# Mood-Based Movie Suggestions Online Recommendation Sites Pick the Perfect Film for You By Geebee Micro | Published 2009-03-21 | Pop Culture Source: Trend Hunter, https://www.trendhunter.com/trends/jinni-movie-recommendations-engines References: [news.cnet](http://news.cnet.com/8301-17939_109-10200031-2.html?part=rss&subj=news&tag=2547-1_3-0-20) Don Reisinger writing for CNET recently published a good article on the top 10 movie recommendation engines on the Internet, many of which boast some pretty unique features. Some of the movie recommendation sites add other tools you can use beyond recommendations alone. For example, [Taste Kid](http://www.tastekid.com/) will take into account the movie inputs you give, and then offer recommendations related to books, music and other things it deems connected to your query. Other sites he uses and recommends are [Nanocrowd](http://www.nanocrowd.com/), [Clerkdogs](http://www.clerkdogs.com/), [Criticker](http://www.criticker.com/), [IMDb](http://www.imdb.com/), [Flixster](http://www.flixster.com/), [Movielens](http://www.movielens.umn.edu/), [Rotten Tomatoes](http://movielens.umn.edu/), and [Netflix](http://www.netflix.com/). But his favorite is [Jinni](http://www.jinni.com/signin.html), which includes an extraordinary semantic search tool where you can even input scenes you remember in a movie and it’ll return results on films that match what you’re looking for. You can even search based on the mood you’re in or what type of plot you’re looking for, and accurate, targeted responses come back for you. ## Trend Insights (Trend Hunter) - Score: 1.6/10 - Popularity: 28% | Activity: 12% | Freshness: 8% - Audience gender: 70% men, 30% women - Primary generations: Millennial, Gen X - Top markets: North America, Europe ## Categories [Trend Hunter](https://www.trendhunter.com/trends) > [Pop Culture](https://www.trendhunter.com/popculture) > [Media](https://www.trendhunter.com/media) ## Key Themes ### What Makes This Trend Stand Out - **Mood-based Movie Recommendations:** Opportunity for movie recommendation engines to further personalize suggestions based on user's mood. - **Cross-genre Recommendations:** Potential for recommendation engines to suggest movies that cut across multiple genres, expanding users' movie-watching experiences. - **Semantic Search Tools:** Disruptive innovation opportunity for search tools to incorporate semantic search capabilities to provide more accurate and targeted results. ### Sectors Adopting This - **Entertainment Industry:** Opportunity for movie recommendation engines to collaborate with streaming platforms and production companies to enhance personalized viewing experiences. - **Technology Industry:** Potential for tech companies to develop advanced algorithms and machine learning models to improve movie recommendation engines. - **Digital Media Industry:** Opportunity for digital media platforms to integrate movie recommendation engines into their platforms to enhance user engagement and retention. ## Related on Trend Hunter - [Mood-Based Movie Finders](https://www.trendhunter.com/trends/movie-engine.md) - [Movie Recommendation Platforms](https://www.trendhunter.com/trends/film-finder.md) - [Emotive Cinematic Experiences](https://www.trendhunter.com/trends/movies-of-mood.md) - [Mood-Based Movie Ideas](https://www.trendhunter.com/trends/feelflix.md) - [AI Movie Recommendations](https://www.trendhunter.com/trends/movie-deep-search.md) - [Movie Title Search Tools](https://www.trendhunter.com/trends/titlefindr.md) - [AI Film Recommenders](https://www.trendhunter.com/trends/whatshouldiwatchai.md) - [Personalized Movie Recommendations](https://www.trendhunter.com/trends/movie-night-curator.md) - [Mood-Based Movie Recommendations](https://www.trendhunter.com/trends/moodies.md)