Improving pseudo-relevance feedback in web information retrieval using web page segmentation

By Shipeng Yu, Deng Cai, Ji-rong Wen, Wei-Ying Ma. The Web Conference, 2003

317 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems

View Paper: https://www.semanticscholar.org/paper/a46b1fe633d6f533a0c26e2f3fe909ced0f686b7

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In Computer Vision and Pattern Recognition

In Information Systems

Citations in the corpus

Learning block importance models for web pages (2004, background): “The most popular ones are DOM-based segmentation [4], location-based segmentation [9] and Vision-based Page Segmentation (VIPS) [17][3].”
Hierarchical clustering of WWW image search results using visual, textual and link information (2004, background): “Many research show that VIPS can greatly improve the performance of web search [6][8][26].”
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models (2017, methodology): “It is also worth comparing IRGAN with pseudo relevance feedback [39, 45, 50], where the top retrieved documents are selected to rene the ranking result.”
Extracting Content Structure for Web Pages Based on Visual Representation (2003, methodology): “7, we can see that pseudo-relevance feedback based on web page content structure significantly outperforms traditional methods and achieves about 27% performance improvement on the Web Track dataset (refer to [17] for more details).”
Detecting Phishing Web Pages with Visual Similarity Assessment Based on Earth Mover's Distance (EMD) (2006, background): “The Web page obfuscation can be carried out in three basic ways: 1. using the downloaded Web page from the real Web site to make the phishing Web page appear and react exactly the same as the real one does, 2. using a script or images to cover the address bar to scam users into believing they have…”
Personalized query expansion for the web (2007, background): “[38] selected the expansion terms from vision-based segments of Web pages in order to cope with the multiple topics residing therein.”
A Survey of Automatic Query Expansion in Information Retrieval (2012, methodology): “An earlier textual form of this approach is passage selection [Xu and Croft 1996]; other AQE methods suitable for web pages involve more sophisticated features such as visual clues [Yu et al. 2003] or tables and forms [Graupmann et al.”