Search (132 results, page 1 of 7)

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Abstract

The Internet has led to an increase in the quantity and diversity of information available for searching. Furthermore, users are bombarded by a constant barrage of electronic messages in the form of e-mail, faxes, etc. This has led to a plethora of search engines, 'intelligent'agents, etc., that aim to help users in their quest for relevant information, or shield them against irrelevant information. All these systems aim to identify the potentially relevant information in among a large pool of available information. No unifying underlying theory for information discovery systems exist as yet. The aim of this article is to provide a logic-based framework for information discovery, and relate this to the traditional field of information retrieval. Furthermore, the often ignored user receives special emphasis. In information discovery, a good understanding of a user's (sometimes hidden) needs and beliefs is essential. We will develop a logic-based approach to express the mechanics of information discovery, while the pragmatics are based on an analysis of the underlying informational semantics of information carriers and information needs of users

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Content

Special issue devoted to the theme 'Knowledge and policy: a search for new ideas'

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Abstract

Previous research investigated how to leverage the new type of social data available on the web, e.g., tags, ratings and reviews, in recommending and personalizing information. However, previous works mainly focused on predicting ratings using collaborative filtering or quantifying personalized ranking quality in simulations. As a consequence, the effect of social information in user's information search and information-selection behavior remains elusive. The objective of our research is to investigate the effects of social information on users' interactive search and information-selection behavior. We present a computational method and a system implementation combining different graph overlays: social, personal and search-time user input that are visualized for the user to support interactive information search. We report on a controlled laboratory experiment, in which 24 users performed search tasks using three system variants with different graphs as overlays composed from the largest publicly available social content and review data from Yelp: personal preferences, tags combined with personal preferences, and tags and social ratings combined with personal preferences. Data comprising search logs, questionnaires, simulations, and eye-tracking recordings show that: 1) the search effectiveness is improved by using and visualizing the social rating information and the personal preference information as compared to content-based ranking. 2) The need to consult external information before selecting information is reduced by the presentation of the effects of different overlays on the search results. Search effectiveness improvements can be attributed to the use of social rating and personal preference overlays, which was also confirmed in a follow-up simulation study. With the proposed method we demonstrate that social information can be incorporated to the interactive search process by overlaying graphs representing different information sources. We show that the combination of social rating information and personal preference information improves search effectiveness and reduce the need to consult external information. Our method and findings can inform the design of interactive search systems that leverage the information available on the social web.

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Abstract

Consider a sentence such as "the current price of tea in China is 35 cents per pound." In a library with millions of books we might find many statements of the above form that we could capture today with relatively simple rules: rather than pursuing every variation of a statement, programs can wait, like predators at a water hole, for their informational prey to reappear in a standard linguistic pattern. We can make inferences from sentences such as "NAME1 born at NAME2 in DATE" that NAME more likely than not represents a person and NAME a place and then convert the statement into a proposition about a person born at a given place and time. The changing price of tea in China, pedestrian birth and death dates, or other basic statements may not be truth and beauty in the Phaedrus, but a digital library that could plot the prices of various commodities in different markets over time, plot the various lifetimes of individuals, or extract and classify many events would be very useful. Services such as the Syllabus Finder1 and H-Bot2 (which Dan Cohen describes elsewhere in this issue of D-Lib) represent examples of information extraction already in use. H-Bot, in particular, builds on our evolving ability to extract information from very large corpora such as the billions of web pages available through the Google API. Aside from identifying higher order statements, however, users also want to search and browse named entities: they want to read about "C. P. E. Bach" rather than his father "Johann Sebastian" or about "Cambridge, Maryland", without hearing about "Cambridge, Massachusetts", Cambridge in the UK or any of the other Cambridges scattered around the world. Named entity identification is a well-established area with an ongoing literature. The Natural Language Processing Research Group at the University of Sheffield has developed its open source Generalized Architecture for Text Engineering (GATE) for years, while IBM's Unstructured Information Analysis and Search (UIMA) is "available as open source software to provide a common foundation for industry and academia." Powerful tools are thus freely available and more demanding users can draw upon published literature to develop their own systems. Major search engines such as Google and Yahoo also integrate increasingly sophisticated tools to categorize and identify places. The software resources are rich and expanding. The reference works on which these systems depend, however, are ill-suited for historical analysis. First, simple gazetteers and similar authority lists quickly grow too big for useful information extraction. They provide us with potential entities against which to match textual references, but existing electronic reference works assume that human readers can use their knowledge of geography and of the immediate context to pick the right Boston from the Bostons in the Getty Thesaurus of Geographic Names (TGN), but, with the crucial exception of geographic location, the TGN records do not provide any machine readable clues: we cannot tell which Bostons are large or small. If we are analyzing a document published in 1818, we cannot filter out those places that did not yet exist or that had different names: "Jefferson Davis" is not the name of a parish in Louisiana (tgn,2000880) or a county in Mississippi (tgn,2001118) until after the Civil War.

