关键词: 信息网络, 信息维, 拓扑维, 在线图处理, 多维信息网络数据仓库模型

Abstract: With the emergence of information network，the information evolves from simple numerical data to complex graph network. How to organize and store the information network data becomes an urging problem. This paper proposes a multi-dimension information network datawarehouse model (MINDM), which aims to provide the data foundation to online graph processing. The MINDM includes edge fact table, node fact table, information link attribution table and topology node attribution table. The experimental results show that the MINDM can eliminate redundancy, reduce the cost of average query time, and save the space storage. The query time remains stable within a few milliseconds while performing queries on the 12.5 thousand ACM papers real dataset, keeping sharp comparison to van relation model with more than hundreds of milliseconds for the same processing stage. With the number of papers growing, the storage space of the proposed model increases much slower than the van relation model.

Key words: InfoNetwork, informational dimension, topological dimension, online graph processing, multi-dimensional information network datawarehouse model