Contextual Ranking of Keywords Using Click Data ICDE`09 Utku Irmak Vadim von Brzeski Vadim von Brzeski Reiner Kraft

Outline Introduction Contextual Shortcuts Methodology Feature Space Evaluation and Results Framework Conclusion

Introduction Application ◦ Contextual advertising ◦ Text summarization ◦ User-centric entity detection system Approach

Contextual Shortcuts Entity Detection ◦ Pattern based ◦ Named ◦ Concept Generating a Concept Vector ◦ Term vector ◦ Unit vector

Contextual Shortcuts 1)in term,not in unit 2)in unit, not in term 3)in both

Methodology (a) Determining whether the entity is relevant to the given context (b) Determining whether the entity is interesting outside of the context

Feature Space Interestingness of a Concept ◦ Search Engine Query Logs ◦ Search Engine Result Pages ◦ Text Based Features ◦ Taxonomy Based Features ◦ Other Relevance of a Concept in a Context ◦ Search engine snippets ◦ Related query suggestions

Evaluation and Results Cross Validation Approach [A,B,C,D] ◦ R1=[A,B,D,C] R2=[B,A,C,D] [(A, 0.15), (B, 0.05), (C, 0.02), (D,0.01)]

Evaluation and Results

Editorial Evaluation

Framework

Conclusion Utilize User-click feedback, interestingness and relevance to ranking the key concept that to improve overall performance.