Association for Computing Machinery
With the emergence of web-based social and information applications, entity similarity search in information networks, aiming to find entities with high similarity to a given query entity, has gained wide attention. However, due to the diverse semantic meanings in heterogeneous information networks, which contain multi-typed entities and relationships, similarity measurement can be ambiguous without context. In this paper, the authors investigate entity similarity search and the resulting ambiguity problems in heterogeneous in-formation networks. They propose to use a meta-path-based ranking model ensemble to represent semantic meanings for similarity queries, exploit the possibility of using user-guidance to understand users query.