Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Mifumo ya Mapendekezo ya AI

Kagua mbinu za mapendekezo, uchujaji shirikishi na maudhui, uainishaji wa matrix, mifumo mseto na hatari za ushiriki.

Njia za mwongozo zinazohusianaMifumo ya Mapendekezo ya AI
Swali 1 ya 8

Je, 'kuchuja kwa kushirikiana' kunategemea nini ili kutoa mapendekezo?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. Je, 'kuchuja kwa kushirikiana' kunategemea nini ili kutoa mapendekezo?
    • Sampuli kwa watumiaji wengi walio na ladha sawa
    • Maelezo ya maandishi ya kila kipengee pekee
    • Bei ya bidhaa
    • Orodha ya 10 bora ya wahariri
  2. Uchujaji unaotegemea maudhui unapendekeza vipengee hasa kwa:
    • Sampuli za nasibu za katalogi
    • Kulinganisha vipengele vya kipengee na mapendeleo yako ya awali
    • Kuhesabu jumla ya mauzo ya kimataifa
    • Kuomba watumiaji wengine kupiga kura
  3. What did the Netflix Prize seek to improve by 10% over the Cinematch baseline?
    • Click-through rate for every recommended film
    • The number of films watched per user
    • Root mean squared error (RMSE) on the competition’s held-out ratings
    • A user’s average watch time on the service
  4. Katika uainishaji wa matrix, watumiaji na vitu vinawakilishwa kama:
    • Bendera moja ya ndiyo/hapana
    • Ukaguzi wa maandishi wazi
    • Tarehe za kalenda
    • Vekta za 'mambo fiche' yaliyofichwa
  5. What mechanism did the Deep Interest Network paper propose for modeling a user’s different interests across candidate ads?
    • A local activation unit that forms a candidate-specific interest representation
    • A fixed user vector that is identical for every candidate
    • A rule that selects only the most popular ad
    • A graph algorithm that proves every ad is relevant
  6. Mshauri wa 'mseto' ni mmoja ambaye:
    • Inafanya kazi wikendi pekee
    • Inachanganya mbinu za ushirikiano na maudhui
    • Haitumii data hata kidogo
    • Inapendekeza vipengee vipya pekee
  7. What is one limitation of collaborative filtering for a new item with no interactions?
    • It cannot use ratings
    • It requires item descriptions only
    • It may lack the interaction data needed to recommend the item
    • It always recommends every new item
  8. What should a recommender evaluation measure besides click-through rate?
    • Only the model’s parameter count
    • Only training loss
    • Only the number of recommendations
    • User outcomes and harms such as diversity, exposure, or unwanted engagement