document: Identifying primary content from web pages and its application to web search ranking Web pages are usually highly structured documents . In some documents , content with different functionality is laid out in blocks , some merely supporting the main discourse . In other documents , there may be several blocks of unrelated main content . Indexing a web page as if it were a linear document can cause problems because of the diverse nature of its content . If the retrieval function treats all blocks of the web page equally without attention to structure , it may lead to irrelevant query matches . In this paper , we describe how content quality of different blocks of a web page can be utilized to improve a retrieval function . Our method is based on segmenting a web page into semantically coherent blocks and learning a predictor of segment content quality . We also describe how to use segment content quality estimates as weights in the BM25F formulation . Experimental results show our method improves relevance of retrieved results by as much as 4.5 % compared to BM25F that treats the body of a web page as a single section , and by a larger margin of over 9 % for difficult queries .
doc_bio_tags: O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O