SEARCHING AS THINKING: THE ROLE OF CUES IN QUERY REFORMULATION

Given the growing volume of information that surrounds us, search, and particularly web search, is now a fundamental part of how people perceive and experience the world. Understanding how searchers interact with search engines is thus an important topic both for designers of information retrieval systems and educators working in the area of digital literacy. Reaching such understanding, however, with the more established, system-centric, approaches in information retrieval (IR) is limited. While inherently iterative nature of the search process is generally acknowledged in the field of IR, research on query reformulation is typically limited to dealing with the what or the how of the query reformulation process. Drawing a complete picture of searchers\u27 behavior is thus incomplete without addressing the why of query reformulation, including what pieces of information, or cues, trigger the reformulation process. Unpacking that aspect of the searchers\u27 behavior requires a more user-centric approach. The overall goal of this study is to advance understanding of the reformulation process and the cues that influence it. It was driven by two broad questions about the use of cues (on the search engine result pages or the full web pages) in the searchers\u27 decisions regarding query reformulation and the effects of that use on search effectiveness. The study draws on data collected in a lab setting from a sample of students who performed a series of search tasks and then went through a process of stimulated recall focused on their query reformulations. Both, query reformulations recorded during the search tasks and cues elicited during the stimulated recall exercise, were coded and then modeled using the mixed effects method. The final models capture the relationships between cues and query reformulation strategies as well as cues and search effectiveness; in both cases some relationships are moderated by search expertise and domain knowledge. The results demonstrate that searchers systematically elicit and use cues with regard to query reformulation. Some of these relationships are independent from search expertise and domain knowledge, while others manifest themselves differently at different levels of search expertise and domain knowledge. Similarly, due to the fact that the majority of the reformulations in this study indicated a failure of the preceding query, mixed results were achieved with identifying relationships between the use of cues and search effectiveness. As a whole, this work offers two contributions to the field of user-centered information retrieval. First, it reaffirms some of the earlier conceptual work about the role of cues in search behavior, and then expands on it by proposing specific relationships between cues and reformulations. Second, it highlights potential design considerations in creating search engine results pages and query term suggestions, as well as and training suggestion for educators working on digital literacy

An Ontology- Content-based Filtering Method

Traditional content-based filtering methods usually utilize text extraction and classification techniques for building user profiles as well as for representations of contents, i.e. item profiles. These methods have some disadvantages e.g. mismatch between user profile terms and item profile terms, leading to low performance. Some of the disadvantages can be overcome by incorporating a common ontology which enables representing both the users' and the items' profiles with concepts taken from the same vocabulary. We propose a new content-based method for filtering and ranking the relevancy of items for users, which utilizes a hierarchical ontology. The method measures the similarity of the user's profile to the items' profiles, considering the existing of mutual concepts in the two profiles, as well as the existence of "related" concepts, according to their position in the ontology. The proposed filtering algorithm computes the similarity between the users' profiles and the items' profiles, and rank-orders the relevant items according to their relevancy to each user. The method is being implemented in ePaper, a personalized electronic newspaper project, utilizing a hierarchical ontology designed specifically for classification of News items. It can, however, be utilized in other domains and extended to other ontologies