Understanding patrons’ micro-level information seeking (MLIS) in information retrieval situations

摘要

Elicitation is a communicative act to request information during a dialogue, which reflects the questioner’s problems at hand, perplexity, interests, or perhaps internal concerns, either voluntarily or unintentionally. A patron with an information need or a problem at hand approaches the retrieval system to ask their first question. However, many more communicative acts requesting information occur during the retrieval interaction. Elicitation during retrieval interaction, as distinct from the patron’s first search question, is termed micro-level information seeking (MLIS). What features does MLIS possess? And is MLIS predictable? These are salient research issues because if a patron’s MLIS is explainable and predictable, it is advantageous for the intermediary, be it human or an intelligent agent, to form a dynamic user model by taking the patron’s MLIS into account to provide better information retrieval support. This study explores the following research questions: (1) What are the purposes of patron elicitations? (2) When does the patron’s elicitation tend to occur? (3) Do patron elicitations differ from intermediary elicitations in terms of frequency of occurrence and time frame? (4) Does patron elicitation behavior relate to contextual variables, such as gender, age, status, knowledge, prior online search experience, individual intermediaries interacted with, or length of interaction? Qualitative and quantitative approaches including discourse analysis, content analysis and statistical analysis are applied. The major research findings include: (1) patrons’ and intermediaries’ elicitation behaviors differ in terms of frequency and time frame, supporting the prior assumption that intermediary elicitation is pre-planned and patron elicitation is situational; (2) patron’s perplexity is situational, being in most cases “search-assignment related”; and (3) patrons’ elicitation behavior is significantly related to their contextual variables. The study suggests dynamic user modeling to take account of the patron’s MLIS.