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We propose a statistical semantic analysis method for Chinese terms. We use words, part-of-speech (POS) tags, word distances, word contexts and the first sememe of a word in HowNet as features to train a Support Vector Machine (SVM) model for analyzing term semantics. The model is used to identify dependencies embedded inside a term. A Conditional Random Field (CRF) model is used afterwards to incorporate...
The business world has become more dynamic than ever before. Global competition and today's rapid pace of development in many fields has led to shorter time-to-market intervals, as well as more complex products and services. These developments do often imply impromptu changes to existing business processes. These dynamics are aggravated when unforeseen paths have to be taken like it is often the case...
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