Online Recommendation Sites Pick the Perfect Film for You
Geebee Micro — March 21, 2009 — Pop Culture
References: news.cnet
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 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, Clerkdogs, Criticker, IMDb, Flixster, Movielens, Rotten Tomatoes, and Netflix.
But his favorite is Jinni, 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.
Some of the movie recommendation sites add other tools you can use beyond recommendations alone. For example, Taste Kid 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, Clerkdogs, Criticker, IMDb, Flixster, Movielens, Rotten Tomatoes, and Netflix.
But his favorite is Jinni, 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 Themes
1. Mood-based Movie Recommendations - Opportunity for movie recommendation engines to further personalize suggestions based on user's mood.
2. Cross-genre Recommendations - Potential for recommendation engines to suggest movies that cut across multiple genres, expanding users' movie-watching experiences.
3. Semantic Search Tools - Disruptive innovation opportunity for search tools to incorporate semantic search capabilities to provide more accurate and targeted results.
Industry Implications
1. Entertainment Industry - Opportunity for movie recommendation engines to collaborate with streaming platforms and production companies to enhance personalized viewing experiences.
2. Technology Industry - Potential for tech companies to develop advanced algorithms and machine learning models to improve movie recommendation engines.
3. Digital Media Industry - Opportunity for digital media platforms to integrate movie recommendation engines into their platforms to enhance user engagement and retention.
1.6
Score
Popularity
Activity
Freshness
