Search (95 results, page 1 of 5)

  • × theme_ss:"Retrievalstudien"
  1. Agata, T.: ¬A measure for evaluating search engines on the World Wide Web : retrieval test with ESL (Expected Search Length) (1997) 0.06
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  2. Lazonder, A.W.; Biemans, H.J.A.; Wopereis, I.G.J.H.: Differences between novice and experienced users in searching information on the World Wide Web (2000) 0.04
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    Abstract
    Searching for information on the WWW basically comes down to locating an appropriate Web site and to retrieving relevant information from that site. This study examined the effect of a user's WWW experience on both phases of the search process. 35 students from 2 schools for Dutch pre-university education were observed while performing 3 search tasks. The results indicate that subjects with WWW-experience are more proficient in locating Web sites than are novice WWW-users. The observed differences were ascribed to the experts' superior skills in operating Web search engines. However, on tasks that required subjects to locate information on specific Web sites, the performance of experienced and novice users was equivalent - a result that is in line with hypertext research. Based on these findings, implications for training and supporting students in searching for information on the WWW are identified. Finally, the role of the subjects' level of domain expertise is discussed and directions for future research are proposed
  3. Wu, C.-J.: Experiments on using the Dublin Core to reduce the retrieval error ratio (1998) 0.03
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    Abstract
    In order to test the power of metadata on information retrieval, an experiment was designed and conducted on a group of 7 graduate students using the Dublin Core as the cataloguing metadata. Results show that, on average, the retrieval error rate is only 2.9 per cent for the MES system (http://140.136.85.194), which utilizes the Dublin Core to describe the documents on the World Wide Web, in contrast to 20.7 per cent for the 7 famous search engines including HOTBOT, GAIS, LYCOS, EXCITE, INFOSEEK, YAHOO, and OCTOPUS. The very low error rate indicates that the users can use the information of the Dublin Core to decide whether to retrieve the documents or not
  4. Palmquist, R.A.; Kim, K.-S.: Cognitive style and on-line database search experience as predictors of Web search performance (2000) 0.03
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    Abstract
    This study sought to investigate the effects of cognitive style (field dependent and field independent) and on-line database search experience (novice and experienced) on the WWW search performance of undergraduate college students (n=48). It also attempted to find user factors that could be used to predict search efficiency. search performance, the dependent variable was defined in 2 ways: (1) time required for retrieving a relevant information item, and (2) the number of nodes traversed for retrieving a relevant information item. the search tasks required were carried out on a University Web site, and included a factual task and a topical search task of interest to the participant. Results indicated that while cognitive style (FD/FI) significantly influenced the search performance of novice searchers, the influence was greatly reduced in those searchers who had on-line database search experience. Based on the findings, suggestions for possible changes to the design of the current Web interface and to user training programs are provided
  5. Khan, K.; Locatis, C.: Searching through cyberspace : the effects of link display and link density on information retrieval from hypertext on the World Wide Web (1998) 0.03
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  6. Griesbaum, J.: Evaluierung hybrider Suchsysteme im WWW (2000) 0.03
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    Abstract
    Der Ausgangspunkt dieser Arbeit ist die Suchproblematik im World Wide Web. Suchmaschinen sind einerseits unverzichtbar für erfolgreiches Information Retrieval, andererseits wird ihnen eine mäßige Leistungsfähigkeit vorgeworfen. Das Thema dieser Arbeit ist die Untersuchung der Retrievaleffektivität deutschsprachiger Suchmaschinen. Es soll festgestellt werden, welche Retrievaleffektivität Nutzer derzeit erwarten können. Ein Ansatz, um die Retrievaleffektivität von Suchmaschinen zu erhöhen besteht darin, redaktionell von Menschen erstellte und automatisch generierte Suchergebnisse in einer Trefferliste zu vermengen. Ziel dieser Arbeit ist es, die Retrievaleffektivität solcher hybrider Systeme im Vergleich zu rein roboterbasierten Suchmaschinen zu evaluieren. Zunächst werden hierzu die grundlegenden Problembereiche bei der Evaluation von Retrievalsystemen analysiert. In Anlehnung an die von Tague-Sutcliff vorgeschlagene Methodik wird unter Beachtung der webspezifischen Besonderheiten eine mögliche Vorgehensweise erschlossen. Darauf aufbauend wird das konkrete Setting für die Durchführung der Evaluation erarbeitet und ein Retrievaleffektivitätstest bei den Suchmaschinen Lycos.de, AItaVista.de und QualiGo durchgeführt.
