Search (2 results, page 1 of 1)

  • × author_ss:"Ke, W."
  1. Zhang, Y.; Broussard, R.; Ke, W.; Gong, X.: Evaluation of a scatter/gather interface for supporting distinct health information search tasks (2014) 0.00
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    Abstract
    Web search engines are important gateways for users to access health information. This study explored whether a search interface based on the Bing API and enabled by Scatter/Gather, a well-known document-clustering technique, can improve health information searches. Forty participants without medical backgrounds were randomly assigned to two interfaces: a baseline interface that resembles typical web search engines and a Scatter/Gather interface. Both groups performed two lookup and two exploratory health-related tasks. It was found that the baseline group was more likely to rephrase queries and less likely to access general-purpose sites than the Scatter/Gather group when completing exploratory tasks. Otherwise, the two groups did not differ in behavior and task performance, with participants in the Scatter/Gather group largely overlooking the features (key words, clusters, and the recluster function) designed to facilitate the exploration of semantic relationships between information objects, a potentially useful means for users in the rather unfamiliar domain of health. The results suggest a strong effect of users' mental models of search on their use of search interfaces and a high cognitive cost associated with using the Scatter/Gather features. It follows that novel features of a search interface should not only be compatible with users' mental models but also provide sufficient affordance to inform users of how they can be used. Compared with the interface, tasks showed more significant impacts on search behavior. In future studies, more effort should be devoted to identify salient features of health-related information needs.
    Type
    a
  2. Ke, W.: Decentralized search and the clustering paradox in large scale information networks (2012) 0.00
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    Abstract
    Amid the rapid growth of information today is the increasing challenge for people to navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web raise important questions about information retrieval in these environments. Collection of all information in advance and centralization of IR operations are extremely difficult, if not impossible, because systems are dynamic and information is distributed. The chapter discusses some of the key issues facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and discusses a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit.
    Type
    a