Characterizing and Evaluating Whole Session Interactive Information Retrieval
Investigators: Prof. Nick Belkin and Prof. Chirag Shah
Sponsored by the National Science Foundation (NSF) Award 1423239
|About the Project|
|This research addresses a newly important issue in contemporary life. As people become more accustomed to using the Web for finding information, they are increasingly using it for addressing ever more complex and personally important information problems. However, current Web search engines have been developed and specifically tuned to helping people find simple, mostly factual information, usually as a single response list to a single, simple query. But when they try to address the new types of problems, people need to engage in longer information seeking episodes than the one query-one response paradigm assumes. They may also need to engage in many activities other than just clicking on a search result, such as reading, evaluating, comparing and using information. Current Web search engines do not sufficiently support this model of information seeking and use. This research addresses this problem by studying why people engage in such complex information seeking (that is, the reasons that motivate them to do this), and what they try to accomplish during the course of an information seeking episode (their search intentions). The end-goal of this research is to design and evaluate new types of search engines for supporting people in accomplishing the goals that have led them to engage in information seeking. This means, in essence, being able to personalize system support to the individual, and the individual's goals and context. Specifically, this research will establish relationships between people's behaviors during an information seeking episode, the motivating goals that led them to engage in information seeking, and their specific intentions at any point in an information seeking episode. This will enable development of systems that will be able to predict how best to support the individual person in addressing their information problem. For example, the findings from this project could help build a system that automatically identifies that a searcher is shopping for a car, and help him/her compare cost-benefits of new vs. used cars, buying vs. leasing, and eventually making an informed decision. Research will be integrated with educational activities via developing modules to supplement courses in iSchools and library/information science programs, etc. This is important, since a broad range of students would learn about new methods of searching and related user studies and evaluation.|
|Progress and Planned Activities|
|Summer 2015||With newly appointed graduate assistant Matt Mitsui, we are working on designing a new user study to understand people's intentions for different search segments.|
|Fall 2015||Lab study to extract search intentions.|
Submitted a short paper to SIGIR 2016.
|Spring 2016||Continuation of the lab study to extract search intentions.|
Started discussions with GESIS in Cologne, Germany for possible partnership.
Got SIGIR 2016 short paper accepted.
|Summer 2016||Continuation of the lab study to extract search intentions.|
|Fall 2016||Continuation of the lab study to extract search intentions.|
|Spring 2017||Continuation of the lab study to extract search intentions.|
Got SIGIR 2017 short paper accepted.
|Summer 2017||Designing of a field study to extract search intentions.|
Got ASIST 2017 full paper accepted.
|Fall 2017||IRB application and pilots for the in situ study. A paper presented at ASIST 2017 conference.|
|Spring 2018||In situ study commenced. A paper presented at ACM CHIIR 2018 conference.|
|Summer 2018||In situ study continued.|
|Data collection tools|