[MAHOUT-329] Implement some recommendation ideas used by the Netflix top teams to boost the recommenders package

• Type: New Feature
• Status: Closed
• Priority: Major
• Resolution: Later
• Labels: gsoc mentor
• Assignee: Robin Anil
• Reporter: Robin Anil
• Created: 12/Mar/10 06:41
• Updated: 31/Jan/24 22:11
• Resolved: 27/Apr/10 08:49

Description

A student with a good proposal

• should be free to work for Mahout in the summer and should be thrilled to work in this area
• should be able to program in Java and be comfortable with datastructures and algorithms
• must be clear about the algorithm or heuristic, how it works, its strengths, its weaknesses and possible tweaks.
• must have a plan on making it a map/reduce implementation
• should be able to show the improvement on the netflix data as compared to the baseline recommender package by the end of summer of code
• must have clear deadlines and pace it evenly across the span of 3 months.
• may have a background in these area. Past work, thesis etc counts, so show it in the proposal clearly

If you can do something extra it counts, but make sure the plan is reasonable within the specified time frame.

Issue Links

• relates to: MAHOUT-371 Proposal to implement Distributed SVD++ Recommender using Hadoop
• relates to: MAHOUT-375 [GSOC] Restricted Boltzmann Machines in Apache Mahout