Component Based Summarization Using Automatic Identification Of Cross-Document Structural Relationship

The world we live today witnesses a fast moving information age due to the ever increasing information available online. People are being exposed vast online documents, being retrieved from various sources. The need for automatic document summarization system has deemed necessary to alleviate information overload. In the context of online news documents, different news sources reporting on a particular event tend to contain common components that make up the main story of the news. Based on this conception, we propose component based summarization, i.e. taking into account the generic components of a news story to produce quality summaries. We focus particularly on news stories related to natural disaster events. Besides that, we also investigate the automatic identification of cross structural relationships (CST) between sentences using case base reasoning (CBR) approach. The identified CST relations will be used to extract highly relevant sentences to be included in the summary. As for the evaluation process, the performance of our proposed approach was evaluated using ROUGE: - a standard evaluation metric used in text summarization