Search (4 results, page 1 of 1)

  • × author_ss:"White, R.W."
  1. White, R.W.: Belief dynamics in web search (2014) 0.04
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    Abstract
    People frequently answer consequential questions, such as those with a medical focus, using Internet search engines. Their primary goal is to revise or establish beliefs in one or more outcomes. Search engines are not designed to furnish answers, and instead provide results that may contain answers. Information retrieval research has targeted aspects of information access such as query formulation, relevance, and search success. However, there are important unanswered questions on how beliefs-and potential biases in those beliefs-affect search behaviors and how beliefs are shaped by searching. To understand belief dynamics, we focus on yes-no medical questions (e.g., "Is congestive heart failure a heart attack?"), with consensus answers from physicians. We show that (a) presearch beliefs are affected only slightly by searching and changes are likely to skew positive (yes); (b) presearch beliefs affect search behavior; (c) search engines can shift some beliefs by manipulating result rank and availability, but strongly-held beliefs are difficult to move using uncongenial information and can be counterproductive, and (d) search engines exhibit near-random answer accuracy. Our findings suggest that search engines should provide correct answers to searchers' questions and develop methods to persuade searchers to shift strongly held but factually incorrect beliefs.
  2. White, R.W.: Interactions with search systems (2016) 0.02
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    LCSH
    Search engines / Technological innovations
    Subject
    Search engines / Technological innovations
  3. White, R.W.; Jose, J.M.; Ruthven, I.: ¬A task-oriented study on the influencing effects of query-biased summarisation in web searching (2003) 0.02
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    Abstract
    The aim of the work described in this paper is to evaluate the influencing effects of query-biased summaries in web searching. For this purpose, a summarisation system has been developed, and a summary tailored to the user's query is generated automatically for each document retrieved. The system aims to provide both a better means of assessing document relevance than titles or abstracts typical of many web search result lists. Through visiting each result page at retrieval-time, the system provides the user with an idea of the current page content and thus deals with the dynamic nature of the web. To examine the effectiveness of this approach, a task-oriented, comparative evaluation between four different web retrieval systems was performed; two that use query-biased summarisation, and two that use the standard ranked titles/abstracts approach. The results from the evaluation indicate that query-biased summarisation techniques appear to be more useful and effective in helping users gauge document relevance than the traditional ranked titles/abstracts approach. The same methodology was used to compare the effectiveness of two of the web's major search engines; AltaVista and Google.
  4. White, R.W.; Roth, R.A.: Exploratory search : beyond the query-response paradigm (2009) 0.02
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    Abstract
    As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world.