Mentor Pattern Identification from Product Usage Logs

  • Ankur Garg
  • Aman Kharb
  • Yash H. Malviya
  • J. P. Sagar
  • Atanu R. Sinha
  • Iftikhar Ahamath Burhanuddin
  • Sunav ChoudharyEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11441)


A typical software tool for solving complex problems tends to expose a rich set of features to its users. This creates challenges such as new users facing a steep onboarding experience and current users tending to use only a small fraction of the software’s features. This paper describes and solves an unsupervised mentor pattern identification problem from product usage logs for softening both challenges. The problem is formulated as identifying a set of users (mentors) that satisfies three mentor qualification metrics: (a) the mentor set is small, (b) every user is close to some mentor as per usage pattern, and (c) every feature has been used by some mentor. The proposed solution models the task as a non-convex variant of an Open image in new window regularized logistic regression problem and develops an alternating minimization style algorithm to solve it. Numerical experiments validate the necessity and effectiveness of mentor identification towards improving the performance of a k-NN based product feature recommendation system for a real-world dataset. Further, t-SNE visuals demonstrate that the proposed algorithm achieves a trade-off that is both quantitatively and qualitatively distinct from alternative approaches to mentor identification such as Maximum Marginal Relevance and K-means.


Mentor identification Unsupervised learning Sparsity-coverage trade-off L1-regularized logistic regression 

Supplementary material

482301_1_En_28_MOESM1_ESM.pdf (198 kb)
Supplementary material 1 (pdf 197 KB)


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ankur Garg
    • 1
  • Aman Kharb
    • 2
  • Yash H. Malviya
    • 3
  • J. P. Sagar
    • 4
  • Atanu R. Sinha
    • 5
  • Iftikhar Ahamath Burhanuddin
    • 5
  • Sunav Choudhary
    • 5
    Email author
  1. 1.The University of Texas at AustinAustinUSA
  2. 2.Indian Institute of Technology KharagpurKharagpurIndia
  3. 3.Apple Inc.CupertinoUSA
  4. 4.Indian Institute of Technology MadrasChennaiIndia
  5. 5.Adobe ResearchBangaloreIndia

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