Developing Structure-preserving and Query-biased Automated Summarization Methods for Web Search Engines

In this project, a new summarization approach was developed to improve the effectiveness of Web search based on two stages. In the first stage, a rule-based approach and a machine learning approach were implemented to identify the sectional hierarchies of Web documents. In the second stage, query-biased summaries are created based on document structure. The evaluation results show that the system has significant improvement over unstructured summaries and Google snippets.

Funding Institution: 


Principal Investigator / Project Partner: 

Tunga Güngör


2006 to 2007

Project Code: 


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