Investigations of search processes that involve complex interactions, such as collaborative search processes, are important research topics. Previous approaches of directly applying individual search process models into collaborative settings have proven to be problematic. In this paper, we proposed an innovative approach to model collaborative search processes using Hidden Markov Model (HMM), which is an automatic technique for analyzing temporal sequential data. Obtained through a user study, the data used in this paper consist of two different tasks in both collaborative exploratory Web search and individual exploratory Web search conditions. Our results showed that the identified hidden patterns of search process through HMM are compatible with previous well-known models. In addition, HMM generates detailed information on the transitions of hidden patterns in search processes, which demonstrated to be useful for analyzing task differences, and for determining the correlation of search process with search performance. The findings can be used for evaluating collaborative search systems as well as providing guidance for the system design. Author KeywordsCollaborative information behavior; exploratory search; Hidden Markov Model; information seeking process.
Mobile devices enable people to look for information at the moment when their information needs are triggered. While experiencing complex information needs that require multiple search sessions, users may utilize desktop computers to fulfill information needs started on mobile devices. Under the context of mobileto-desktop web search, this article analyzes users' behavioral patterns and compares them to the patterns in desktop-to-desktop web search. Then, we examine several approaches of using Mobile Touch Interactions (MTIs) to infer relevant content so that such content can be used for supporting subsequent search queries on desktop computers. The experimental data used in this article was collected through a user study involving 24 participants and six properly designed cross-device web search tasks. Our experimental results show that (1) users' mobile-to-desktop search behaviors do significantly differ from desktop-to-desktop search behaviors in terms of information exploration, sense-making and repeated behaviors. (2) MTIs can be employed to predict the relevance of click-through documents, but applying document-level relevant content based on the predicted relevance does not improve search performance. (3) MTIs can also be used to identify the relevant text chunks at a fine-grained subdocument level. Such relevant information can achieve better search performance than the document-level relevant content. In addition, such subdocument relevant information can be combined with document-level relevance to further improve the search performance. However, the effectiveness of these methods relies on the sufficiency of click-through documents. (4) MTIs can also be obtained from the Search Engine Results Pages (SERPs). The subdocument feedbacks inferred from this set of MTIs even outperform the MTI-based subdocument feedback from the click-through documents. ACM Reference Format:Shuguang Han, Zhen Yue, and Daqing He. 2015. Understanding and supporting cross-device web search for exploratory tasks with mobile touch interactions.
Collaboration in the information seeking and retrieval environment is common, particularly when the search task is complex and exploratory. Multiple factors such as contextual features and task type can affect users' query behavior. This paper presents a study investigating the effects of collaboration and task types on users' query behavior. The study involves two conditions: collaborative search and individual search, and the two search tasks: the recall‐oriented information‐gathering and the utility‐based decision‐making. We analyze users' query behavior in three dimensions: basic query features (e.g. the number of queries), query reformulation patterns (e.g. New, Specification, Generalization and Reconstruction) and query performance. The findings of this study reveal that queries are more diverse in collaborative search and recall‐oriented tasks. Users employed New and Specialization more often as query reformulation types in collaborative search while people in individual search use Reconstruction more often. Besides, the successful query rate is higher in individual search and recall‐oriented tasks.
Purpose -This paper aims to identify the opinions of undergraduate students on the importance of internet-based information sources when they undertake academic tasks. Design/methodology/approach -Based on a set of identified typical academic tasks for undergraduate students, three research questions were designed around the students' usage and views of information resources for completing these tasks. Web-accessible questionnaires were used to collect data from participants in two universities in the USA and China, and the data were analyzed using quantitative methods, which included several statistic methods. Findings -The results confirm that undergraduate students use different information resources for various academic tasks. In their tasks, online electronic resources including search engines are the most commonly used resources, particularly for complex academic tasks. Social networking sites are not used for the students' individual academic tasks, and traditional resources still play equal or more important roles in certain specific academic tasks. Students in collaborative tasks look for resources that make it easy to share documents. Participants from the two countries also exhibit interesting and important differences in their usage of information resources. Originality/value -This study examines undergraduate students' usages and views of different information resources in their various academic tasks, and pays special attention to the impacts of being from their different countries. The study also considers both students' individual academic tasks and collaborative tasks. This study is an invaluable addition to the information seeking behaviour literature. IntroductionWith the rapid development of communication and web technologies, scholars in all disciplines have access to an unprecedented wealth of information, tools and services (2008). The internet lies at the center of a global information infrastructure for distributed, data-intensive and collaborative research (Borgman, 2007). Creating and disseminating information online has become possible and desirable with the help of more vibrant, social and participatory Web 2.0 tools (Anderson, 2007); at the same time, it becomes increasingly critical for people to utilize various online information resources as a great deal of relevant information is available only online.Studying the interactions with information resources in people's search or information seeking is part of the study of information (seeking) behaviour (Ingwersen and Kalervo, 2005). Fisher and Julien (2009) describe in their review that studies of information behaviour can be classified based on the studied populations (such as scientists, students, certain occupational groups, or ordinary people in everyday life situations), the employed information sources (interpersonal, social networking, the internet, and libraries), the key contextual aspects and the underlying theoretical frameworks. This classification helps us to establish the research focus of this paper, which can be summ...
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