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Footnote

Rez. in: Philosophisch-ethische Rezensionen vom 09.11.2019 (Jürgen Czogalla), Unter: https://philosophisch-ethische-rezensionen.de/rezension/Goedert1.html. In: B.I.T. online 23(2020) H.3, S.345-347 (W. Sühl-Strohmenger) [Unter: https%3A%2F%2Fwww.b-i-t-online.de%2Fheft%2F2020-03-rezensionen.pdf&usg=AOvVaw0iY3f_zNcvEjeZ6inHVnOK]. In: Open Password Nr. 805 vom 14.08.2020 (H.-C. Hobohm) [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzE0MywiOGI3NjZkZmNkZjQ1IiwwLDAsMTMxLDFd].

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Date

22. 7.2000 19:01:22

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Abstract

As part of ongoing investigation of information seeking behaviour of end users in electronic environments, a comparison was made of those users having expertise in a topic area and those with expertise in online searching. Computer scientists and online search specialists conducted assigned searches in a HyperCard database on the topic of hypertext. Both groups of experts were able to conduct successful searches and outperformed a novice control group. Search specialists took slightly less time tahn the domain experts, modified queries by adding terms found in the text, and tended to focus on query formulation. Domain experts focused on the text and used their domain knowledge for further question answering

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Abstract

An exploratory study was conducted of elementary school children searching a full-text electronic encyclopedia on CD-ROM. 28 third and forth graders and 24 sixth graders conducted 2 assigned searches, one open-ended, the other one closed, after 2 demonstration sessions. Keystrokes captured by the computer and observer notes were used to examine user information-seeking strategies from a mental model perspective. Older searchers were more successful in finding required information, and took less time than younger searchers. No differences in total number of moves were found. Analysis of search patterns showed that novices used a heuristic, highly interactive search strategy. Searchers used sentence and phrase queries, indicating unique mental models for this search system. Most searchers accepted system defaults and used the AND connective in formulating queries. Transition matrix analysis showed that younger searchers generally favoured query refining moves and older searchers fovoured examining title and text moves. Suggestions for system designers were made and future research questions were identified

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Source

Politische Meinung. 381(2001) Nr.1, S.65-74 [https%3A%2F%2Fwww.dgfe.de%2Ffileadmin%2FOrdnerRedakteure%2FSektionen%2FSek02_AEW%2FKWF%2FPublikationen_Reihe_1989-2003%2FBand_17%2FBd_17_1994_355-406_A.pdf&usg=AOvVaw2KcbRsHy5UQ9QRIUyuOLNi]

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Source

http%3A%2F%2Fcogprints.org%2F1380%2F1%2FvdM_correlation.pdf&usg=AOvVaw0g7DvZbQPb2U7dYb49b9v_

