Software Engineering and Knowledge Engineering: Theory and by Zheng Shengbao, Jiang Shuping, Wang Xiaowen (auth.), Wei

By Zheng Shengbao, Jiang Shuping, Wang Xiaowen (auth.), Wei Zhang (eds.)

2012 foreign convention on software program Engineering, wisdom Engineering and data Engineering (SEKEIE 2012) can be held in Macau, April 1-2, 2012 . This convention will convey researchers and specialists from the 3 components of software program Engineering, wisdom Engineering and knowledge Engineering jointly to proportion their newest examine effects and ideas.

This quantity e-book lined major contemporary advancements within the software program Engineering, wisdom Engineering and knowledge Engineering box, either theoretical and utilized. we're comfortable this convention draws your attentions, and thank your help to our convention. we are going to take in impressive advice, and make our convention extra winning and perfect.

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Additional info for Software Engineering and Knowledge Engineering: Theory and Practice: Selected papers from 2012 International Conference on Software Engineering, Knowledge Engineering and Information Engineering (SEKEIE 2012)

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Now there are two ways to adjust array sequence of rule database: static adjust and dynamic adjust. 2 Static Adjustments Algorithm of Ordering Matching Rule A. Static adjustment algorithm of Statistical analysis Using Statistical analysis [3] algorithm to optimize the matching rules of network Intrusion detection refers to the algorithm which based on the used frequency within the stipulated period of time of intrusion detection matching rules. It dynamically adjusts the relative order of matching rules.

More authority to determine the weight of the approach is to use TF-IDF formula, that is Wik = tfik/ dfk tfik which is feature item in the document Di, frequency called the term frequency dfk is the set of documents D tk feature items appear in the number of documents, called the document frequency. ;t , w ) 1 1 2 2 n n Among them, wk is the weight of term tk,1 ≤ k ≤ n . 4 Vector Space Model, VSM The basic idea of vector space model is the m documents involved in all the features of items that appear to form an n-dimensional vector space T ( T1 , T2 , ⋯, Tn), where n is the total number of feature items.

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