Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Paid placement strategies for internet search engines
Proceedings of the 11th international conference on World Wide Web
Modern Information Retrieval
Mining the Web: Discovering Knowledge from HyperText Data
Mining the Web: Discovering Knowledge from HyperText Data
Crawling a country: better strategies than breadth-first for web page ordering
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
WIM: An Information Mining Model for the Web
LA-WEB '05 Proceedings of the Third Latin American Web Congress
How much of it is real? Analysis of paid placement in Web search engine results
Journal of the American Society for Information Science and Technology
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Applications of web query mining
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Algorithmic challenges in web search engines
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
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We present the main algorithmic challenges that large Web search engines face today. These challenges are present in all the modules of a Web retrieval system, ranging from the gathering of the data to be indexed (crawling) to the selection and ordering of the answers to a query (searching and ranking). Most of the challenges are ultimately related to the quality of the answer or the efficiency in obtaining it, although some are relevant even to the existence of current search engines: context based advertising. As the Web grows and changes at a fast pace, the algorithms behind these challenges must rely in large scale experimentation, both in data volume and computation time, to understand the main issues that affect them. We show examples of our own research and of the state of the art. The full version of this paper appears in [1] .