Abstract: With the development of Internet，the event from large amount of Internet information，which is important and will become chance，can be extracted.The traditional algorithms，which are based on the model of high frequency，are hard to discover the important and unobserved event.In this paper，a new automatic keyword exaction method based on Small-World Network theory，is proposed.This method is based on the ideas of KeyGraph，constructs the graph of terms and relation，and is optimized by Small-World Network theory.The extracted words can represent more information of the document content，and the low frequent but important terms can also be extracted.Finally，through experiment validated，latency event，which is extracted by this method，is chance.

Key words: keyword extraction, small-world network, chance

摘要： 随着互联网络的不断发展，人们需要从大量数据中提取可能成为机会的信息，传统的基于高频模式的重要事件提取算法不能满足现状。提出了一种基于小世界网络（Small World）理论的关键字提取算法，该算法以KeyGraph思想为基础，构建词语关联图，并利用小世界理论对图进行优化，从而不仅能够发现高频事件，而且能够发现相对低频而且意义重要的事件。最后，通过实验验证，用该算法提取的潜在事件是机会。

关键词: 关键字提取, 小世界网络, 机会