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Found 5 papers, 2 papers with code
Transitivity, Time Consumption, and Quality of Preference Judgments in Crowdsourcing
In this work, we collect judgments from multiple judges using a crowdsourcing platform and aggregate them to compare the two kinds of preference judgments in terms of transitivity, time consumption, and quality.
Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval
Neural IR models, such as DRMM and PACRR, have achieved strong results by successfully capturing relevance matching signals.
PACRR: A Position-Aware Neural IR Model for Relevance Matching
In order to adopt deep learning for information retrieval, models are needed that can capture all relevant information required to assess the relevance of a document to a given user query.
Knowledge Questions from Knowledge Graphs
We address the novel problem of automatically generating quiz-style knowledge questions from a knowledge graph such as DBpedia.
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