FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2893036933> ?p ?o ?g. }

• W2893036933 endingPage "354" @default.
• W2893036933 startingPage "329" @default.
• W2893036933 abstract "Preference data occur when assessors express comparative opinions about a set of items, by rating, ranking, pair comparing, liking, or clicking. The purpose of preference learning is to ( a) infer on the shared consensus preference of a group of users, sometimes called rank aggregation, or ( b) estimate for each user her individual ranking of the items, when the user indicates only incomplete preferences; the latter is an important part of recommender systems. We provide an overview of probabilistic approaches to preference learning, including the Mallows, Plackett–Luce, and Bradley–Terry models and collaborative filtering, and some of their variations. We illustrate, compare, and discuss the use of these methods by means of an experiment in which assessors rank potatoes, and with a simulation. The purpose of this article is not to recommend the use of one best method but to present a palette of different possibilities for different questions and different types of data." @default.
• W2893036933 created "2018-10-05" @default.
• W2893036933 creator A5022332974 @default.
• W2893036933 creator A5025750693 @default.
• W2893036933 creator A5053277407 @default.
• W2893036933 creator A5060177975 @default.
• W2893036933 creator A5061402879 @default.
• W2893036933 date "2019-03-07" @default.
• W2893036933 modified "2023-10-16" @default.
• W2893036933 title "Model-Based Learning from Preference Data" @default.
• W2893036933 cites W1596709027 @default.
• W2893036933 cites W1966729776 @default.
• W2893036933 cites W1973196098 @default.
• W2893036933 cites W2022838594 @default.
• W2893036933 cites W2033442452 @default.
• W2893036933 cites W2049540116 @default.
• W2893036933 cites W2049689417 @default.
• W2893036933 cites W2054141820 @default.
• W2893036933 cites W2063445365 @default.
• W2893036933 cites W2074184241 @default.
• W2893036933 cites W2075196028 @default.
• W2893036933 cites W2085040216 @default.
• W2893036933 cites W2101409192 @default.
• W2893036933 cites W2103322363 @default.
• W2893036933 cites W2112420033 @default.
• W2893036933 cites W2152977846 @default.
• W2893036933 cites W2160637580 @default.
• W2893036933 cites W2165836430 @default.
• W2893036933 cites W2200988052 @default.
• W2893036933 cites W2217766582 @default.
• W2893036933 cites W2299232349 @default.
• W2893036933 cites W2320532185 @default.
• W2893036933 cites W2496838373 @default.
• W2893036933 cites W2563497845 @default.
• W2893036933 cites W2749733699 @default.
• W2893036933 cites W2782656953 @default.
• W2893036933 cites W298464722 @default.
• W2893036933 cites W3098280172 @default.
• W2893036933 cites W3099508828 @default.
• W2893036933 cites W3099791880 @default.
• W2893036933 cites W4211124088 @default.
• W2893036933 cites W4248672808 @default.
• W2893036933 cites W646847456 @default.
• W2893036933 cites W1555310745 @default.
• W2893036933 doi "https://doi.org/10.1146/annurev-statistics-031017-100213" @default.
• W2893036933 hasPublicationYear "2019" @default.
• W2893036933 type Work @default.
• W2893036933 sameAs 2893036933 @default.
• W2893036933 citedByCount "13" @default.
• W2893036933 countsByYear W28930369332017 @default.
• W2893036933 countsByYear W28930369332019 @default.
• W2893036933 countsByYear W28930369332020 @default.
• W2893036933 countsByYear W28930369332021 @default.
• W2893036933 countsByYear W28930369332022 @default.
• W2893036933 countsByYear W28930369332023 @default.
• W2893036933 crossrefType "journal-article" @default.
• W2893036933 hasAuthorship W2893036933A5022332974 @default.
• W2893036933 hasAuthorship W2893036933A5025750693 @default.
• W2893036933 hasAuthorship W2893036933A5053277407 @default.
• W2893036933 hasAuthorship W2893036933A5060177975 @default.
• W2893036933 hasAuthorship W2893036933A5061402879 @default.
• W2893036933 hasBestOaLocation W28930369332 @default.
• W2893036933 hasConcept C105795698 @default.
• W2893036933 hasConcept C114614502 @default.
• W2893036933 hasConcept C119857082 @default.
• W2893036933 hasConcept C154945302 @default.
• W2893036933 hasConcept C164226766 @default.
• W2893036933 hasConcept C177264268 @default.
• W2893036933 hasConcept C181204326 @default.
• W2893036933 hasConcept C189430467 @default.
• W2893036933 hasConcept C199360897 @default.
• W2893036933 hasConcept C21569690 @default.
• W2893036933 hasConcept C23123220 @default.
• W2893036933 hasConcept C2781249084 @default.
• W2893036933 hasConcept C33923547 @default.
• W2893036933 hasConcept C41008148 @default.
• W2893036933 hasConcept C49937458 @default.
• W2893036933 hasConcept C557471498 @default.
• W2893036933 hasConcept C58489278 @default.
• W2893036933 hasConcept C86037889 @default.
• W2893036933 hasConceptScore W2893036933C105795698 @default.
• W2893036933 hasConceptScore W2893036933C114614502 @default.
• W2893036933 hasConceptScore W2893036933C119857082 @default.
• W2893036933 hasConceptScore W2893036933C154945302 @default.
• W2893036933 hasConceptScore W2893036933C164226766 @default.
• W2893036933 hasConceptScore W2893036933C177264268 @default.
• W2893036933 hasConceptScore W2893036933C181204326 @default.
• W2893036933 hasConceptScore W2893036933C189430467 @default.
• W2893036933 hasConceptScore W2893036933C199360897 @default.
• W2893036933 hasConceptScore W2893036933C21569690 @default.
• W2893036933 hasConceptScore W2893036933C23123220 @default.
• W2893036933 hasConceptScore W2893036933C2781249084 @default.
• W2893036933 hasConceptScore W2893036933C33923547 @default.
• W2893036933 hasConceptScore W2893036933C41008148 @default.
• W2893036933 hasConceptScore W2893036933C49937458 @default.
• W2893036933 hasConceptScore W2893036933C557471498 @default.
• W2893036933 hasConceptScore W2893036933C58489278 @default.
• W2893036933 hasConceptScore W2893036933C86037889 @default.

• next