Rank-preserving two-level caching for scalable search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Learning Algorithms for Keyphrase Extraction
Information Retrieval
Domain-Specific Keyphrase Extraction
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improved automatic keyword extraction given more linguistic knowledge
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
Mining search engine query logs via suggestion sampling
Proceedings of the VLDB Endowment
Coherent keyphrase extraction via web mining
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Relevance-index size tradeoff in contextual advertising
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Learning website hierarchies for keyword enrichment in contextual advertising
Proceedings of the fourth ACM international conference on Web search and data mining
Efficient Search Engine Measurements
ACM Transactions on the Web (TWEB)
Data Mining and Knowledge Discovery
Aggregate suppression for enterprise search engines
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Estimating clustering coefficients and size of social networks via random walk
Proceedings of the 22nd international conference on World Wide Web
Mining a search engine's corpus without a query pool
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The ImpressionRank of a web page (or, more generally, of a web site) is the number of times users viewed the page while browsing search results. ImpressionRank captures the visibility of pages and sites in search engines and is thus an important measure, which is of interest to web site owners, competitors, market analysts, and end users. All previous approaches to estimating the ImpressionRank of a page rely on privileged access to private data sources, like the search engine's query log. In this paper we present the first external algorithm for estimating the ImpressionRank of a web page. This algorithm relies on access to three public data sources: the search engine, the query suggestion service of the search engine, and the web. In addition, the algorithm is local and uses modest resources. It can therefore be used by almost any party to estimate the ImpressionRank of any page on any search engine. En route to estimating the ImpressionRank of a page, our algorithm solves a novel variant of the keyword extraction problem: it finds the most popular search keywords that drive impressions of a page. Empirical analysis of the algorithm on the Google and Yahoo! search engines indicates that it is accurate and provides interesting insights about sites and search queries.