Matches in SemOpenAlex for { <https://semopenalex.org/work/W3206914405> ?p ?o ?g. }
- W3206914405 endingPage "25307" @default.
- W3206914405 startingPage "25297" @default.
- W3206914405 abstract "Intelligent human-device interfaces play key roles in fully automated vehicles (FAVs), ensuring smooth interactions and improving the driving experience. Listening to news is a popular method of relaxing during a journey; as a result, travelers require automatic recommendations of preferred news programs. Most existing news recommender systems usually learn topic-level representations of users and news for recommendations while neglecting to learn more informative aspect-level features, resulting in limited recommendation performance. To bridge this significant gap, we propose a novel Aspect-driven News Recommender System (ANRS) built on aspect-level user preferences and news representation learning. In ANRS, a news aspect-level encoder and a user aspect-level encoder are devised to learn the fine-grained aspect-level representations of users’ preferences and news characteristics respectively. These representations are subsequently fed into a click predictor to predict the probability of a given user clicking on the candidate news item. Extensive experiments demonstrate the superiority of our method over state-of-the-art baseline methods." @default.
- W3206914405 created "2021-10-25" @default.
- W3206914405 creator A5016151794 @default.
- W3206914405 creator A5034219446 @default.
- W3206914405 creator A5043549588 @default.
- W3206914405 creator A5052441498 @default.
- W3206914405 creator A5070178549 @default.
- W3206914405 creator A5082317196 @default.
- W3206914405 date "2022-12-01" @default.
- W3206914405 modified "2023-10-16" @default.
- W3206914405 title "Aspect-Driven User Preference and News Representation Learning for News Recommendation" @default.
- W3206914405 cites W1832693441 @default.
- W3206914405 cites W2054141820 @default.
- W3206914405 cites W2250539671 @default.
- W3206914405 cites W2285970137 @default.
- W3206914405 cites W2295739661 @default.
- W3206914405 cites W2612769033 @default.
- W3206914405 cites W2741252866 @default.
- W3206914405 cites W2742272831 @default.
- W3206914405 cites W2744316982 @default.
- W3206914405 cites W2788893025 @default.
- W3206914405 cites W2797467480 @default.
- W3206914405 cites W2806093883 @default.
- W3206914405 cites W2808613198 @default.
- W3206914405 cites W2897660518 @default.
- W3206914405 cites W2903803738 @default.
- W3206914405 cites W2906877346 @default.
- W3206914405 cites W2917650914 @default.
- W3206914405 cites W2940642489 @default.
- W3206914405 cites W2950416834 @default.
- W3206914405 cites W2950421571 @default.
- W3206914405 cites W2953222773 @default.
- W3206914405 cites W2963869731 @default.
- W3206914405 cites W2964536660 @default.
- W3206914405 cites W2964694324 @default.
- W3206914405 cites W2965952986 @default.
- W3206914405 cites W2970793364 @default.
- W3206914405 cites W2988777870 @default.
- W3206914405 cites W2997310152 @default.
- W3206914405 cites W3008055133 @default.
- W3206914405 cites W3014847672 @default.
- W3206914405 cites W3025058555 @default.
- W3206914405 cites W3026534984 @default.
- W3206914405 cites W3028791585 @default.
- W3206914405 cites W3034236656 @default.
- W3206914405 cites W3034503922 @default.
- W3206914405 cites W3086725055 @default.
- W3206914405 cites W3093729421 @default.
- W3206914405 cites W3120558633 @default.
- W3206914405 cites W3157741298 @default.
- W3206914405 cites W3182194020 @default.
- W3206914405 cites W3183887682 @default.
- W3206914405 cites W3184218698 @default.
- W3206914405 cites W4224313641 @default.
- W3206914405 cites W4289257875 @default.
- W3206914405 doi "https://doi.org/10.1109/tits.2022.3182568" @default.
- W3206914405 hasPublicationYear "2022" @default.
- W3206914405 type Work @default.
- W3206914405 sameAs 3206914405 @default.
- W3206914405 citedByCount "5" @default.
- W3206914405 countsByYear W32069144052022 @default.
- W3206914405 countsByYear W32069144052023 @default.
- W3206914405 crossrefType "journal-article" @default.
- W3206914405 hasAuthorship W3206914405A5016151794 @default.
- W3206914405 hasAuthorship W3206914405A5034219446 @default.
- W3206914405 hasAuthorship W3206914405A5043549588 @default.
- W3206914405 hasAuthorship W3206914405A5052441498 @default.
- W3206914405 hasAuthorship W3206914405A5070178549 @default.
- W3206914405 hasAuthorship W3206914405A5082317196 @default.
- W3206914405 hasBestOaLocation W32069144052 @default.
- W3206914405 hasConcept C100776233 @default.
- W3206914405 hasConcept C107457646 @default.
- W3206914405 hasConcept C111368507 @default.
- W3206914405 hasConcept C111919701 @default.
- W3206914405 hasConcept C118505674 @default.
- W3206914405 hasConcept C126322002 @default.
- W3206914405 hasConcept C12725497 @default.
- W3206914405 hasConcept C127313418 @default.
- W3206914405 hasConcept C136764020 @default.
- W3206914405 hasConcept C144024400 @default.
- W3206914405 hasConcept C154945302 @default.
- W3206914405 hasConcept C162324750 @default.
- W3206914405 hasConcept C175444787 @default.
- W3206914405 hasConcept C177291462 @default.
- W3206914405 hasConcept C17744445 @default.
- W3206914405 hasConcept C199539241 @default.
- W3206914405 hasConcept C23123220 @default.
- W3206914405 hasConcept C26517878 @default.
- W3206914405 hasConcept C2776359362 @default.
- W3206914405 hasConcept C2781249084 @default.
- W3206914405 hasConcept C38652104 @default.
- W3206914405 hasConcept C41008148 @default.
- W3206914405 hasConcept C46312422 @default.
- W3206914405 hasConcept C49774154 @default.
- W3206914405 hasConcept C557471498 @default.
- W3206914405 hasConcept C59404180 @default.
- W3206914405 hasConcept C71924100 @default.
- W3206914405 hasConcept C94625758 @default.