Potential for personalization
By Jaime Teevan, Susan T. Dumais, Eric Horvitz. 2010
174 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jaime Teevan
- Daniel J. Liebling
- Susan T. Dumais
- Min-Ling Zhang
- Meredith Ringel Morris
- Yiming Yang
- Siddharth Gopal
- Chaomei Chen
In Information Systems
- Jaime Teevan
- Susan T. Dumais
- Daniel J. Liebling
- Donna K. Harman
- Ryen W. White
- Meredith Ringel Morris
- Emre Kıcıman
- Yiming Yang
Citations in the corpus
- Counterfactual Estimation and Optimization of Click Metrics for Search Engines (2014, neutral): “For example, user behavior like clicks is used to infer personalized relevance for evaluation purposes [31], and to compare two ranking systems by interleaving [8].”
- To personalize or not to personalize: modeling queries with variation in user intent (2008, background): “[24] have reported individual variation in what different people personally consider relevant to the same queries.”
- Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study (2015, unknown): “For example, user behavior like clicks is used to infer personalized relevance for evaluation purposes [31], and to compare two ranking systems by interleaving [6].”