First, we must congratulate InfoSeeker, Ruoyuan Gao for having her\npaper accepted at ICTIR 2019!<\/p>\n\n\n\n
Next, we are excited to share the news that our InfoSeekers, Shawon\nSarkar, Matthew Mitsui, Jiqun Liu and Chirag Shah, have published a new article!\nThe title of the article is: Implicit information need as explicit problems, help,\nand behavioral signals.<\/p>\n\n\n\n
ABSTRACT<\/strong><\/p>\n\n\n\n Information need is one of the most fundamental\naspects of information seeking, which traditionally conceptualizes as the\ninitiation phase of an individual\u2019s information seeking behavior. However, the\nvery elusive and inexpressible nature of information need makes it hard to\nelicit from the information seeker or to extract through an automated process.\nOne approach to understanding how a person realizes and expresses information\nneed is to observe their seeking behaviors, to engage processes with\ninformation retrieval systems, and to focus on situated performative actions.\nUsing Dervin\u2019s Sense-Making theory and conceptualization of information need\nbased on existing studies, the work reported here tries to understand and\nexplore the concept of information need from a fresh methodological perspective\nby examining users\u2019 perceived barriers and desired helps in different stages of\ninformation search episodes through the analyses of various implicit and\nexplicit user search behaviors. In a controlled lab study, each participant\nperformed three simulated online information search tasks. Participants\u2019\nimplicit behaviors were collected through search logs, and explicit feedback\nwas elicited through pre-task and post-task questionnaires. A total of 208 query\nsegments were logged, along with users\u2019 annotations on perceived problems and\nhelp. Data collected from the study was analyzed by applying both quantitative\nand qualitative methods. The findings identified several behaviors \u2013 such as\nthe number of bookmarks, query length, number of the unique queries, time spent\non search results observed in the previous segment, the current segment, and\nthroughout the session \u2013 strongly associated with participants\u2019 perceived\nbarriers and help needed. The findings also showed that it is possible to build\naccurate predictive models to infer perceived problems of articulation of\nqueries, useless and irrelevant information, and unavailability of information\nfrom users\u2019 previous segment, current segment, and whole session behaviors. The\nfindings also demonstrated that by combining perceived problem(s) and search\nbehavioral features, it was possible to infer users\u2019 needed help(s) in search\nwith a certain level of accuracy (78%).<\/p>\n\n\n\n KEYWORDS<\/strong><\/p>\n\n\n\n Information need Implicit information need as explicit problems, help, and\nbehavioral signals is available via the following link: https:\/\/doi.org\/10.1016\/j.ipm.2019.102069<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" First, we must congratulate InfoSeeker, Ruoyuan Gao for having her paper accepted at ICTIR 2019! Next, we are excited to share the news that our InfoSeekers, Shawon Sarkar, Matthew Mitsui, Jiqun Liu and Chirag Shah, have published a new article! The title of the article is: Implicit information need as explicit problems, help, and behavioral signals. ABSTRACT Information need is one of the most fundamental aspects of information seeking, which traditionally conceptualizes as the initiation phase of an individual\u2019s information…<\/p>\n
Information searching
Interactive IR<\/p>\n\n\n\n