Corporate Decision Making with Self-Organizing Patent Maps Labeled by Technical Terms and AHP
نویسندگان
چکیده
In this paper, we propose an approach for corporate decision making with self-organizing patent maps labeled by technical terms and AHP. First, we select the patent area of interest and collect pertinent patent documents in text format. Second, we extract keywords by text mining to transform patent documents into feature vectors of the companies. Third, we input the feature matrix of technical terms and company names into self-organizing maps to create patent maps labeled by the technical terms. Then, we consider several corporate strategies utilizing the patent maps and make a decision with AHP. We apply our approach to two patent areas (information home appliance and 3D image) to show examples of corporate decision making.
منابع مشابه
Considering Corporate Strategies with Self-Organizing Patent Maps and Decision Making with AHP
Previously, we proposed an approach for corporate decision making with self-organizing patent maps labeled by technical terms and AHP. First, we extracted keywords by text mining to transform patent documents into feature vectors of the companies. Second, we inputted the feature matrix of technical terms and company names into self-organizing maps to create patent maps labeled by the technical ...
متن کاملCreating Product Maps with Self-Organizing Maps for Purchase Decision Making
We propose a way of creating product maps with self-organizing maps (SOMs) for purchase decision making. We previously proposed a way of purchase decision support using SOMs and the Analytic Hierarchy Process (AHP). We provided several class boundaries, which divided the input features into several classes before creating self-organizing product maps. Because the number of classes and their bou...
متن کاملComprehensive Decision Modeling of Reverse Logistics System: A Multi-criteria Decision Making Model by using Hybrid Evidential Reasoning Approach and TOPSIS (TECHNICAL NOTE)
In the last two decades, product recovery systems have received increasing attention due to several reasons such as new governmental regulations and economic advantages. One of the most important activities of these systems is to assign returned products to suitable reverse manufacturing alternatives. Uncertainty of returned products in terms of quantity, quality, and time complicates the decis...
متن کاملDecision Manifolds: Classification Inspired by Self-Organization
We present a classifier algorithm that approximates the decision surface of labeled data by a patchwork of separating hyperplanes. The hyperplanes are arranged in a way inspired by how Self-Organizing Maps are trained. We take advantage of the fact that the boundaries can often be approximated by linear ones connected by a low-dimensional nonlinear manifold. The resulting classifier allows for ...
متن کاملGait Based Vertical Ground Reaction Force Analysis for Parkinson’s Disease Diagnosis Using Self Organizing Map
The aim of this work is to use Self Organizing Map (SOM) for clustering of locomotion kinetic characteristics in normal and Parkinson’s disease. The classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. The proposed methodology aims at overcoming the constraints of traditional analysi...
متن کامل