Add to ORKGContains fulltext : 79177.pdf (author's version ) (Open Access)Workshop Learning to Rank for Information Retrieval (LR4IR 2009
International audienceWe investigate the problem of passage retrieval for Question Answering (QA) sy...
We investigate the problem of passage retrieval for Question Answering (QA) systems. We adopt a mach...
RankEval is a Python open-source tool for the analysis and evaluation of ranking models based on ens...
Contains fulltext : 79174.pdf (author's version ) (Open Access)Dutch-Belgium Infor...
Contains fulltext : 86344.pdf (publisher's version ) (Open Access)26 p
Contains fulltext : 227663.pdf (publisher's version ) (Closed access
Contains fulltext : 92097.pdf (preprint version ) (Open Access)International Confe...
This paper is concerned with learning to rank for information retrieval (IR). Ranking is the central...
Due to the fast growth of the Web and the difficulties in finding desired information, efficient and...
Ranking is a core problem for information retrieval since the performance of the search system is di...
Purpose - Learning to rank algorithms inherently faces many challenges. The most important challenge...
This work describes an answer ranking engine for non-factoid questions built using a large online co...
Relevance feedback is the most popular query reformulation strategy. However, clicking data as user&...
Learning to Rank (LtR) is an effective machine learning methodology for inducing high-quality docume...
Ranking a set of documents based on their relevances with respect to a given query is a central prob...
International audienceWe investigate the problem of passage retrieval for Question Answering (QA) sy...
We investigate the problem of passage retrieval for Question Answering (QA) systems. We adopt a mach...
RankEval is a Python open-source tool for the analysis and evaluation of ranking models based on ens...
Contains fulltext : 79174.pdf (author's version ) (Open Access)Dutch-Belgium Infor...
Contains fulltext : 86344.pdf (publisher's version ) (Open Access)26 p
Contains fulltext : 227663.pdf (publisher's version ) (Closed access
Contains fulltext : 92097.pdf (preprint version ) (Open Access)International Confe...
This paper is concerned with learning to rank for information retrieval (IR). Ranking is the central...
Due to the fast growth of the Web and the difficulties in finding desired information, efficient and...
Ranking is a core problem for information retrieval since the performance of the search system is di...
Purpose - Learning to rank algorithms inherently faces many challenges. The most important challenge...
This work describes an answer ranking engine for non-factoid questions built using a large online co...
Relevance feedback is the most popular query reformulation strategy. However, clicking data as user&...
Learning to Rank (LtR) is an effective machine learning methodology for inducing high-quality docume...
Ranking a set of documents based on their relevances with respect to a given query is a central prob...
International audienceWe investigate the problem of passage retrieval for Question Answering (QA) sy...
We investigate the problem of passage retrieval for Question Answering (QA) systems. We adopt a mach...
RankEval is a Python open-source tool for the analysis and evaluation of ranking models based on ens...