AI gudaha Makhaayada iyo Kediska Talooyinka Menu

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Maxay shaandhaynta wada shaqayntu ugu horrayn ku tiirsan tahay si ay talooyin u soo jeediyaan?
   • Qaababka isticmaalayaasha leh dhadhanka la midka ah
   • Nuxurka nafaqeynta ee saxan kasta
   • Naqshadaynta gudaha makhaayadda
   • Heerkulka jikada ee wakhtiga dhabta ah
2. Waa maxay sababta dib-u-eegista macdan qodista moodooyinka NLP ay faa'iido u leeyihiin barnaamijyada cuntada?
   • Si degdeg ah ayay cuntada u kariyaan
   • Waxay soo koobaan dareenka waxayna soosaaraan calaamadaha heerka saxanka qoraalka
   • Waxay beddelaan baahida menu-yada
   • Waxay dejiyeen qiimaha makhaayadaha
3. In a proposed two-stage food recommender, what would candidate retrieval do before ranking?
   • Confirm the restaurant reservation
   • Process the customer’s payment
   • Select a candidate subset for a later scoring stage
   • Guarantee the final recommendation matches every preference
4. Maxaa gundhigyada loo isticmaalaa talinta menu?
   • Kaydinta furaha macaamiisha
   • Sirta cinwaannada gaarsiinta
   • Cabbiraadda heerkulka foornada
   • Matalaya suxuunta sida vector-ka si alaabada la midka ah ay u wada fadhiyaan meel dhow
5. Why can a new diner with no recorded preferences pose a cold-start problem?
   • Interaction-based personalization has little user-history evidence to work from
   • The restaurant must change its menu
   • The model cannot represent food text
   • Opening hours become unavailable to everyone
6. What can the MenuAI research system do with a menu image and a nutritional search key?
   • Book a table without user confirmation
   • Rank menu dishes according to a query such as calories or protein
   • Diagnose a food allergy from a photograph
   • Guarantee a dish is available today
7. Why include restaurant availability or opening hours in recommendations?
   • It improves a model’s parameter count
   • It guarantees the restaurant is highest rated
   • A highly relevant option is not useful if it is unavailable at the requested time
   • It replaces user preferences
8. What is one limitation of review-mining sentiment for food recommendations?
   • Sentiment scores are always objective
   • Reviews contain exact nutrition facts
   • Review mining removes popularity bias
   • A review’s language may be sparse, subjective, or unrepresentative of the current menu