System and method based on large data analysis for achieving IT (information technology) argument collection

Abstract

The invention discloses a system and a method based on large data analysis for achieving IT argument collection. The method includes that, after a user presents a hypothetic viewpoint, the system automatically collects and analyzes arguments from an industrial macroscopic dimension, a customer demand dimension, a competitive information dimension and an expert opinion dimension; the system performs Internet retrieval and, according to retrieval results, performs large data analysis through a historical data method, a future data method, an inflection data method and a professional consultation data method to separately extract and analyze industrial arguments, customer arguments, competitor arguments and expert advice arguments, and to output large data analysis results in images, diagrams or texts.

Description

technical field [0001] The invention relates to the field of big data analysis, in particular to a system and method for realizing IT argument collection based on big data analysis. Background technique [0002] In some IT companies, telecommunications companies, consultants and other companies, they all have strategic planning departments or product planning departments. Planning engineers in these departments often provide business decision makers with certain business decision-making basis based on some analysis. In the analysis of planning engineers, some views of the industry or the industry are usually put forward for decision makers to refer to, but these views require a lot of evidence and arguments to support, which leads to a large workload for these engineers to demonstrate, and most of the time they spend Gather and query similar relevant information, and may not find very strong evidence. For example, the view that "SDN is the development trend of the future da...

AI Technical Summary

Problems solved by technology

In the analysis of planning engineers, some views of the industry or the industry are usually put forward for decision makers to refer to, but these views require a lot of evidence and arguments to support, which leads to a large workload for these engineers to demonstrate, and most of the time they spend Gather and query similar relevant information and may not find very strong evidence

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