What actually is done in case of text summarization in case-based reasoning terminology is that, the situation is defined as the ensemble of some consecutive sentences, and the solution is the set of the sentences selected as the outcome of the summarization process. In order to make a quality summary considering the context, a semantic understanding, seems to be important. In this respect we propose an approach to use a two-layered CBR approach. Regarding this, we proposed an approach to text summarization based on two-layered case-based reasoning framework. Regarding this, the primary CBR cycle tries to make a summary of the source text, and the secondary CBR cycle tries to detect the context, and changes the bias values (fixed values) related to the primary CBR modules.
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