  7. Wood, F.; Ford, N.; Miller, D.; Sobczyk, G.; Duffin, R.: Information skills, searching behaviour and cognitive styles for student-centred learning : a computer-assisted learning approach (1996) 0.03
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    Abstract
    Undergraduates were tested to establish how they searched databases, the effectiveness of their searches and their satisfaction with them. The students' cognitive and learning styles were determined by the Lancaster Approaches to Studying Inventory and Riding's Cognitive Styles Analysis tests. There were significant differences in the searching behaviour and the effectiveness of the searches carried out by students with different learning and cognitive styles. Computer-assisted learning (CAL) packages were developed for three departments. The effectiveness of the packages were evaluated. Significant differences were found in the ways students with different learning styles used the packages. Based on the experience gained, guidelines for the teaching of information skills and the production and use of packages were prepared. About 2/3 of the searches had serious weaknesses, indicating a need for effective training. It appears that choice of searching strategies, search effectiveness and use of CAL packages are all affected by the cognitive and learning styles of the searcher. Therefore, students should be made aware of their own styles and, if appropriate, how to adopt more effective strategies
    Source
    Journal of information science. 22(1996) no.2, S.79-92
    Theme
    Computer Based Training
  8. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.03
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    Abstract
    A study was done to test the effectiveness of retrieval using title word searching. It was based on actual search profiles used in the Mechanized Information Center at Ohio State University, in order ro replicate as closely as possible actual searching conditions. Fewer than 50% of the relevant titles were retrieved by keywords in titles. The low rate of retrieval can be attributes to three sources: titles themselves, user and information specialist ignorance of the subject vocabulary in use, and to general language problems. Across fields it was found that the social sciences had the best retrieval rate, with science having the next best, and arts and humanities the lowest. Ways to enhance and supplement keyword in title searching on the computer and in printed indexes are discussed.
    Date
    14. 3.1996 13:22:21
  9. Dresel, R.; Hörnig, D.; Kaluza, H.; Peter, A.; Roßmann, A.; Sieber, W.: Evaluation deutscher Web-Suchwerkzeuge : Ein vergleichender Retrievaltest (2001) 0.03
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    Abstract
    Die deutschen Suchmaschinen, Abacho, Acoon, Fireball und Lycos sowie die Web-Kataloge Web.de und Yahoo! werden einem Qualitätstest nach relativem Recall, Precision und Availability unterzogen. Die Methoden der Retrievaltests werden vorgestellt. Im Durchschnitt werden bei einem Cut-Off-Wert von 25 ein Recall von rund 22%, eine Precision von knapp 19% und eine Verfügbarkeit von 24% erreicht
  10. Davis, C.H.: From document retrieval to Web browsing : some universal concerns (1997) 0.03
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    Abstract
    Computer based systems can produce enourmous retrieval sets even when good search logic is used. Sometimes this is desirable, more often it is not. Appropriate filters can limit search results, but they represent only a partial solution. Simple ranking techniques are needed that are both effective and easily understood by the humans doing the searching. Optimal search output, whether from a traditional database or the Internet, will result when intuitive interfaces are designed that inspire confidence while making the necessary mathematics transparent. Weighted term searching using powers of 2, a technique proposed early in the history of information retrieval, can be simplifies and used in combination with modern graphics and textual input to achieve these results
  11. MacCall, S.L.; Cleveland, A.D.; Gibson, I.E.: Outline and preliminary evaluation of the classical digital library model (1999) 0.03
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    Abstract
    The growing number of networked information resources and services offers unprecedented opportunities for delivering high quality information to the computer desktop of a wide range of individuals. However, currently there is a reliance on a database retrieval model, in which endusers use keywords to search large collections of automatically indexed resources in order to find needed information. As an alternative to the database retrieval model, this paper outlines the classical digital library model, which is derived from traditional practices of library and information science professionals. These practices include the selection and organization of information resources for local populations of users and the integration of advanced information retrieval tools, such as databases and the Internet into these collections. To evaluate this model, library and information professionals and endusers involved with primary care medicine were asked to respond to a series of questions comparing their experiences with a digital library developed for the primary care population to their experiences with general Internet use. Preliminary results are reported
  12. Sanderson, M.: ¬The Reuters test collection (1996) 0.03
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  13. Kantor, P.; Kim, M.H.; Ibraev, U.; Atasoy, K.: Estimating the number of relevant documents in enormous collections (1999) 0.02
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    Abstract
