Search (13197 results, page 2 of 660)

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Abstract

Considers two kinds of queries that may be applied to a database. The first is a query written by a searcher to express an information need. The second is a request for documents most similar to a document already judge relevant by the searcher. Examines the effectiveness of these two procedures and shows that in important cases the latter query types is more effective than the former. This provides a new view of the cluster hypothesis and a justification for document neighbouring procedures. If all the documents in a database have readily available precomputed nearest neighbours, a new search algorithm, called parallel neighbourhood searching. Shows that this feedback-based method provides significant improvement in recall over traditional linear searching methods, and appears superior to traditional feedback methods in overall performance

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Abstract

With the increased use of local area networks, CD-ROMs and the Internet, an enormous amount of traditional material is becoming available. Quality issues are therefore becoming even more vital. Describes a methodology being evaluated by The Centre for Information Quality (CIQM) whereby databases can be quantitatively labelled by their producers, so that users can judge how much reliance can be place on them. At the same time, each label bacomes a database specific standard to which its information provider must adhere. This may be a route to responsible information supply

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Abstract

Reports on one area of research in an Electronic Libraries Programme (eLib) MODELS (MOving to Distributed Environments for Library Services) supporting study in 3 investigative areas: examination of current database producers' guidelines for their abstract writers; a brief survey of abstracts in some traditional online databases; and a detailed survey of abstracts from 3 types of electronic database (print sourced online databases, Internet subject trees or directories, and Internet gateways). Examination of database producers' guidelines, reported here, gave a clear view of the intentions behind professionally produced traditional (printed index based) database abstracts and provided a benchmark against which to judge the conclusions of the larger investigations into abstract style, readability and content

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Abstract

This paper reports the design of a Chinese test collection with multilingual queries and the application of this test collection to evaluate information retrieval Systems. The effective indexing units, IR models, translation techniques, and query expansion for Chinese text retrieval are identified. The collaboration of East Asian countries for construction of test collections for cross-language multilingual text retrieval is also discussed in this paper. As well, a tool is designed to help assessors judge relevante and gather the events of relevante judgment. The log file created by this tool will be used to analyze the behaviors of assessors in the future.

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Abstract

OFTEN LIBRARIES TRY TO ASSESS DIGITAL LIBRARY SERVICE for their user populations in comprehensive terms that judge its overall success or failure. This article's key assumption is that the people involved must be understood before services can be assessed, especially if evaluators and developers intend to improve a digital library product. Its argument is simply that anthropology can provide the initial understanding, the intellectual basis, on which informed choices about sample population, survey design, or focus group selection can reasonably be made. As an example, this article analyzes the National Gallery of the Spoken Word (NGSW). It includes brief descriptions of nine NGSW micro-cultures and three pairs of dichotomies within these micro-cultures.

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Abstract

State of the art review of the criteria used to judge and evaluate the quality of databases, including: content, ease of use, accessibility, customer support, documentation, and value to cost ratio. Concludes that the principle factor governing quality is content, defined by the scope and the coverage of the database and its currency, accuracy, consistency and completeness. Scope is determined by its composition and coverage, including time period, number of periodicals and other primary sources, number of articles and geographic and language distribution. Currency is measured by the time lag between publication of the primary source and availability of the corresponding records in the database. Accuracy is governed by the extent to which the records are free from errors of all types. Consistency depends on the extent to which records within the database follow the same rules. Completeness is measured by the consistency with which applicable data elements are assigned to all the records in the database. Reviews the major contributions to the literature in the field and summarizes the background of milestone studies

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Abstract

In this report, we investigate how retrieving information can be improved through task-related indexing of documents based an ontologies. Different index types, varying from content-based keywords to structured task based indexing ontologies, are compared in an experiment that simulates the task of creating instructional material from a database of source material. To be able to judge the added value of task- and ontology-related indexes, traditional information retrieval performance measures are extended with new measures reflecting the quality of the material produced with the retrieved information. The results of the experiment show that a structured task-based indexing ontology improves the quality of the product created from retrieved material only to some extent, but that it certainly improves the efficiency and effectiveness of search and retrieval and precision of use.

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Abstract

This article describes a collaboratively engineered general-purpose knowledge management (KM) ontology that can be used by practitioners, researchers, and educators. The ontology is formally characterized in terms of nearly one hundred definitions and axioms that evolved from a Delphi-like process involving a diverse panel of over 30 KM practitioners and researchers. The ontology identifies and relates knowledge manipulation activities that an entity (e.g., an organization) can perform to operate an knowledge resources. It introduces a taxonomy for these resources, which indicates classes of knowledge that may be stored, embedded, and/or represented in an entity. It recognizes factors that influence the conduct of KM both within and across KM episodes. The Delphi panelists judge the ontology favorably overall: its ability to unify KM concepts, its comprehensiveness, and utility. Moreover, various implications of the ontology for the KM field are examined as indicators of its utility for practitioners, educators, and researchers.

