基于情报元相似度的多源竞争情报片段融合方法研究

Approach of Multi-source Competitive Intelligence Fragments Fusion Based on Intelligence Element Similarity

[目的/意义]大数据环境下,多源情报的粗糙性与多学科、跨领域性,以及单源情报片段的片面性与模糊随机不确定性,为竞争情报的收集与分析带来挑战。[方法/过程]文章提出了一种基于情报元相似度的多源竞争情报片段融合方法,通过四次相似度分析过程,实现情报元的序化、融合以及重构,消除冗余和噪音信息的同时,解决了情报碎片的内容整合问题,为竞争情报的深度知识融合提供坚实的数据支撑。[结果/结论]针对企业A的实例研究,实现了多源情报片段产品情报元的相似度分析与融合,一定程度上体现了本方法的科学性、可行性和智能性。[局限]针对海量情报元的相似度算法待进一步优化。

[Purpose/significance] In the big data environment,the roughness,multidisciplinary and cross-domain characteristicsof multi-source intelligence,as well as the one-sidedness and fuzzy random uncertainty of single source intelligence fragments,bring challenges for the collection and analysis of competitive intelligence. [Method/process] This paper proposes an approach of multi-source competitive intelligence fragments fusion based on intelligence element similarity,which aims to eliminate the redundant and interferential information and solve the content integration problem of intelligence fragments through four processes of similarity analysis as well as the sequencing,integration and reconstruction strategies of intelligence element,which can provide a solid data support for the in-depth knowledge fusion of competitive intelligence. [Result/conclusion] A fusion case study of the enterprise A realizes the similarity analysis and fusion process of the product intelligence elements of multi-source intelligence fragments,which reflects the scientificity,feasibility and intelligence of this method to a certain extent. [Limitations]Similarity algorithm optimization of mass intelligence elements needs to be further carried out.