We report a comprehensive evaluation showing that rank-based features allow us to achieve the desired effectiveness with ranking models being up to 3.5 times ...
People also ask
What helps SEO ranking?
What is ranking and retrieval?
ABSTRACT. Learning to Rank (LtR) is an effective machine learning me- thodology for inducing high-quality document ranking func-.
We report a comprehensive evaluation showing that rank-based features allow us to achieve the desired effectiveness with ranking models being up to 3.5 times ...
Speeding Up Document Ranking with Rank-based Features. Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto. 2015.
We report a comprehensive evalu- ation showing that rank-based features allow us to achieve the desired effectiveness with ranking models being up to 3.5 times ...
Jan 16, 2024 · The role of LTR is to use many additional features, on a smaller top N, to tie-break documents up and down relative to this rough first pass.
Missing: Speeding | Show results with:Speeding
Dec 6, 2010 · An interesting algorithm - called DocRank - for creating a PageRank like score for business documents (ie documents without links like PDF, MS Word documents, ...
Missing: Speeding | Show results with:Speeding
Nov 17, 2023 · Ranking is a class of supervised learning algorithms that aim to sort a list of items based on their relevance to a query.
The commit- tee perceptron algorithm improves upon existing solutions by biasing the final solution towards maximizing an arbi- trary rank-based performance ...
This paper investigates the opportunities offered by modern graphic cards (GPUs) to efficiently exploit LtR complex models based on trees ensembles to rank ...