    In assessing information retrieval systems, it is important to know not only the precision of the retrieved set, but also to compare the number of retrieved relevant items to the total number of relevant items. For large collections, such as the TREC test collections, or the World Wide Web, it is not possible to enumerate the entire set of relevant documents. If the retrieved documents are evaluated, a variant of the statistical "capture-recapture" method can be used to estimate the total number of relevant documents, providing the several retrieval systems used are sufficiently independent. We show that the underlying signal detection model supporting such an analysis can be extended in two ways. First, assuming that there are two distinct performance characteristics (corresponding to the chance of retrieving a relevant, and retrieving a given non-relevant document), we show that if there are three or more independent systems available it is possible to estimate the number of relevant documents without actually having to decide whether each individual document is relevant. We report applications of this 3-system method to the TREC data, leading to the conclusion that the independence assumptions are not satisfied. We then extend the model to a multi-system, multi-problem model, and show that it is possible to include statistical dependencies of all orders in the model, and determine the number of relevant documents for each of the problems in the set. Application to the TREC setting will be presented
  14. Pemberton, J.K.; Ojala, M.; Garman, N.: Head to head : searching the Web versus traditional services (1998) 0.02
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    Source
    Online. 22(1998) no.3, S.24-26,28
  15. ¬The Eleventh Text Retrieval Conference, TREC 2002 (2003) 0.02
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    Abstract
    Proceedings of the llth TREC-conference held in Gaithersburg, Maryland (USA), November 19-22, 2002. Aim of the conference was discussion an retrieval and related information-seeking tasks for large test collection. 93 research groups used different techniques, for information retrieval from the same large database. This procedure makes it possible to compare the results. The tasks are: Cross-language searching, filtering, interactive searching, searching for novelty, question answering, searching for video shots, and Web searching.
  16. Crestani, F.; Rijsbergen, C.J. van: Information retrieval by imaging (1996) 0.02
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  17. Voorhees, E.M.; Harman, D.K.: ¬The Text REtrieval Conference (2005) 0.02
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    Abstract
    Text retrieval technology targets a problem that is all too familiar: finding relevant information in large stores of electronic documents. The problem is an old one, with the first research conference devoted to the subject held in 1958 [11]. Since then the problem has continued to grow as more information is created in electronic form and more people gain electronic access. The advent of the World Wide Web, where anyone can publish so everyone must search, is a graphic illustration of the need for effective retrieval technology. The Text REtrieval Conference (TREC) is a workshop series designed to build the infrastructure necessary for the large-scale evaluation of text retrieval technology, thereby accelerating its transfer into the commercial sector. The series is sponsored by the U.S. National Institute of Standards and Technology (NIST) and the U.S. Department of Defense. At the time of this writing, there have been twelve TREC workshops and preparations for the thirteenth workshop are under way. Participants in the workshops have been drawn from the academic, commercial, and government sectors, and have included representatives from more than twenty different countries. These collective efforts have accomplished a great deal: a variety of large test collections have been built for both traditional ad hoc retrieval and related tasks such as cross-language retrieval, speech retrieval, and question answering; retrieval effectiveness has approximately doubled; and many commercial retrieval systems now contain technology first developed in TREC.
  18. Belkin, N.J.: ¬An overview of results from Rutgers' investigations of interactive information retrieval (1998) 0.02
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    Abstract
    Over the last 4 years, the Information Interaction Laboratory at Rutgers' School of communication, Information and Library Studies has performed a series of investigations concerned with various aspects of people's interactions with advanced information retrieval (IR) systems. We have benn especially concerned with understanding not just what people do, and why, and with what effect, but also with what they would like to do, and how they attempt to accomplish it, and with what difficulties. These investigations have led to some quite interesting conclusions about the nature and structure of people's interactions with information, about support for cooperative human-computer interaction in query reformulation, and about the value of visualization of search results for supporting various forms of interaction with information. In this discussion, I give an overview of the research program and its projects, present representative results from the projects, and discuss some implications of these results for support of subject searching in information retrieval systems
    Date
    22. 9.1997 19:16:05
  19. TREC: experiment and evaluation in information retrieval (2005) 0.02
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    Abstract
    The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.
