rank all the (geo) things!

Rank all the (geo) things!@jsuchal@SynopsiTV

Blogs, newsletters

How do you learn things?

Courses, training

Conferences Work

Research papers?

WHY NOT?

WHY NOT?

“It’s not useful for the real-world.”

“I wouldn’t understand any of

that.”

About me

PhD dropout FIIT STU Bratislava

foaf.sk, otvorenezmluvy.sk, govdata.sk

sme.sk news recommender

developer @ SynopsiTV

My workflow

My workflow

MAGIC!M

AG

IC!

MA

GIC

!

Search vs. recommender engine

Search engine

input: queryoutput: list of results

Recommendation engine

input: movieoutput: list of similar movies

Academic Mode

Accurately interpreting clickthrough data as implicit feedback

Thorsten Joachims, Laura Granka, Bing Pan, Helene Hembrooke, and Geri Gay. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in Information retrieval, SIGIR ’05, pages 154–161, New York, NY, USA, 2005. ACM.

Significant on two-tailed tests at a 95% confidence level !!!

Learning to Rank for Spatiotemporal Search

Blake Shaw, Jon Shea, Siddhartha Sinha, and Andrew Hogue. 2013. Learning to rank for spatiotemporal search. In Proceedings of the sixth ACM international conference on Web search and data mining (WSDM '13). ACM, New York, NY, USA, 717-726.

Learning to Rank for Spatiotemporal Search

Learning to Rank for Spatiotemporal Search

Learning to Rank for Spatiotemporal Search

Learning to Rank for Spatiotemporal Search

Learning to Rank for Spatiotemporal Search

Accurately interpreting clickthrough data as implicit feedback

Thorsten Joachims, Laura Granka, Bing Pan, Helene Hembrooke, and Geri Gay. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in Information retrieval, SIGIR ’05, pages 154–161, New York, NY, USA, 2005. ACM.

Accurately interpreting clickthrough data as implicit feedback

Evaluation Metrics

● Mean Average Precision @ N○ probability of target result being in top N items

● Mean Reciprocal Rank○ 1 / rank of target result

● Normalized Discounted Cumulative Gain● Expected Reciprocal Rank

Optimizing search engines using clickthrough data

Thorsten Joachims. Optimizing search engines using clickthrough data. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’02, pages 133–142, New York, NY, USA, 2002. ACM.

Optimizing search engines using clickthrough data

Query chains: learning to rank from implicit feedback

Filip Radlinski and Thorsten Joachims. Query chains: learning to rank from implicit feedback. In KDD ’05: Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, pages 239–248, New York, NY, USA, 2005. ACM.

On Caption Bias in Interleaving Experiments

Katja Hofmann, Fritz Behr, and Filip Radlinski: On Caption Bias in Interleaving Experiments In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM) 2012

On Caption Bias in Interleaving Experiments

Fighting Search Engine Amnesia: Reranking Repeated Results

Milad Shokouhi, Ryen W. White, Paul Bennett, and Filip Radlinski. Fighting search engine amnesia: reranking repeated results. In Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’13, pages 273–282, New York, NY, USA, 2013. ACM.

In this paper, we observed that the same results are often shown to users multiple times during search sessions. We showed that there are a number of effects at play, which can be leveraged to improve information retrieval performance. In particular, previously skipped results are much less likely to be clicked, and previously clicked results may or may not be re-clicked depending on other factors of the session.

Challenges

Diversification

Group recommendations

Context-aware recommendations

Time of day

DeviceMood

Season

Location

Seriousrecommenders and search?Get in touch!

@synopsitv @jsuchal