1. Detecting Search Sessions Using Document Metadata and Implicit Feedback Tomáš Kramár

2. Why search sessions?

4. Which Jaguar?

7. Short contexts Search sessions Encompass single search intent User’s current interests, goals, preferences best cars honda jaguarjava IO sockets

8. Approaches Temporal Considers periods of inactivity Lexical distance Compares queries Content- based Compares features extracted from documents

9. Approaches Temporal Considers periods of inactivity WTF? Lexical distance Compares queries “Information retrieval”, “IR” Content- based Compares features extracted from documents Not everything is equally interesting

10. Document metadata and implicit feedback Match keywords of documents Consider only documents with value of implicit feedback above the threshold Enhance metadata with ConceptNet relations

11. Results ApproachF-score Lexical0.662 Temporal (30 min)0.641 Temporal (5min)0.510 Metadata0.432 Enhanced metadata0.421 Lexical + metadata0.694 Lexical + enhanced metadata0.689

12. ApproachF-score Lexical0.662 Temporal (30 min)0.641 Temporal (5min)0.510 Metadata0.432 Enhanced metadata 0.421 Lexical + metadata0.694 Lexical + enhanced metadata 0.689 Observations Low performance of raw metadata Low quality metadata Decreased performance of enhanced metadata Enhancing common words with common words Best performance of lexical + metadata usb phonograph; l3866usb vincov les; podhajska; velky meder the ills; youcoco

13. Future work

14. Summary Detecting search sessions by analyzing content of visited documents Considering implicit feedback Best: lexical + metadata