This research calls this new hybrid Bayesian clustering method. Furthermore, in order to determine the performance of our study, we present a case study using retrieved patent documents related to “humanoid robots and systems” from the United States Patent and Trademark Office. Therefore, in the experimental results, we will find the vacant technology area of “humanoid robots and systems” technology.
منابع مشابه
A Clustering Method of Highly Dimensional Patent Data Using Bayesian Approach
Patent data have diversely technological information of any technology field. So, many companies have managed the patent data to build their R&D policy. Patent analysis is an approach to the patent management. Also, patent analysis is an important tool for technology forecasting. Patent clustering is one of the works for patent analysis. In this paper, we propose an efficient clustering method ...
متن کاملHigh-Dimensional Unsupervised Active Learning Method
In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...
متن کاملSteel Consumption Forecasting Using Nonlinear Pattern Recognition Model Based on Self-Organizing Maps
Steel consumption is a critical factor affecting pricing decisions and a key element to achieve sustainable industrial development. Forecasting future trends of steel consumption based on analysis of nonlinear patterns using artificial intelligence (AI) techniques is the main purpose of this paper. Because there are several features affecting target variable which make the analysis of relations...
متن کاملCombination of Transformed-means Clustering and Neural Networks for Short-Term Solar Radiation Forecasting
In order to provide an efficient conversion and utilization of solar power, solar radiation datashould be measured continuously and accurately over the long-term period. However, the measurement ofsolar radiation is not available to all countries in the world due to some technical and fiscal limitations. Hence,several studies were proposed in the literature to find mathematical and physical mod...
متن کاملA new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble
An ensemble clustering has been considered as one of the research approaches in data mining, pattern recognition, machine learning and artificial intelligence over the last decade. In clustering, the combination first produces several bases clustering, and then, for their aggregation, a function is used to create a final cluster that is as similar as possible to all the cluster bundles. The inp...
متن کامل