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Collaborative information search (CIS) is a growing and significant research area. Query formulation and reformulation is an important search strategy in information search. However, limited research has investigated query behavior during CIS. The purpose of this paper is to characterize collaborative query reformulation (CQR) by exploring the sources of collaborative query (CQ) terms and the types and patterns of CQR in the context of tourism information search.

An empirical study was designed to investigate search query reformulation as tourists performed CIS on a devised interface. A total of 36 participants (in 18 pairs) took part in the study; data were documented in pre- and post-search questionnaires, search logs and chat logs.

The findings show that participants intermixed individual search and collaborative search during CIS. Participants constructed CQ terms mainly by selecting terms from individual search queries and discussion chat logs. Eight types of CQR were identified, with specialization (82 percent) accounting for the most used search tactics. At most times, participants were found to add terms to the previous query. Findings demonstrated 27 specific CQR patterns; in excess of two-third participants (69 percent) took only one move to reformulate CQ by adding terms, or replacing/using new words.

The results of this research can be used to inform the design of search systems supporting collaborative querying in CIS.

This study is highlighting an important research direction of CQ reformulation in collaborative search while previous studies of the topic are limited, comparing to the vast body of work on query reformulation in individual information search using regular search systems.

Collaborative information searching is common for people when planning their group trip. However, little research has explored how tourists collaborate during information search. Existing tourism Web portals or search engines rarely support tourists’ collaborative information search activities. Taking advantage of previous studies of collaborative tourism information search behavior, in the current paper the purpose of this paper is to propose the design of a collaborative search system collaborative tourism information search (ColTIS) to support online information search and travel planning.

ColTIS was evaluated and compared with Google Talk-embedded Tripadvisor.com through a user study involving 18 pairs of participants. The data included pre- and post-search questionnaires, web search logs and chat history. For quantitative measurement, statistical analysis was performed using SPSS; for log data and the qualitative feedback from participants, the content analysis was employed.

Results suggest that collaborative query formulation, division of search tasks, chatting and results sharing are important means to facilitate tourists’ collaborative search. ColTIS was found to outperform Tripadvisor significantly regarding the ease of use, collaborative support and system usefulness.

The innovation of the study lies in the development of an integrated real-time collaborative tourism information search system with unique features. These features include collaborative query reformulation, travel planner and automatic result and query sharing that assist multiple people search for holiday information together. For system designers and tourism practitioners, implications are provided.

Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. Aims to address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harnessing the collective knowledge of other searchers.

The design and implementation of the Query Graph Visualizer (QGV), a collaborative querying system which harvests and clusters previously issued queries to form query networks that represent related information needs are described. A preliminary evaluation of the QGV is also described in which a group of participants evaluated the usability and usefulness of the system by completing a set of tasks and a questionnaire based on Nielsen's heuristic evaluation technique.

In the QGV, a submitted query is matched to its closest cluster and a recursive algorithm is applied to find other related clusters, forming a query network. The queries in the network are explored in the QGV, helping users locate other queries that might meet their current information needs. The results of the evaluation suggest the usefulness and usability of the system. Participants could complete their assigned tasks using the QGV and positively rated the system in terms of usability.

The techniques described can be used to design information retrieval systems that learn from the trials and tribulations of other searchers and help users in their quest for relevant and quality information

Purpose — This chapter illustrates and explains the ambiguity and vagueness of the term social search and aims at describing and classifying the heterogeneous landscape of social search implementations on the WWW.

Methodology/approach — We have looked at different definitions as well as the context of social search by carrying out an extensive literature review, and tried to unify and enhance existing ideas and concepts. Our definition of social search is illustrated by a general review of existing social search engines, which are analyzed and described by their specific features and social aspects.

Findings — The chapter presents a discussion of social search as well as a comparison of existing social search engines.

Social implications — The definition of social search and the comparison of social search engines summarize the many ways people can search the web together and allow for an assessment of future developments in this area.

Originality/value of paper — Although different attempts to define social search have been made in the past, we present an argumentation that unifies some existing definitions and which is different from other interpretations of the social search concept. We present an overview and a comparison of the different genres of social search engines.

The purpose of this paper is to explore the differences between collaborative and individual search techniques in a scenario-based task focussed on query behavior, cognitive load, search time, and task type about the search.

To help understand the influences on searching for relevant information in pairs or individual contexts, the authors conducted an exploratory user study with 30 participants, using two search tasks completed in a controlled laboratory setting.

On the basis of the analysis, the authors found that collaborative search teams resulted in more queries, more diverse query terms, and more varied query results compared to those working individually. The study results indicated that the cognitive load imposed on the participants did not differ between a collaborative search and an individual search except for the component of performance on the NASA Task Load Index. The results further showed that the total search time was a significant difference on average between the two conditions (i.e. individual information search and collaborative information search) for the second task. And there were significant differences of the mean of total search time between the two tasks for the both conditions. The authors also found that there was no significant relationship between query behavior and the total cognitive load.

The findings from this study have implications for a better understanding of collaborative search interface design, searchers’ cognitive load, query behavior, and general collaborative information search.