    Content
    Enthält die Beiträge: 1. The Text REtrieval Conference - Ellen M. Voorhees and Donna K. Harman 2. The TREC Test Collections - Donna K. Harman 3. Retrieval System Evaluation - Chris Buckley and Ellen M. Voorhees 4. The TREC Ad Hoc Experiments - Donna K. Harman 5. Routing and Filtering - Stephen Robertson and Jamie Callan 6. The TREC Interactive Tracks: Putting the User into Search - Susan T. Dumais and Nicholas J. Belkin 7. Beyond English - Donna K. Harman 8. Retrieving Noisy Text - Ellen M. Voorhees and John S. Garofolo 9.The Very Large Collection and Web Tracks - David Hawking and Nick Craswell 10. Question Answering in TREC - Ellen M. Voorhees 11. The University of Massachusetts and a Dozen TRECs - James Allan, W. Bruce Croft and Jamie Callan 12. How Okapi Came to TREC - Stephen Robertson 13. The SMART Project at TREC - Chris Buckley 14. Ten Years of Ad Hoc Retrieval at TREC Using PIRCS - Kui-Lam Kwok 15. MultiText Experiments for TREC - Gordon V. Cormack, Charles L. A. Clarke, Christopher R. Palmer and Thomas R. Lynam 16. A Language-Modeling Approach to TREC - Djoerd Hiemstra and Wessel Kraaij 17. BM Research Activities at TREC - Eric W. Brown, David Carmel, Martin Franz, Abraham Ittycheriah, Tapas Kanungo, Yoelle Maarek, J. Scott McCarley, Robert L. Mack, John M. Prager, John R. Smith, Aya Soffer, Jason Y. Zien and Alan D. Marwick Epilogue: Metareflections on TREC - Karen Sparck Jones
    Footnote
    Rez. in: JASIST 58(2007) no.6, S.910-911 (J.L. Vicedo u. J. Gomez): "The Text REtrieval Conference (TREC) is a yearly workshop hosted by the U.S. government's National Institute of Standards and Technology (NIST) that fosters and supports research in information retrieval as well as speeding the transfer of technology between research labs and industry. Since 1992, TREC has provided the infrastructure necessary for large-scale evaluations of different text retrieval methodologies. TREC impact has been very important and its success has been mainly supported by its continuous adaptation to the emerging information retrieval needs. Not in vain, TREC has built evaluation benchmarks for more than 20 different retrieval problems such as Web retrieval, speech retrieval, or question-answering. The large and intense trajectory of annual TREC conferences has resulted in an immense bulk of documents reflecting the different eval uation and research efforts developed. This situation makes it difficult sometimes to observe clearly how research in information retrieval (IR) has evolved over the course of TREC. TREC: Experiment and Evaluation in Information Retrieval succeeds in organizing and condensing all this research into a manageable volume that describes TREC history and summarizes the main lessons learned. The book is organized into three parts. The first part is devoted to the description of TREC's origin and history, the test collections, and the evaluation methodology developed. The second part describes a selection of the major evaluation exercises (tracks), and the third part contains contributions from research groups that had a large and remarkable participation in TREC. Finally, Karen Spark Jones, one of the main promoters of research in IR, closes the book with an epilogue that analyzes the impact of TREC on this research field.
    LCSH
    Text processing (Computer science) / Congresses
    Subject
    Text processing (Computer science) / Congresses
  20. Bar-Ilan, J.: ¬The Web as an information source on informetrics? : A content analysis (2000) 0.01
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    Abstract
    This article addresses the question of whether the Web can serve as an information source for research. Specifically, it analyzes by way of content analysis the Web pages retrieved by the major search engines on a particular date (June 7, 1998), as a result of the query 'informetrics OR informetric'. In 807 out of the 942 retrieved pages, the search terms were mentioned in the context of information science. Over 70% of the pages contained only indirect information on the topic, in the form of hypertext links and bibliographical references without annotation. The bibliographical references extracted from the Web pages were analyzed, and lists of most productive authors, most cited authors, works, and sources were compiled. The list of reference obtained from the Web was also compared to data retrieved from commercial databases. For most cases, the list of references extracted from the Web outperformed the commercial, bibliographic databases. The results of these comparisons indicate that valuable, freely available data is hidden in the Web waiting to be extracted from the millions of Web pages

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