Beyond actions : exploring the discovery of tactics from user logs

Search log analysis has become a common practice to gain insights into user search behaviour; it helps gain an understanding of user needs and preferences, as well as an insight into how well a system supports such needs. Currently, log analysis is typically focused on low-level user actions, i.e. logged events such as issued queries and clicked results, and often only a selection of such events are logged and analysed. However, types of logged events may differ widely from interface to interface, making comparison between systems difficult. Further, the interpretation of the meaning of and subsequent analysis of a selection of events may lead to conclusions out of context—e.g. the statistics of observed query reformulations may be influenced by the existence of a relevance feedback component. Alternatively, in lab studies user activities can be analysed at a higher level, such as search tactics and strategies, abstracted away from detailed interface implementation. Unfortunately, until now the required manual codings that map logged events to higher-level interpretations have prevented large-scale use of this type of analysis. In this paper, we propose a new method for analysing search logs by (semi-)automatically identifying user search tactics from logged events, allowing large-scale analysis that is comparable across search systems. In addition, as the resulting analysis is at a tactical level we reduce potential issues surrounding the need for interpretation of low-level user actions for log analysis. We validate the efficiency and effectiveness of the proposed tactic identification method using logs of two reference search systems of different natures: a product search system and a video search system. With the identified tactics, we perform a series of novel log analyses in terms of entropy rate of user search tactic sequences, demonstrating how this type of analysis allows comparisons of user search behaviours across systems of different nature and design. This analysis provides insights not achievable with traditional log analysis

From information retrieval to hypertext and back again, the role of interaction in the information exploration interface

grantor: University of TorontoThis work explores the design space of user interfaces for large-scale full-text database retrieval systems. Research suggests that elements of hypertext interfaces may be merged with traditional information retrieval (IR) algorithms to produce flexible hybrid interfaces for user-directed information exploration. This work examines the effectiveness of multiple-view newspaper-like interfaces, and describes a prototype that uses newspaper-style layouts to organize information retrieval results. Finally, it explores some possible visualization techniques designed to aid browsing performance. The first of two experiments in this thesis examines the effectiveness of the simultaneous display of several documents retrieved by a given query. Experimental results suggest that viewed recall increases with increasing numbers of articles displayed on the screen simultaneously. Subjects' decision-making strategies appear to be independent of user interface factors. The second experiment tests differences in behavior between query-based and link-based browsing. Differences in performance are found between groups of users employing different strategies, but not between interface conditions. These results suggest that dynamic query-mediated hypertext interfaces are viable alternatives to more explicit queries, and that subjects' intrinsic strategies have significant impact on their interaction with the system and on their performance. This work proposes an implementation of dynamic links in the WWW medium. It concludes with a discussion about the nature of hypertext interfaces and about the role of the user interface in information exploration tasks, and suggests some avenues for future research in this area.Ph.D