BS (Electrical Engineering), Washington University
MS (Language Technologies and Information Systems Management), Carnegie Mellon University
PhD (Language Technologies), Carnegie Mellon University
Dr. Jaime Arguello, Associate Professor at the UNC School of Information and Library Science (SILS), teaches courses and conducts research in the areas of information retrieval, data mining, and machine learning. His main area of research is aggregated search, where the goal is to develop search systems that integrate results from multiple independent sources. Dr. Arguello develops algorithms and evaluation methodologies for deciding which sources to select and how to display them. His most recent research studies how users interact with aggregated search displays and how differences in display affect users’ expectations and behaviors. He received a 2015 NSF CAREER Award for a five-year project titled “Making Aggregated Search Results More Effective and Useful.”
Dr. Arguello’s second main area of research focuses on search assistance, where the goal is to develop interactions to help search engine users working on complex tasks. This research aims to understand when and how people employ search assistance. The ultimate goal is to develop systems that automatically provide assistance at the right times and in the appropriate ways. In 2017, Dr. Arguello and SILS Associate Professor Robert Capra received an NSF grant worth nearly $500,000 to develop and evaluate systems that will automatically display relevant search trails as a form of search assistance to users.
Dr. Arguello holds a PhD in Computer Science from Carnegie Mellon University, and publishes regularly at information retrieval venues such as SIGIR, ECIR, CIKM, and IIIX.
Courses Regularly Taught:
INLS 509: Information Retrieval
INLS 613: Text Data Mining
INLS 890: Experimental Information Retrieval
Awards and Recognition:
Best Paper Award, ECIR 2017
Distinguished Teaching Award for Post-Baccalaureate Instruction, UNC-Chapel Hill 2017
Best Meta-Reviewer Award, ECIR 2015
Best Paper Award, IIIX 2014
Deborah Barreau Award for Teaching Excellence, UNC SILS 2014
UNC-IBM Junior Faculty Development Award (Funds: $7,500), UNC 2013
Best Poster Award, IIIX 20012
Best Student Paper Award, ECIR 2011
Best Paper Award, SIGIR 2009
Yahoo! Key Scientific Challenges Award, 2009
Best Paper Award Nomination, ICWSM 2008
Selected Publications, Papers, Presentations:
J. Arguello. Aggregated Search. In Foundations and Trends in Information Retrieval. 10(5). Now Publishers. 2017.
J. Arguello and R. Capra. The Effects of Aggregated Search Coherence on Search Behavior. In ACM Transactions of Information Systems. 35(1). ACM. 2016.
S. Avula, G. Chadwick, J. Arguello, and R. Capra. SearchBots: User Engagement with ChatBots during Collaborative Search. To Appear in Proceedings of the 3rd ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR'18), 2018.
H. Kim and J. Arguello Evaluation of Features to Predict the Usefulness of Online Reviews. In Proceedings of the 80th Annual Meeting of the Association of Information Science and Technology (ASIST'17), 2017.
J. Arguello, S. Avula, and F. Diaz. Using Query Performance Predictors to Reduce Spoken Queries. In Proceedings of the 39th European Conference on Information Retrieval. (ECIR'17), 2017.
R. Capra, J. Arguello, and Y. Zhang. The Effects of Search Task Determinability on Search Behavior. In Proceedings of the 39th European Conference on Information Retrieval. (ECIR'17), 2017. (Best Paper Award)
R. Capra, J. Arguello, A. Crescenzi, and E. Vardell. Differences in the Use of Search Assistance for Tasks of Varying Complexity. In SIGIR 2015: Proceedings of the 38th International ACM Conference in Research and Development in Information Retrieval. Santiago. 2015 [acceptance rate: 20%]
J. Arguello and Kyle Shaffer. Predicting Speech Acts in MOOC Forum Posts. In ICWSM2015:Proceedings of the 9th International AAAI Conference in Web and Social Media. Oxford. 2015 [acceptance rate: 19%]
J. Arguello. Improving Aggregated Search Coherence. In ECIR 2015: Proceedings of the 37th European Conference in Information Retrieval. Vienna. 2015
J. Arguello and R. Capra. The Effects of Vertical Rank and Border on Aggregated Search Coherence and Search Behavior. In CIKM 2014: Proceedings of the 23rd ACM International Conference on Information and Knowledge Management. Shanghai. 2014 [acceptance rate: 20%]
K. Brennan, D. Kelly, and J. Arguello. The Effect of Cognitive Abilities on Information search for Tasks of Varying Levels of Complexity. In IIIX ’14: Proceedings of the Information Interaction in Context Conference. Regensberg. 2014. [acceptance rate: 46%] (Best Paper Award).
J. Arguello. Predicting Search Task Difficulty. In ECIR ’14: Proceedings of 36th European Conference in Information Retrieval. Amsterdam. 2014. [acceptance rate: 23%]
J. Arguello, R. Capra, and W. Wu. Factors Affecting Aggregated Search Coherence and Search Behavior. In CIKM ’13: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. San Francisco. 2013. [acceptance rate: 17%]
R. Capra, J. Arguello, and F. Scholer. Augmenting Web Result Surrogates with Images. In CIKM ’13: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. San Francisco. 2013. [acceptance rate: 17%]
A. Crescenzi, R. Capra, and J. Arguello. Time Pressure, User Satisfaction, and Task Difficulty. In ASISandT ’13: Proceeding of 76th Annual Meeting of the American Society of Information Science and Technology. Montreal. 2013. (Poster Paper)
J. Arguello and R. Capra. The Effect of Aggregated Search Coherence on Search Behavior. In CIKM ’12: Proceedings of the 21st ACM International Conference on Information and Knowledge Management. Maui. 2012. [acceptance rate: 13.4%]
J. Arguello, D. Kelly, W. Wu, and A. Edwards. Task Complexity, Vertical Salience, and User Interaction in Aggregated Search. In SIGIR ’12: Proceedings of the 21st ACM Conference in 35th International Conference in Research and Development in Information Retrieval. Portland. 2012. [acceptance rate: 20%]
W. Wu, D. Kelly, A. Edwards, J. Arguello. Grannies, Tanning Beds, Tattoos, and NASCAR: Evaluation of Search Tasks with Varying Levels of Cognitive Complexity. In IIIX ’12: 6th International Symposium of Information Interaction in Context. Nijmegen. 2012 (Best Poster Award).