Category Archives: Recommendation Engine

Customer Service and Recommendation System

You may be wondering about the relationship, I alluded to in the title. A personalization and recommendation system like sifarish bootstraps from user and item engagement data. This kind of data is gleaned from various signals e.g. an user’s engagement with … Continue reading

Posted in Big Data, Customer Service, eCommerce, Hadoop and Map Reduce, Recommendation Engine | Tagged , | 1 Comment

Diversity in Personalization with Attribute Diffusion

One of the nagging problems in  personalized recommendation systems is crowding of items with same attribute values in the recommendation list. For example, if you happen to like certain artiste, the songs by the same artiste will tend to flood recommended … Continue reading

Posted in Big Data, Data Science, Hadoop and Map Reduce, Personalization, Recommendation Engine | Tagged , | Leave a comment

Positive Feedback Driven Recommendation Rank Reordering

The basic recommendation output consisting of the tuple (user, item, predicted rating), is easy to obtain from any Collaborative Filtering (CF) based Recommendation and Personalization engine, including sifarish. It’s been reported that there is a bigger return for the quality of … Continue reading

Posted in Big Data, Collaborative Filtering, Hadoop and Map Reduce, Personalization, Recommendation Engine | Tagged , , | 1 Comment

Location and Time Based Service

When I implemented feature similarity based matching engine in my open source Personalization and Recommendation Engine sifarish, it was for addressing the cold start problem. It allowed me to do content or feature based recommendation for users with limited engagement. … Continue reading

Posted in Big Data, Hadoop and Map Reduce, Mobile, Real Time Processing, Recommendation Engine, Search, Spark, Storm | Tagged , , , | Leave a comment

Novelty in Personalization

We all have the unfortunate  experience of being pigeon holed by Personalization and Recommendation engines. When recommendation are based on our past behavior and there is very little  opportunity to explore. But our past actions are not always good predictors for … Continue reading

Posted in Big Data, Data Mining, Data Science, Hadoop and Map Reduce, Personalization, Recommendation Engine | Tagged , | 1 Comment

Popularity Shaken

We will be addressing two important issues faced by recommendation systems. First, how do you solve the cold start problem i.e., provide recommendations for new users with very limited behavior data available. Second, even if we have a recommendation list for … Continue reading

Posted in Big Data, Hadoop and Map Reduce, Recommendation Engine, Storm | Tagged , , | 3 Comments

Making Recommendations in Real Time

Making recommendations based on an user’s current behavior in a small time window is a powerful feature that has been added to sifarish recently. In this post I will go over the details of this feature. The real time feature … Continue reading

Posted in Big Data, Collaborative Filtering, Data Mining, Data Science, Hadoop and Map Reduce, Real Time Processing, Recommendation Engine, Redis, Storm | Tagged , | 2 Comments