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Abstract

In this issue Maglaughin and Sonnenwald provided 12 graduate students with searches related to the student's work and asked them to judge the twenty most recent retrieved representations by highlighting passages thought to contribute to relevance, marking out passages detracting from relevance, and providing a relevant, partially relevant or relevant judgement on each. By recorded interview they were asked about how these decisions were made and to describe the three classes of judgement. The union of criteria identified in past studies did not seem to fully capture the information supplied so a new set was produced and coding agreement found to be adequate. Twenty-nine criteria were identified and grouped into six categories based upon the focus of the criterion. Multiple criteria are used for most judgements, and most criteria may have either a positive or negative effect. Content was the most frequently mentioned criterion.

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Abstract

This article explicates the common ground between two currently independent fields of inquiry, namely information arts and information science, and suggests a framework that could unite them as a single field of study. The article defines and clarifies the meaning of information art and presents an axiological framework that could be used to judge the value of works of information art. The axiological framework is applied to examples of works of information art to demonstrate its use. The article argues that both information arts and information science could be studied under a common framework; namely, the domain-analytic or sociocognitive approach. It also is argued that the unification of the two fields could help enhance the meaning and scope of both information science and information arts and therefore be beneficial to both fields.

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Abstract

This article introduces a new task-based evaluation measure called Relevance Prediction that is a more intuitive measure of an individual's performance on a real-world task than interannotator agreement. Relevance Prediction parallels what a user does in the real world task of browsing a set of documents using standard search tools, i.e., the user judges relevance based on a short summary and then that same user - not an independent user - decides whether to open (and judge) the corresponding document. This measure is shown to be a more reliable measure of task performance than LDC Agreement, a current gold-standard based measure used in the summarization evaluation community. Our goal is to provide a stable framework within which developers of new automatic measures may make stronger statistical statements about the effectiveness of their measures in predicting summary usefulness. We demonstrate - as a proof-of-concept methodology for automatic metric developers - that a current automatic evaluation measure has a better correlation with Relevance Prediction than with LDC Agreement and that the significance level for detected differences is higher for the former than for the latter.

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Abstract

The potential of summary personalization is high, because a summary that would be useless to decide the relevance of a document if summarized in a generic manner, may be useful if the right sentences are selected that match the user interest. In this paper we defend the use of a personalized summarization facility to maximize the density of relevance of selections sent by a personalized information system to a given user. The personalization is applied to the digital newspaper domain and it used a user-model that stores long and short term interests using four reference systems: sections, categories, keywords and feedback terms. On the other side, it is crucial to measure how much information is lost during the summarization process, and how this information loss may affect the ability of the user to judge the relevance of a given document. The results obtained in two personalization systems show that personalized summaries perform better than generic and generic-personalized summaries in terms of identifying documents that satisfy user preferences. We also considered a user-centred direct evaluation that showed a high level of user satisfaction with the summaries.

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Abstract

This paper presents a study of relevance feedback in a cross-language information retrieval environment. We have performed an experiment in which Portuguese speakers are asked to judge the relevance of English documents; documents hand-translated to Portuguese and documents automatically translated to Portuguese. The goals of the experiment were to answer two questions (i) how well can native Portuguese searchers recognise relevant documents written in English, compared to documents that are hand translated and automatically translated to Portuguese; and (ii) what is the impact of misjudged documents on the performance improvement that can be achieved by relevance feedback. Surprisingly, the results show that machine translation is as effective as hand translation in aiding users to assess relevance in the experiment. In addition, the impact of misjudged documents on the performance of RF is overall just moderate, and varies greatly for different query topics.

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Abstract

Since millions seek health information online, it is vital for this information to be comprehensible. Most studies use readability formulas, which ignore vocabulary, and conclude that online health information is too difficult. We developed a vocabularly-based, naïve Bayes classifier to distinguish between three difficulty levels in text. It proved 98% accurate in a 250-document evaluation. We compared our classifier with readability formulas for 90 new documents with different origins and asked representative human evaluators, an expert and a consumer, to judge each document. Average readability grade levels for educational and commercial pages was 10th grade or higher, too difficult according to current literature. In contrast, the classifier showed that 70-90% of these pages were written at an intermediate, appropriate level indicating that vocabulary usage is frequently appropriate in text considered too difficult by readability formula evaluations. The expert considered the pages more difficult for a consumer than the consumer did.

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Abstract

Users intuitively know which documents are relevant when they see them. Formal relevance assessment, however, is a complex issue. In this entry relevance assessment are described both from a human perspective and a systems perspective. Humans judge relevance in terms of the relation between the documents retrieved and the way in which these documents are understood and used. This is a subjective and personal judgment and is called user relevance. Systems compute a function between the query and the document features that the systems builders believe will cause documents to be ranked by the likelihood that a user will find the documents relevant. This is an objective measurement of relevance in terms of relations between the query and the documents retrieved-this is called system relevance (or sometimes similarity).

