Video clerks power new movie recommendation engine

SAN FRANCISCO -- Even as technology threatens the survival of video rental stores, serial entrepreneur Stuart Skorman thinks there's still a place for the movie-matchmaking advice of veteran video store clerks.

To prove his point, Skorman hired more than 20 former video store clerks to pour their collective wisdom into a new Internet search engine, called ClerkDogs, that's being unleashed Tuesday.

Skorman is betting this combination of human intelligence and data crunching will emerge as a more engaging and intuitive alternative to the highly automated movie-recommendation system that has helped fuel the success of online DVD rental leader Netflix Inc.

Netflix spits out recommendations for its 8.7 million subscribers by drawing upon a database of 2 billion ratings that its customers have entered during the past decade. By knowing whether you liked one movie, Netflix suggests others you might enjoy by mining the past preferences and renting patterns of subscribers who watched the same movies.

ClerkDogs also dives into a vast data pool in order to suggest movies, but augments its findings in key ways.

After it asks visitors to enter the name of a movie they liked, ClerkDogs' engine generates a list of suggestions based on a computer-driven analysis of video clerks' insights and written reviews. And for a more personal touch, it lets its users tweak recommendations based on their moods at the time of a request. ClerkDogs users can slide a scale indicating whether they are looking for movies with a little more romance, suspense, humor and other elements contained in the movie they initially selected.

The revisions help ClerkDogs get even closer to a visitor's interests, pulling from the information provided by the video store clerks.

Skorman, a former video store owner, likens the system to having a conversation with a movie buff — something that's not possible on Netflix's recommendation engine because it relies on a strict one- to five-star rating system and doesn't adjust for a renter's changing emotions.