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» Aggregating User-Centered Rankings to Improve Web Search
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WSDM
2009
ACM
104views Data Mining» more  WSDM 2009»
14 years 1 months ago
Top-k aggregation using intersections of ranked inputs
There has been considerable past work on efficiently computing top k objects by aggregating information from multiple ranked lists of these objects. An important instance of this...
Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vas...
SIGIR
2010
ACM
13 years 10 months ago
How good is a span of terms?: exploiting proximity to improve web retrieval
Ranking search results is a fundamental problem in information retrieval. In this paper we explore whether the use of proximity and phrase information can improve web retrieval ac...
Krysta Marie Svore, Pallika H. Kanani, Nazan Khan
ECIR
2011
Springer
12 years 10 months ago
Introducing the User-over-Ranking Hypothesis
The User-over-Ranking hypothesis states that rather the user herself than a web search engine’s ranking algorithm can help to improve retrieval performance. The means are longer ...
Benno Stein, Matthias Hagen
WWW
2010
ACM
14 years 1 months ago
Exploring searcher interactions for distinguishing types of commercial intent
An improved understanding of the relationship between search intent, result quality, and searcher behavior is crucial for improving the effectiveness of web search. While recent p...
Qi Guo, Eugene Agichtein
WWW
2004
ACM
14 years 7 months ago
Updating pagerank with iterative aggregation
We present an algorithm for updating the PageRank vector [1]. Due to the scale of the web, Google only updates its famous PageRank vector on a monthly basis. However, the Web chan...
Amy Nicole Langville, Carl Dean Meyer