The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of collaborators in an academic network that is automatically and dynamically formed. By using the constructed Collaborative Hit Matrix (CHM), results are obtained that are based on the search behaviour and earned preferences of specialist communities of researchers, which are relevant to the user's need and reduce the time spent on bad links.

By using the Digital Bibliography Library Project (DBLP), the research communities are formed implicitly and dynamically based on the users’ research presence in the search environment and in the publication scenario, which is also used to assign users’ roles and establish links between the users. The CHM, to store the hit count and hit list of page results for queries, is also constructed and updated after every search session to enhance the collaborative search among the researchers.

The implicit researchers community formation, the assignment and dynamic updating of roles of the researchers based on research, search presence and search behaviour on the web as well as the usage of these roles during Collaborative Web Search have highly improved the relevancy of results. The CHM that holds the collaborative responses provided by the researchers on the search query results to support searching distinguishes this system from others. Thus the proposed system considerably improves the relevancy and reduces the time spent on bad links, thus improving recall and precision.

The research findings illustrate the better performance of the system, by connecting researchers working in the same field and allowing them to help each other in a web search environment.

The purpose of this paper is to explore users’ learning in the collaborative information search process when they conduct an academic task as a group.

This paper presents a longitudinal study for a three-month period on an actual task. The participants, who were undergraduate students, needed to write a research proposal in three months to apply for funding for a research project, including a three-hour experiment.

The results show that undergraduates’ learning in the collaborative search process for academic group work included knowledge reconstruction, tuning, and assimilation. Their understanding of the topic concepts improved through the process, and their attitudes became more optimistic. Besides, the learning in the collaborative information search process also enhanced participants’ skills in communication, research, information search, and collaboration. To improve learning outcomes, professional and appropriate academic resources are required, as well as effective division of labor, positive sharing behaviors, and use of collaborative systems.

The future development of collaborative information search systems should focus on the needs of academic research and support for elements such as instant communication and knowledge sharing.

This paper contributes to research into searching as learning by understanding undergraduates’ collaborative search behavior for writing a proposal.

In this work, a new general framework is proposed to guide navigation over a collaborative concept network, in order to discover paths between concepts. Finding semantic chains between concepts over a semantic network is an issue of great interest for many applications, such as explanation generation and query expansion. Collaborative concept networks over the web tend to have features such as large dimensions, high connectivity degree, dynamically evolution over the time, which represent special challenges for efficient graph search methods, since they result in huge memory requirements, high branching factors, unknown dimensions and high cost for accessing nodes. The paper aims to discuss these issues.

The proposed framework is based on the novel notion of heuristic semantic walk (HSW). In the HSW framework, a semantic proximity measure among concepts, reflecting the collective knowledge embedded in search engines or other statistical sources, is used as a heuristic in order to guide the search in the collaborative network. Different search strategies, information sources and proximity measures, can be used to adapt HSW to the collaborative semantic network under consideration.

Experiments held on the Wikipedia network and Bing search engine on a range of different semantic measures show that the proposed HSW approach with weighted randomized walk strategy outperforms state-of-the-art search methods.

To the best of the authors' knowledge, the proposed HSW model is the first approach which uses search engine-based proximity measures as heuristic for semantic search.

Collaboration is often required for activities that are too complex or difficult to be dealt with by a single individual. Many situations requiring information-seeking activities also call for people to work together. Often the methods, systems, and tools that provide access to information assume that they are used only by individuals working on their tasks alone. This review points to the need to acknowledge the importance of collaboration in information-seeking processes, to study models, and to develop systems that are specifically designed to enable collaborative information seeking (CIS) tasks. This chapter reviews the literature from various domains including library and information science, human–computer interaction, collaborative systems, and information retrieval. Focus of the review is on the extent to which people work together on information seeking tasks and the systems and tools that are available for them to be successful. Since CIS occurs in the broader context of collaboration in general, a review of literature about collaborations is first undertaken to define it and place it into context with related terms such as cooperation and communication. A more focused review of research follows relating CIS to systems that have attempted to support such interactions. Included are identification and synthesis of a number of core issues in the field and how best to evaluate systems and collaborative tools. Key lessons learned from the review are summarized, and gaps in the literature identified to spur future research and study.

This study proposes an integrated collaborative web site among government agencies to enhance customer satisfaction with the service quality of government agencies.

The present authors invited all involved public‐sector agencies to integrate their service processes into a model of one‐stop shopping and established collaborative mechanism for providing customized service.

The present study has identified five factors that were critical for success in such an undertaking. These factors included: establishing appropriate regulations for the implementation process; designing a viable collaborative‐service system; establishing a closely connected virtual organization; ensuring the participation of senior managers from all agencies; and obtaining the cooperation of the facilitators from various agencies (including appropriate merit and bonus incentives).

The real challenge for establishing the collaborative‐service web site was managerial – in combining the service processes of a dozen or more agencies to make the model work. Managerial issues that need to be addressed were the design of service processes, the overall organizational structure, the establishment of audit and supervision procedures, and the establishment an operational model for the web site.

This web site serves as a successful “one‐stop‐shopping” model that increases customer satisfaction with the service quality of government agencies. This study provides information for other government agencies that might wish to establish similar collaborative models to enhance service in the public sector.