Netflix prize i KDD’09 best paper 07/11/2009Posted by Mikołaj Morzy in Uncategorized.
Jak zapewne niektórzy już wiedzą, Belkor Pragmatic Chaos złamał barierę 10% i wygrał 1 000 000$ w konkursie Netflix Prize. Z naszego punktu widzenia najciekawsze jest to, że jeden z członków zespołu, Yehuda Koren z Yahoo! Research zdobył też nagrodę KDD’09 Best Paper za artykuł „Collaborative Filtering with Temporal Dynamics„. Ze streszczenia:
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are evolving, leading them to ever redefine their taste. Thus, modeling temporal dynamics should be a key when designing recommender systems or general customer preference models. However, this raises unique challenges. Within the eco-system intersecting multiple products and customers, many different characteristics are shifting simultaneously, while many of them influence each other and often those shifts are delicate and associated with a few data instances. This distinguishes the problem from concept drift explorations, where mostly a single concept is tracked. Classical time-window or instance decay approaches cannot work, as they lose too much signal when discarding data instances. A more sensitive approach is required, which can make better distinctions between transient effects and long term patterns. The paradigm we offer is creating a model tracking the time changing behavior throughout the life span of the data. This allows us to exploit the relevant components of all data instances, while discarding only what is modeled as being irrelevant. Accordingly, we revamp two leading collaborative filtering recommendation approaches. Evaluation is made on a large movie rating dataset by Netflix. Results are encouraging and better than those previously reported on this dataset.
Ten artykuł może stanowić istotny początek badań nad danymi pochodzącymi od użytkowników wielu różnych sieci społecznych.