Towards a new summarization approach for search engine results: An application for Turkish

With the drastic increase of available information sources on the Internet, people with different backgrounds share the same problem: locating useful information for their actual needs. Search engines make this task easier only in certain ways; people still have to do the sifting process by themselves. At this point, automatic summarization can complement the task of search engines. In this paper, we consider a new summarization approach for Web information retrieval; i.e. structure-preserving and query-biased summarization. We evaluate this approach on Turkish Web documents using TREC-like topics defined for Turkish. The results of the task-based evaluation show that this approach has significant improvement over Google snippets and unstructured query-biased summaries in terms of f-measure using the relevance prediction approach.