Intelligent Matching System of Clauses in International Investment Arbitration Cases Based on Big Data Statistical Model

Abstract

Abstract The international investment arbitration system between investors and host countries originated from the international commercial arbitration system. International investment disputes are usually disputes caused by the host country’s policies to protect public interests and the dissatisfaction of private investors caused by regulations. There are few methods for intelligently recommending judgment documents based on factual texts in international investment arbitration cases. Because of this, this paper proposes a recommendation algorithm for international investment arbitration adjudication documents based on multimodal feature fusion. This paper teaches the structural information of paragraph tags and the relationship between paragraph contexts and incomplete judgment documents. The algorithm achieves a good structuring effect of international investment arbitration documents.