Efficient entity relation discovery on Web

With popularization of Web, there are billions of pages on Web, which contain affluent information of real world entities and their relations. Therefore, much research focuses on named entity extraction and entity relation discovery for constructing social networks which can reflect the real society. However, some former entity relation discovery approaches, extracting a small group of entities in a limited community or intranet, is not so scalable. So when it is applied to a large group of entities on Web, it may fail. In this paper, we employ co-occurrence to identify the relations between entities. The contribution of the paper is: 1. Empirically evaluating various frequently used measures for co-occurrence and find Cosine outperforms the others; 2. Presenting two novel efficient algorithms for discovering relations between entities and comparing them.EI041699-1704