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Interaction. LBSC 734 Module 4 Doug Oard. Agenda. Where interaction fits Query formulation Selection part 1: Snippets Selection part 2: Result sets Examination. Moore’s Law. computer performance. transistors speed storage. 1950. 1990. 2030. Human Cognition. human
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Interaction LBSC 734 Module 4 Doug Oard
Agenda • Where interaction fits • Query formulation • Selection part 1: Snippets • Selection part 2: Result sets • Examination
Moore’s Law computer performance transistors speed storage ... 1950 1990 2030
Human Cognition human performance 1950 1990 2030 1990
human performance: the limiting factor Goal: Maximize Human Effectiveness Slide idea by Bill Buxton
Resource Query Ranked List Documents System discovery Vocabulary discovery Concept discovery Document discovery Documents source reselection Interaction Points Help users decide where to start Source Selection Help users formulate queries Query Formulation Help users make sense of results and navigate information space Search Selection Examination Delivery
Information Needs RIN0 Real information needs (RIN) = visceral need PIN0 PINm Perceived information needs (PIN) = conscious need … Request = formalized need r0 r1 rn Query = compromised need q0 q1 q2 q3 qr Stefano Mizzaro. (1999) How Many Relevances in Information Retrieval? Interacting With Computers, 10(3), 305-322.
Broder’s Web Query Taxonomy • Informational (~50%) • Acquire static information (“topical”) • Navigational (~20%) • Reach a particular site (“known item”) • Transactional (~30%) • Perform a Web-mediated activity (“service”) Andrei Broder, SIGIR Forum, Fall 2002
Bates’ “Berry Picking” Model A sketch of a searcher… “moving through many actions towards a general goal of satisfactory completion of research related to an information need.” Q2 Q4 Q3 Q1 Q5 Q0
Agenda • Where interaction fits • Query formulation • Selection part 1: Snippets • Selection part 2: Result sets • Examination