In episode 15 of Recsperts, we delve into podcast recommendations with senior data scientist, Mirza Klimenta. Mirza discusses his work on the ARD Audiothek, a public broadcaster of audio-on-demand content, where he is part of pub. Public Value Technologies, a subsidiary of the two regional public broadcasters BR and SWR.

We explore the use and potency of simple algorithms and ways to mitigate popularity bias in data and recommendations. We also cover collaborative filtering and various approaches for content-based podcast recommendations, drawing on Mirza's expertise in multidimensional scaling for graph drawings. Additionally, Mirza sheds light on the responsibility of a public broadcaster in providing diversified content recommendations.

Towards the end of the episode, Mirza shares personal insights on his side project of becoming a novelist. Tune in for an informative and engaging conversation.

Enjoy this enriching episode of RECSPERTS - Recommender Systems Experts.

• (00:00 ) - Episode Overview


• (01:43 ) - Introduction Mirza Klimenta


• (08:06 ) - About ARD Audiothek


• (21:16 ) - Recommenders for the ARD Audiothek


• (30:03 ) - User Engagement and Feedback Signals


• (46:05 ) - Optimization beyond Accuracy


• (51:39 ) - Next RecSys Steps for the Audiothek


• (57:16 ) - Underserved User Groups


• (01:04:16 ) - Cold-Start Mitigation


• (01:05:06 ) - Diversity in Recommendations


• (01:07:50 ) - Further Challenges in RecSys


• (01:10:03 ) - Being a Novelist


• (01:16:07 ) - Closing Remarks

• Mirza Klimenta on LinkedIn
• ARD Audiothek
• pub. Public Value Technologies
• Implicit: Fast Collaborative Filtering for Implicit Datasets
• Fairness in Recommender Systems: How to Reduce the Popularity Bias

Papers:

• Steck (2019): Embarrasingly Shallow Auoencoders for Sparse Data
• Hu et al. (2008): Collaborative Filtering for Implicit Feedback Datasets
• Cer et al. (2018): Universal Sentence Encoder

General Links:

• Follow me on Twitter: https://twitter.com/MarcelKurovski
• Send me your comments, questions and suggestions to marcel@recsperts.com
• Podcast Website: https://www.recsperts.com/