Search (10 results, page 1 of 1)

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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.

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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.

Content

Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks

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Abstract

Information seeking is a fundamental human activity. In the modern world, it is frequently conducted through interactions with search systems. The retrieval and comprehension of information returned by these systems is a key part of decision making and action in a broad range of settings. Advances in data availability coupled with new interaction paradigms, and mobile and cloud computing capabilities, have created a broad range of new opportunities for information access and use. In this comprehensive book for professionals, researchers, and students involved in search system design and evaluation, search expert Ryen White discusses how search systems can capitalize on new capabilities and how next-generation systems must support higher order search activities such as task completion, learning, and decision making. He outlines the implications of these changes for the evolution of search evaluation, as well as challenges that extend beyond search systems in areas such as privacy and societal benefit.

Footnote

Vgl. auch den Beitrag: Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern. In: http://www.password-online.de/?wysija-page=1&controller=email&action=view&email_id=254&wysijap=subscriptions&user_id=1045..

LCSH

Search engines / Technological innovations

Subject

Search engines / Technological innovations

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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.

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Footnote

Einführung in einen Themenschwerpunkt "Evaluating exploratory search systems"

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Abstract

In explicit collaborative search, two or more individuals coordinate their efforts toward a shared goal. Every day, Internet users with similar information needs have the potential to collaborate. However, online search is typically performed in solitude. Existing search systems do not promote explicit collaborations, and collaboration opportunities (collabportunities) are missed. In this article, we describe a method to evaluate the feasibility of transforming these collabportunities into recommendations for explicit collaboration. We developed a technique called pseudocollaboration to evaluate the benefits and costs of collabportunities through simulations. We evaluate the performance of our method using three data sets: (a) data from single users' search sessions, (b) data with collaborative search sessions between pairs of searchers, and (c) logs from a large-scale search engine with search sessions of thousands of searchers. Our results establish when and how collabportunities would significantly help or hinder the search process versus searches conducted individually. The method that we describe has implications for the design and implementation of recommendation systems for explicit collaboration. It also connects system-mediated and user-mediated collaborative search, whereby the system evaluates the likely benefits of collaborating for a search task and helps searchers make more informed decisions on initiating and executing such a collaboration.

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Abstract

Advances in search technology have meant that search systems can now offer assistance to users beyond simply retrieving a set of documents. For example, search systems are now capable of inferring user interests by observing their interaction, offering suggestions about what terms could be used in a query, or reorganizing search results to make exploration of retrieved material more effective. When providing new search functionality, system designers must decide how the new functionality should be offered to users. One major choice is between (a) offering automatic features that require little human input, but give little human control; or (b) interactive features which allow human control over how the feature is used, but often give little guidance over how the feature should be best used. This article presents a study in which we empirically investigate the issue of control by presenting an experiment in which participants were asked to interact with three experimental systems that vary the degree of control they had in creating queries, indicating which results are relevant in making search decisions. We use our findings to discuss why and how the control users want over search decisions can vary depending on the nature of the decisions and the impact of those decisions on the user's search.

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Abstract

When users have poorly defined or complex goals, search interfaces that offer only keyword-searching facilities provide inadequate support to help them reach their information-seeking objectives. The emergence of interfaces with more advanced capabilities, such as faceted browsing and result clustering, can go some way toward addressing such problems. The evaluation of these interfaces, however, is challenging because they generally offer diverse and versatile search environments that introduce overwhelming amounts of independent variables to user studies; choosing the interface object as the only independent variable in a study would reveal very little about why one design outperforms another. Nonetheless, if we could effectively compare these interfaces, then we would have a way to determine which was best for a given scenario and begin to learn why. In this article, we present a formative inspection framework for the evaluation of advanced search interfaces through the quantification of the strengths and weaknesses of the interfaces in supporting user tactics and varying user conditions. This framework combines established models of users and their needs and behaviors to achieve this. The framework is applied to evaluate three search interfaces and demonstrates the potential value of this approach to interactive information retrieval evaluation.

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Abstract

Interactive query expansion (IQE) (c.f. [Efthimiadis, E. N. (1996). Query expansion. Annual Review of Information Systems and Technology, 31, 121-187]) is a potentially useful technique to help searchers formulate improved query statements, and ultimately retrieve better search results. However, IQE is seldom used in operational settings. Two possible explanations for this are that IQE is generally not integrated into searchers' established information-seeking behaviors (e.g., examining lists of documents), and it may not be offered at a time in the search when it is needed most (i.e., during the initial query formulation). These challenges can be addressed by coupling IQE more closely with familiar search activities, rather than as a separate functionality that searchers must learn. In this article we introduce and evaluate a variant of IQE known as Real-Time Query Expansion (RTQE). As a searcher enters their query in a text box at the interface, RTQE provides a list of suggested additional query terms, in effect offering query expansion options while the query is formulated. To investigate how the technique is used - and when it may be useful - we conducted a user study comparing three search interfaces: a baseline interface with no query expansion support; an interface that provides expansion options during query entry, and a third interface that provides options after queries have been submitted to a search system. The results show that offering RTQE leads to better quality initial queries, more engagement in the search, and an increase in the uptake of query expansion. However, the results also imply that care must be taken when implementing RTQE interactively. Our findings have broad implications for how IQE should be offered, and form part of our research on the development of techniques to support the increased use of query expansion.

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Abstract

Web searchers typically fall to view search results beyond the first page nor fully examine those results presented to them. In this article we describe an approach that encourages a deeper examination of the contents of the document set retrieved in response to a searcher's query. The approach shifts the focus of perusal and interaction away from potentially uninformative document surrogates (such as titles, sentence fragments, and URLs) to actual document content, and uses this content to drive the information seeking process. Current search interfaces assume searchers examine results document-by-document. In contrast our approach extracts, ranks, and presents the contents of the top-ranked document set. We use query-relevant topranking sentences extracted from the top documents at retrieval time as fine-grained representations of topranked document content and, when combined in a ranked list, an overview of these documents. The interaction of the searcher provides implicit evidence that is used to reorder the sentences where appropriate. We evaluate our approach in three separate user studies, each applying these sentences in a different way. The findings of these studies show that top-ranking sentences can facilitate effective information access.