From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Ideation as an intellectual information acquisition and use context: Investigating game designers’ information-based ideation behavior

Human Information Behavior (HIB) research commonly examines behavior in the context of why information is acquired and how it will be used, but usually at the level of the work or everyday-life tasks the information will support. HIB has not been examined in detail at the broader contextual level of intellectual purpose (i.e. the higher-order conceptual tasks the information was acquired to support). Examination at this level can enhance holistic understanding of HIB as a ‘means to an intellectual end’ and inform the design of digital information environments that support information interaction for specific intellectual purposes. We investigate information-based ideation (IBI) as a specific intellectual information acquisition and use context by conducting Critical Incident-style interviews with ten game designers, focusing on how they interact with information to generate and develop creative design ideas. Our findings give rise to a framework of their ideation-focused HIB, which systems designers can leverage to reason about how best to support certain behaviors to drive design ideation. These findings emphasize the importance of intellectual purpose as a driver for acquisition and desired outcome of use

An analytical inspection framework for evaluating the search tactics and user profiles supported by information seeking interfaces

Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects

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

Designing Interfaces to Support Collaboration in Information Retrieval

Information retrieval systems should acknowledge the existence of collaboration in the search process. Collaboration can help users to be more effective in both learning systems and in using them. We consider some issues of viewing interfaces to information retrieval systems as collaborative notations and how to build systems that more actively support collaboration. We describe a system that embodies just one kind of explicit support; a graphical representation of the search process that can be manipulated and discussed by the users. By acknowledging the importance of other people in the search process, we can develop systems that not only improve help-giving by people but which can lead to a more robust search activity, more able to cope with, and indeed exploit, the failures of any intelligent agents used

INVESTIGATING SEARCH PROCESSES IN COLLABORATIVE EXPLORATORY WEB SEARCH

People are often engaged in collaboration in workplaces or daily life due to the complexity of tasks. In the information seeking and retrieval environment, the task can be as simple as fact-finding or a known-item search, or as complex as exploratory search. Given the complex nature of the information needs, exploratory searches may require the collaboration among multiple people who share the same search goal. For instance, students may work together to search for information in a collaborative course project; friends may search together while planning a vacation. There are demands for collaborative search systems that could support this new format of search (Morris, 2013). Despite the recognized importance of understanding search process for designing successful search system (Bates, 1990; M. Hearst, 2009), it is particularly difficult to study collaborative search process because of the complex interactions involved. In this dissertation, I propose and demonstrate a framework of investigating search processes in the collaborative exploratory search. I designed a laboratory-based user study to collect the data, compared two search conditions: individual search and collaborative search as well as two task types through the study. I first applied a novel Hidden Markov Model approach to analyze the search states in the collaborative search process, the results of which provide a holistic picture of the collaborative search process. I then investigated two important components in the collaborative search process – query behaviors and communications. The findings reveal the characteristics of query and communication patterns in the collaborative search. It also suggests that although the collaboration between two people on search did not achieve a higher performance than two individuals, the collaboration indeed make people feel more satisfied with their performance and less stressed. The results of this study not only provide implications for designing effective collaborative search systems, but also show valuable research directions and methodologies for other researchers

Investigating User Search Tactic Patterns and System Support in Using Digital Libraries

This study aims to investigate users\u27 search tactic application and system support in using digital libraries. A user study was conducted with sixty digital library users. The study was designed to answer three research questions: 1) How do users engage in a search process by applying different types of search tactics while conducting different search tasks?; 2) How does the system support users to apply different types of search tactics?; 3) How do users\u27 search tactic application and system support for different types of search tactics affect search outputs? Sixty student subjects were recruited from different disciplines in a state research university. Multiple methods were employed to collect data, including questionnaires, transaction logs and think-aloud protocols. Subjects were asked to conduct three different types of search tasks, namely, known-item search, specific information search and exploratory search, using Library of Congress Digital Libraries. To explore users\u27 search tactic patterns (RQ1), quantitative analysis was conducted, including descriptive statistics, kernel regression, transition analysis, and clustering analysis. Types of system support were explored by analyzing system features for search tactic application. In addition, users\u27 perceived system support, difficulty, and satisfaction with search tactic application were measured using post-search questionnaires (RQ2). Finally, the study examined the causal relationships between search process and search outputs (RQ 3) based on multiple regression and structural equation modeling. This study uncovers unique behavior of users\u27 search tactic application and corresponding system support in the context of digital libraries. First, search tactic selections, changes, and transitions were explored in different task situations - known-item search, specific information search, and exploratory search. Search tactic application patterns differed by task type. In known-item search tasks, users preferred to apply search query creation and following search result evaluation tactics, but less query reformulation or iterative tactic loops were observed. In specific information search tasks, iterative search result evaluation strategies were dominantly used. In exploratory tasks, browsing tactics were frequently selected as well as search result evaluation tactics. Second, this study identified different types of system support for search tactic application. System support, difficulty, and satisfaction were measure in terms of search tactic application focusing on search process. Users perceived relatively high system support for accessing and browsing tactics while less support for query reformulation and item evaluation tactics. Third, the effects of search tactic selections and system support on search outputs were examined based on multiple regression. In known-item searches, frequencies of query creation and accessing forwarding tactics would positively affect search efficiency. In specific information searches, time spent on applying search result evaluation tactics would have a positive impact on success rate. In exploratory searches, browsing tactics turned out to be positively associated with aspectual recall and satisfaction with search results. Based on the findings, the author discussed unique patterns of users\u27 search tactic application as well as system design implications in digital library environments

Investigating people: a qualitative analysis of the search behaviours of open-source intelligence analysts

The Internet and the World Wide Web have become integral parts of the lives of many modern individuals, enabling almost instantaneous communication, sharing and broadcasting of thoughts, feelings and opinions. Much of this information is publicly facing, and as such, it can be utilised in a multitude of online investigations, ranging from employee vetting and credit checking to counter-terrorism and fraud prevention/detection. However, the search needs and behaviours of these investigators are not well documented in the literature. In order to address this gap, an in-depth qualitative study was carried out in cooperation with a leading investigation company. The research contribution is an initial identification of Open-Source Intelligence investigator search behaviours, the procedures and practices that they undertake, along with an overview of the difficulties and challenges that they encounter as part of their domain. This lays the foundation for future research in to the varied domain of Open-Source Intelligence gathering