Task Intelligence for Search and Recommendation

Chirag Shah is an Associate Professor in the Information School (iSchool) at the University of Washington (UW ) in Seattle. Before UW, he was on the faculty at Rutgers University. His research interests include studies of interactive information retrieval/seeking, trying to understand the task a person is doing and providing proactive recommendations. In addition, he works to make these smart systems also fair, equitable, and transparent under the umbrella of Responsible AI. Dr. Shah received his Ph.D. in Information Science from University of North Carolina (UNC) at Chapel Hill. He directs the InfoSeeking Lab where he investigates issues related to information seeking, human–computer interaction (HCI), and fairness in machine learning. Shah has authored/edited two books on Collaborative Information Seeking (CIS), and a book on Social Information Seeking (SIS). He was a guest editor for the IEEE Computer Special Issue on CIS published in March 2014. He has also written a textbook on Data Science. He has taught undergraduate and graduate courses in IR, HCI, and Data Science at the University of North Carolina (UNC) Chapel Hill, Rutgers University, and University of Washington. He has also taught several courses and tutorials on topics related to search, recommendation, and fairness in machine learning at different international places, including at SIGIR, WSDM, and RecSys conferences, Russian Summer School on Information Retrieval (RuSSIR), and Asian Summer School in Information Access (ASSIA). In 2019, Shah received the Microsoft BCS/BCS IRSG Karen Sparck Jones Award for contributions to information retrieval. He is the Founding Editor-in-Chief of ASIS&T Information Matters.Ryen W. White is a Partner Research Area Manager at Microsoft Research, where he leads several world-class teams of scientists and engineers comprising the Language and Intelligent Assistance research area. In recent roles, Ryen led the applied science organization for Microsoft Cortana andwas chief scientist for Microsoft Health. Ryen’s research has historically been focused on understanding search interaction and developing tools to help people search more effectively. He received his Ph.D. in Computer Science from University of Glasgow, United Kingdom. Ryen has published hundreds of conference papers and journal articles in web search and other areas. He was identified as the “Center of the SIGIR Universe” (most central author in the co-authorship graph) in the 40 years of the ACM SIGIR conference. Ryen has received many best-paper awards in conferences and journals, including three best papers at the ACM SIGIR conference. His book, Interactions with Search Systems, received the ASIS&T Best Information Science book award in 2017. Ryen’s doctoral research received the British Computer Society’s Distinguished Dissertation Award. In 2014, he received the Microsoft BCS/BCS IRSG Karen Spärck Jones Award for contributions to information retrieval. Ryen co-founded the ACM SIGIR Conference on Human-Information Interaction and Retrieval (CHIIR) and chaired its inaugural steering committee. He was program chair of SIGIR 2017 and The Web Conference 2019. Ryen was co-editor-in-chief of the Information Retrieval Journal (2018–2021), and is now the editor-in-chief of ACM Transactions on the Web.

• Preface.- Acknowledgments.- Introduction.- Task Frameworks, Expressions, and Representations.- Using Task Construct in IR.- Explicating Task.- Applying Task Information for Search and Recommendations.- Task-Based Evaluation.- Conclusions and Future Directions.- Bibliography.- Authors' Biographies .