Search (79 results, page 1 of 4)

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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

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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

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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.

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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

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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

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Source

Online. 22(1998) no.3, S.24-26,28

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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.

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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.

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Abstract

The traditional recall and precision measure is inappropriate when retrieval algorithms that retrieve information from Wide Area Networks are evaluated. The principle reason is that information available in WANs is dynamic and its size os orders of magnitude greater than the size of the usual test collections. To overcome these problems, a new efffectiveness measure has been developed, which we call the 'usefulness measure'

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Abstract

89 articles from a small, Danish left-wing newspaper were indexed by PRECIS and KWIC. The articles cover a wide range of social science subjects. Controlled test searches in both indexes were carried out by 20 students of library science. The results obtained from this small-scale retrieval test were evaluated by a chi-square test. The PRECIS index led to more correct answers and fewer wrong answers than the KWIC index, i.e. it had both better recall and greater precision. Furthermore, the students were more confident in their judgement of the relevance of retrieved articles in the PRECIS index than in the KWIC index; and they generally favoured the PRECIS index in the subjective judgement they were asked to make

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Abstract

The Text REtrieval Conference (TREC) workshop series encourages research in information retrieval from large text applications by providing a large test collection, uniform scoring procedures and a forum for organizations interested in comparing their results. Now in its seventh year, the conference has become the major experimental effort in the field. Participants in the TREC conferences have examined a wide variety of retrieval techniques, including methods using automatic thesauri, sophisticated term weighting, natural language techniques, relevance feedback and advanced pattern matching. The TREC conference series is co-sponsored by the National Institute of Standards and Technology (NIST) and the Information Technology Office of the Defense Advanced Research Projects Agency (DARPA)

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Abstract

This article reports on a comparison of the postcoordinate retrieval effectiveness of two indexing languages: LCSH and PRECIS. The effect of augmenting each with title words was also studies. The database for the study was over 15.000 UK MARC records. Users returned 5.326 relevant judgements for citations retrieved for 61 SDI profiles, representing a wide variety of subjects. Results are reported in terms of precision and relative recall. Pure/applied sciences data and social science data were analyzed separately. Cochran's significance tests for ratios were used to interpret the findings. Recall emerged as the more important measure discriminating the behavior of the two languages. Addition of title words was found to improve recall of both indexing languages significantly. A direct relationship was observed between recall and exhaustivity. For the social sciences searches, recalls from PRECIS alone and from PRECIS with title words were significantly higher than those from LCSH alone and from LCSH with title words, respectively. Corresponding comparisons for the pure/applied sciences searches revealed no significant differences

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Abstract

Purpose The purpose of this paper is to propose a method to have more accurate results in comparing performance of the paired information retrieval (IR) systems with reference to the current method, which is based on the mean effectiveness scores of the systems across a set of identified topics/queries. Design/methodology/approach Based on the proposed approach, instead of the classic method of using a set of topic scores, the documents level scores are considered as the evaluation unit. These document scores are the defined document's weight, which play the role of the mean average precision (MAP) score of the systems as a significance test's statics. The experiments were conducted using the TREC 9 Web track collection. Findings The p-values generated through the two types of significance tests, namely the Student's t-test and Mann-Whitney show that by using the document level scores as an evaluation unit, the difference between IR systems is more significant compared with utilizing topic scores. Originality/value Utilizing a suitable test collection is a primary prerequisite for IR systems comparative evaluation. However, in addition to reusable test collections, having an accurate statistical testing is a necessity for these evaluations. The findings of this study will assist IR researchers to evaluate their retrieval systems and algorithms more accurately.

Date

20. 1.2015 18:30:22

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Abstract

The purpose of this article is to bring attention to the problem of variations in relevance assessments and the effects that these may have on measures of retrieval effectiveness. Through an analytical review of the literature, I show that despite known wide variations in relevance assessments in experimental test collections, their effects on the measurement of retrieval performance are almost completely unstudied. I will further argue that what we know about tha many variables that have been found to affect relevance assessments under experimental conditions, as well as our new understanding of psychological, situational, user-based relevance, point to a single conclusion. We can no longer rest the evaluation of information retrieval systems on the assumption that such variations do not significantly affect the measurement of information retrieval performance. A series of thourough, rigorous, and extensive tests is needed, of precisely how, and under what conditions, variations in relevance assessments do, and do not, affect measures of retrieval performance. We need to develop approaches to evaluation that are sensitive to these variations and to human factors and individual differences more generally. Our approaches to evaluation must reflect the real world of real users

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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

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Abstract

In order to compare the value of subject descriptors and title keywords as entries to subject searches, two studies were carried out. Both studies concentrated on monographs in the humanities and social sciences, held by the online public access catalogue of the National Library of the Netherlands. In the first study, a comparison was made by subject librarians between the subject descriptors and the title keywords of 475 records. They could express their opinion on a scale from 1 (descriptor is exactly or almost the same as word in title) to 7 (descriptor does not appear in title at all). It was concluded that 37 per cent of the records are considerably enhanced by a subject descriptor, and 49 per cent slightly or considerably enhanced. In the second study, subject librarians performed subject searches using title keywords and subject descriptors on the same topic. The relative recall amounted to 48 per cent and 86 per cent respectively. Failure analysis revealed the reasons why so many records that were found by subject descriptors were not found by title keywords. First, although completely meaningless titles hardly ever appear, the title of a publication does not always offer sufficient clues for title keyword searching. In those cases, descriptors may enhance the record of a publication. A second and even more important task of subject descriptors is controlling the vocabulary. Many relevant titles cannot be retrieved by title keyword searching because of the wide diversity of ways of expressing a topic. Descriptors take away the burden of vocabulary control from the user.

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Abstract

Information Retrieval (IR) develops complex systems, constituted of several components, which aim at returning and optimally ranking the most relevant documents in response to user queries. In this context, experimental evaluation plays a central role, since it allows for measuring IR systems effectiveness, increasing the understanding of their functioning, and better directing the efforts for improving them. Current evaluation methodologies are limited by two major factors: (i) IR systems are evaluated as "black boxes", since it is not possible to decompose the contributions of the different components, e.g., stop lists, stemmers, and IR models; (ii) given that it is not possible to predict the effectiveness of an IR system, both academia and industry need to explore huge numbers of systems, originated by large combinatorial compositions of their components, to understand how they perform and how these components interact together. We propose a Combinatorial visuaL Analytics system for Information Retrieval Evaluation (CLAIRE) which allows for exploring and making sense of the performances of a large amount of IR systems, in order to quickly and intuitively grasp which system configurations are preferred, what are the contributions of the different components and how these components interact together. The CLAIRE system is then validated against use cases based on several test collections using a wide set of systems, generated by a combinatorial composition of several off-the-shelf components, representing the most common denominator almost always present in English IR systems. In particular, we validate the findings enabled by CLAIRE with respect to consolidated deep statistical analyses and we show that the CLAIRE system allows the generation of new insights, which were not detectable with traditional approaches.

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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