There have been significant efforts to understand, describe, and predict the social commerce intention of users in the areas of social commerce and web data management. Based on recent developments in knowledge graph and inductive logic programming in artificial intelligence, in this paper, we propose a knowledge-graph-based social commerce intention analysis method. In particular, a knowledge base is constructed to represent the social commerce environment by integrating information related to social relationships, social commerce factors, and domain background knowledge. In this study, knowledge graphs are used to represent and visualize the entities and relationships related to social commerce, while inductive logic programming techniques are used to discover implicit information that can be used to interpret the information behaviors and intentions of the users. Evaluation tests confirmed the effectiveness of the proposed method. In addition, the feasibility of using knowledge graphs and knowledge-based data mining techniques in the social commerce environment is also confirmed.

中文翻译：

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基于知识图分析的社会商务意图解读与预测

在社交商务和Web数据管理领域，人们已经做出了巨大的努力来理解，描述和预测用户的社交商务意图。基于人工智能知识图和归纳逻辑程序设计的最新发展，本文提出了一种基于知识图的社会商业意图分析方法。特别是，通过集成与社交关系，社交商务因素和领域背景知识有关的信息，构建了一个代表社交商务环境的知识库。在这项研究中，知识图用于表示和可视化与社交商务相关的实体和关系，而归纳逻辑编程技术则用于发现隐式信息，这些隐式信息可用于解释用户的信息行为和意图。评估测试证实了该方法的有效性。此外，还证实了在社交商务环境中使用知识图和基于知识的数据挖掘技术的可行性。