1D0-61A · Question #41
Evonka is listening to music from an online music provider (such as Pandora or Jango). She builds a list of music preferences, including favorite songs. The music service then suggests additional…
The correct answer is B. Crowdsourcing. Crowdsourcing is correct because collaborative filtering works by pooling the preferences and behaviors of a large group of users - the "crowd" - to make personalized recommendations. Evonka's taste data is combined with data from thousands of other listeners, and the system…
Question
Evonka is listening to music from an online music provider (such as Pandora or Jango). She builds a list of music preferences, including favorite songs. The music service then suggests additional songs she might enjoy. The music provider is an example of a cloud- computing application that uses a technology for collaborative filtering, which helps define the list of songs available to listeners. Which term describes this technology?
Options
- ABit-torrent
- BCrowdsourcing
- CGrid computing
- DSoftware as a Service
How the community answered
(26 responses)- A4% (1)
- B88% (23)
- C8% (2)
Explanation
Crowdsourcing is correct because collaborative filtering works by pooling the preferences and behaviors of a large group of users - the "crowd" - to make personalized recommendations. Evonka's taste data is combined with data from thousands of other listeners, and the system surfaces songs that similar users enjoyed. BitTorrent (A) is a peer-to-peer file-sharing protocol, not a recommendation technology. Grid computing (C) refers to distributing computational workloads across many machines to solve large problems - it's about processing power, not preference aggregation. SaaS (D) describes the delivery model of software over the internet, which may apply to the music service generally, but it does not describe the filtering mechanism specifically.
Memory tip: Break down the word - crowd + sourcing = sourcing data from the crowd. Any time a system learns from many users' collective input to benefit individual users, think crowdsourcing.
Topics
Community Discussion
6
Hiroshi T.Apr 7, 2026Crowdsourcing is correct here because collaborative filtering builds recommendations by aggregating data from the collective behavior of many users, which is exactly what crowdsourcing means in this context. The music service pools listener preferences across its entire user base to surface suggestions for any individual listener, and that crowd-driven data collection is the defining characteristic that separates this from the other options.
Prof. SaraApr 7, 2026Hiroshi, you have the mechanism right but the label backwards, because crowdsourcing requires users to knowingly and voluntarily contribute data, whereas collaborative filtering harvests passive behavioral signals (plays, skips, saves) without the user acting as a deliberate contributor, which is exactly the distinction exam writers test when they pair those two distractors together.
Prof. SaraMar 31, 2026The trap here is D, and the exam writers know it, because the scenario itself calls Pandora a cloud-computing application, so your eye wants to bubble SaaS and move on. SaaS describes how the software is delivered, not the mechanism that surfaces song suggestions, so eliminate it and refocus on what collaborative filtering actually does: it pools the listening behavior and ratings of thousands of users and feeds that crowd-contributed data back to every individual listener. That aggregation of input from a large, distributed group of people is the textbook definition of crowdsourcing, which maps directly to B. Grid computing (C) is about harnessing distributed processing power for computation-heavy tasks, not about harvesting user preferences, and BitTorrent (A) is a peer-to-peer file transfer protocol with no relevance to recommendation logic. Lock in B, crowdsourcing, and remember the mnemonic CROWD PICKS YOUR PLAYLIST: when a service learns from the collective to serve the individual, that is crowdsourcing at work.
Luis F.Apr 22, 2026Crowdsourcing is the right call here because the music service is pooling preference data from tons of users to make those recommendations, not just Evonka's own history. Quick question though, do you think there's a meaningful difference between crowdsourcing and what Pandora specifically calls its Music Genome Project, where human analysts tag songs manually instead of relying purely on listener behavior?
Quincy P.Apr 14, 2026Crowdsourcing fits, but what user behavior actually feeds the collaborative filter here?
Prof. SaraApr 15, 2026The filter needs explicit signals like upvotes and saves plus implicit ones like dwell time and answer-select patterns, and without weighting those differently you get popularity bias masquerading as relevance.