In web search today, a user types a few keywords and gets back links to web pages consisting of unstructured data. This leaves a lot to be desired for when there is structure data stores that can provide more relevant results for such queries. With our work, we aim to analyze the web query and extract structured semantics, map it to the corresponding structured data sources, and modify the web ranking functions to incorporate the results from the structured data. These techniques are general and are applicable to diverse domains, such as shopping, movies, autos, and travel. In fact we have created a collaboration with our search engine product team and part of our work is already included in live search.
Page Last Updated: 1 May 2009
- Stelios Paparizos, Entwining Structure into Web Search, in DBRank '13, ACM, August 2013
- Jeffrey Pound, Stelios Paparizos, and Panayiotis Tsaparas, Facet Discovery for Structured Web Search: A Query-log Mining Approach, in Proc. SIGMOD Conf., June 2011
- Nikos Sarkas, Stelios Paparizos, and Panayiotis Tsaparas, Structured Annotations of Web Queries, in Proc. SIGMOD Conf., June 2010
- Tao Cheng, Hady Lauw, and Stelios Paparizos, Fuzzy Matching of Web Queries to Structured Data, in Proc. ICDE Conf, March 2010
- Stelios Paparizos, Alexandros Ntoulas, John Shafer, and Rakesh Agrawal, Answering web queries using structured data sources, in Proc. SIGMOD Conf., June 2009