Entity Relation Mining in Large-Scale Data

Currently, the web-based Named-Entity relationship extraction has been a new research field with a tremendous potential. The goal of web-based entity relationship extraction is to explore the relationship between a set of realistic entities. It’s a challenging research field and has a widely application value in the related fields of text mining. In this paper, we propose a newly defined framework called Snowball++ based on the traditional entity relationship extraction frameworks. In our Snowball++ framework, we focus on the many-to-many relations more than one-to-one relations. The system is also implemented in the many-to-many manner and it improves the precision and recall. It’s worth to notice that Snowball++ will assign a specific relation type to each entity-relationship pair and the whole training process only need a few manual labor. For the sake of building a efficient and scalable system, we implement the Snowball++ framework on the Hadoop platform which is a totally distributed computing system. Eventually, the experiments show that our framework and implementation are efficient and effective.