earticle

영어

Knowledge mapping will undoubtedly bring great convenience to application users for being behind the strong support of knowledge base. In this paper, we study how to discover the evolution of knowledge map in multi-languages. Our approach is uniquely designed to capture the rich topology of semantic items and to link the sub-graph to a global knowledge map. Instead of building a knowledge map start from scratch, we conceptually define semantic classes as a quantized unit of evolutionary link in sub-graph and discover new knowledge with multi-language dictionaries. Discovered new knowledge items are then connected to form an evolution knowledge map using a measure derived from the underlying semantic classes. We integrate these noisy items and entities into a unified probabilistic knowledge map using ideas from graph-based algorithm.