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Abstract

Purpose - The purpose of this paper is to show that uncertainty may be caused not only by a knowledge gap in the mind of a user with respect to a given subject or topic, but also by the various complexities associated with the information seeking and retrieval (IS&R) process in a digital environment. Design/methodology/approach - Both quantitative and qualitative studies were conducted to collect data from users in the higher education sector regarding whether or not they experienced uncertainty in relation to the IS&R process. Analysis: a correlation analysis was undertaken to establish whether there were any relationships between information-seeking activities and information-seeking problems. Findings - The findings of this research show that uncertainty existed at different stages of the IS&R process amongst users. It was established that uncertainty was caused by a number of information-seeking activities and information-seeking problems, and that such uncertainty could continue over the course of successive search sessions, leading to the proposal of a new model of uncertainty. Research limitations/implications - The proposed model of uncertainty should contribute to a better understanding of the issues related to IS&R in a digital environment. Practical implications - A number of benefits could be realised in systems design from the application of this model in terms of reducing the negative impact of uncertainty, while at the same time helping users to gain from the positive aspects of uncertainty in IS&R.
Originality/value - The general consensus is that uncertainty is a mental state of users reflecting a gap in knowledge which triggers an IS&R process, and that the gap is reduced as relevant information is found, and thus that the uncertainty disappears as the search process concludes. However, in the present study it is argued that some form of uncertainty is always associated with some part of the IS&R process and that it also fluctuates throughout the IS&R process. Users may therefore feel uncertain at any stage of the IS&R process and this may be related to: the initial information need and expression of that need, the search process itself, including identification of relevant systems, services and resources; and the assessment of, and reaction to, the results produced by the search process. Uncertainty may be unresolved, or even increase, as the user progresses, often iteratively, through the IS&R process and may remain even after its completion, resulting in what may be called a persistent uncertainty. In other words, this research hypothesises that, in addition to the uncertainty that triggers the information search process (Wilson et al., 2000), users suffer from varying degrees of uncertainty at every stage of the information search and retrieval process, and that in turn, triggers different information-seeking behaviours.

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Date

17. 7.1996 9:33:22
22. 7.2000 19:05:41

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Abstract

In the Web, making judgments of information quality and authority is a difficult task for most users because overall, there is no quality control mechanism. This study examines the problem of the judgment of information quality and cognitive authority by observing people's searching behavior in the Web. Its purpose is to understand the various factors that influence people's judgment of quality and authority in the Web, and the effects of those judgments on selection behaviors. Fifteen scholars from diverse disciplines participated, and data were collected combining verbal protocols during the searches, search logs, and postsearch interviews. It was found that the subjects made two distinct kinds of judgment: predictive judgment, and evaluative judgment. The factors influencing each judgment of quality and authority were identified in terms of characteristics of information objects, characteristics of sources, knowledge, situation, ranking in search output, and general assumption. Implications for Web design that will effectively support people's judgments of quality and authority are also discussed

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Abstract

New challenges arise for researchers and practitioners as we move away from concentration on the technology of searching, and turn our attention to using information for problem solving and creativity in the workplace and daily living. This paper explores links between information behavior, information literacy and the impact of information, drawing on the author's research into the user's perspective of information seeking and use and the model of the Information Search Process (ISP). The ISP model describes thoughts, actions and feelings in six stages of interacting with information to construct meaning. Central to the ISP model is the finding that information commonly increases uncertainty in the early stages of the search process. Increased uncertainty creates a zone of intervention for intermediaries and system designers that support users in their quest for seeking meaning from information. Innovative approaches to interaction between people and information are needed to bridge the divide between information behavior, information literacy and impact of information in order to address issues of the twenty-first century.

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Source

Ratio. 22(1980), S.155-164

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Date

13. 7.2008 19:22:28

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Abstract

It is argued that the current generation of online catalogues do not meet basic user expectations about how to search for information. After a brief examination of virtual reality and its associated technology, a new form of online catalogue, the 'virtual reality library' is proposed. Users browse an information space, a computer-controlled set of shelf orderings for items. Its form, workings and design are investigated in detail. The concept of the virtual reality library is then applied to information resources which either have no physical repository or have one which is not accessible to users

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Abstract

Colours, icons, graphics, hypertext links and other multimedia elements are variables that affect information search strategies and information seeking behaviour. These variables are culturally constructed and represented and are subject to individual and community interpretation. Hypothesizes that users in different communities (in intercultural or multicultural context) will interpret differently the meanings of the multimedia objects on the Internet. Users' interpretations of multimedia objects may differ from the intentions of the designers. A study in this area is being undertaken

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Footnote

Article included in a special issue devoted to the theme 'Knowledge and policy: a search for new ideas'