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Abstract

Wikipedia is frequently viewed as an inclusive medium. But inclusivity within this online encyclopedia is not a simple matter of just allowing anyone to contribute. In its quest for legitimacy as an encyclopedia, Wikipedia relies on outsiders to judge claims championed by rival editors. In choosing these experts, Wikipedians define the boundaries of acceptable comment on any given subject. Inclusivity then becomes a matter of how the boundaries of expertise are drawn. In this article I examine the nature of these boundaries and the implications they have for inclusivity and credibility as revealed through the talk pages produced and sources used by a particular subset of Wikipedia's creators-those involved in writing articles on the topic of Philippine history.

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Abstract

In the age of mobile commerce, users receive floods of commercial messages. How do users judge the relevance of such information? Is their relevance judgment affected by contextual factors, such as location and time? How do message content and contextual factors affect users' privacy concerns? With a focus on mobile ads, we propose a research model based on theories of relevance judgment and mobile marketing research. We suggest topicality, reliability, and economic value as key content factors and location and time as key contextual factors. We found mobile relevance judgment is affected mainly by content factors, whereas privacy concerns are affected by both content and contextual factors. Moreover, topicality and economic value have a synergetic effect that makes a message more relevant. Higher topicality and location precision exacerbate privacy concerns, whereas message reliability alleviates privacy concerns caused by location precision. These findings reveal an interesting intricacy in user relevance judgment and privacy concerns and provide nuanced guidance for the design and delivery of mobile commercial information.

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Abstract

This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT-2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a machine fooling a human judge recedes in this work relative to the question of "how would one prove it?" The original contribution of the work presents a metric and simple grammatical set for understanding the writing mechanics of chatbots in evaluating their readability and statistical clarity, engagement, delivery, overall quality, and plagiarism risks. While Turing's original prose scores at least 14% below the machine-generated output, whether an algorithm displays hints of Turing's true initial thoughts (the "Lovelace 2.0" test) remains unanswerable.

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Content

Enthält die Beiträge: DERVIN, B.: Given a context by any other name: methodological tools for taming the unruly beast; WILSON, T.: Information behaviour: an inter-disciplinary perspective; GLUCK, M.: Making sense of semiotics: privelinging respondents in revealing contextual geographic syntactic and semantic codes; TALJA, S.: Constituing 'information' and 'user' as research objects: a theory of knowledge formations as a alternative to the information man-theory; TUOMININ, K. u. R. SAVOLAINEN: A social constructionist approach to the study of information as discursive action; LECKIE, G.J. u. K.E. PETTIGREW: A general model of the information seeking of professionals: role theory through the back door?; ALLEN, B.: Information needs: a person-in-situation approach; BYSTRÖM, K.: Municipal administrators at work - information needs and seeking (IN&S) in relation to task complexity: a case-study amongst municipals officials; LOUGHRIDGE, B.: Investigating the management information needs of heads of academic departments in universities in the United Kingdom: a critical success factors approach; BARNES, D.M., A.H. SPINK u. D.E. YEATTS: Effective information systems for high-performing self-managed teams; SONNENWALD, D.H. u. L.A. LIEVROUW: Collaboration during the design process: a case study of communication, information behavior, and project performance; ALGON, J.: Classifications of tasks, steps, and information-related behaviors of individuals on project teams; MALMSJÖ, A.: Information seeking behaviour and development of information systems: a contextual view; BARRY, C.: Information-seeking in an advanced IT culture: a case study; KIRK, J.: Managers' use of information: a grounded theory approach; KUHLTHAU, C.C.: The influence of uncertainty on the information seeking behavior of a securities analyst; LIMBERG, L.: Information use for learning purposes; SOLOMON, P.: Information behavior in sense making: a three-year case study of work planning; WANG, P.: Users' information needs at different stages of a research project: a cognitive view; BRUCE, H.: A user oriented view of Internet as information infrastructure; WILLIAMSON, K.: The information needs and information-seeking behavior of older adults: an Australian study; TODD, R.J.: Information utilisation: a cognitive analysis of how girls utilise drug information based on Brookes' Fundamental Equation (K(S) + delta I = K(S + delta S)); JULIEN, H.E.: How career information helps adolescents' decision making; DAVENPORT, E,. M. HIGGINS u. I. SOMERVILLE: The appropriatation of home information systems in Scottish households; ERDELEZ, S.: Information encountering: a conceptual framework for accidental information discovery; HARMON, E.G. u. E.R. BALLESTEROS: Unconscious cognition: the elicitation of deeply embedded information needs; SCHWABE, G.: Citizenship information in Norway, Germany, and from the European Commission: the need and its delivery