Search (85 results, page 1 of 5)

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Abstract

Anhand eines einfachen Modells wird geprüft, ob der Nutzen den Aufbau einer Spezialsuchmaschine trägt. Zum Vergleich werden fünf große Suchmaschinen herangezogen und deren Ergebnisse bei gleichen Fragestellungen analysiert. Es ergeben sich gravierende Abweichungen sowohl in der Überdeckung der Ergebnismengen als auch im Ranking. Es erscheint also sinnvoll, eine eigene Suchmaschine zu betreiben

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Abstract

Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework

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Abstract

In this paper, we present a novel personalized concept-based search mechanism for the Web of Data based on results categorization. The innovation of the paper comes from combining novel categorization and personalization techniques, and using categorization for providing personalization. In our approach, search results (Linked Open Data resources) are dynamically categorized into Upper Mapping and Binding Exchange Layer (UMBEL) concepts using a novel fuzzy retrieval model. Then, results with the same concepts are grouped together to form categories, which we call conceptlenses. Such categorization enables concept-based browsing of the retrieved results aligned to users' intent or interests. When the user selects a concept lens for exploration, results are immediately personalized. In particular, all concept lenses are personally re-organized according to their similarity to the selected lens. Within the selected concept lens; more relevant results are included using results re-ranking and query expansion, as well as relevant concept lenses are suggested to support results exploration. This allows dynamic adaptation of results to the user's local choices. We also support interactive personalization; when the user clicks on a result, within the interacted lens, relevant lenses and results are included using results re-ranking and query expansion. Extensive evaluations were performed to assess our approach: (i) Performance of our fuzzy-based categorization approach was evaluated on a particular benchmark (~10,000 mappings). The evaluations showed that we can achieve highly acceptable categorization accuracy and perform better than the vector space model. (ii) Personalized search efficacy was assessed using a user study with 32 participants in a tourist domain. The results revealed that our approach performed significantly better than a non-adaptive baseline search. (iii) Dynamic personalization performance was evaluated, which illustrated that our personalization approach is scalable. (iv) Finally, we compared our system with the existing LOD search engines, which showed that our approach is unique.

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Abstract

Brajnik et alia describe their view of an effective retrieval interface, one which coaches the searcher using stored knowledge not only of database structure, but of strategic situations which are likely to occur, such as repeating failed tactics in a low return search, or failing to try relevance feedback techniques. The emphasis is on the system suggesting search strategy improvements by relating them to an analysis of work entered so far and selecting and ranking those found relevant. FIRE is an interface utilizing these techniques. It allows the user to assign documents to useful, topical and trash folders, maintains thesauri files automatically searchable on query terms, and it builds, using user entries and a rule system, a picture of the retrieval situation from which it generates suggestions. Six participants used FIRE in INSPEC20K database searches, two for their own information needs and four needs provided by the authors. Satisfaction was measured in a structured post search interview, behavior by log analysis, and performance by recall and precision in the canned searches. Participants found the suggestions helpful, but insisted they would have taken those approaches without such assistance. Users took the suggestions offered and preferred those demanding the least effort.

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Abstract

This is a propitious time for information science. The WWW has propelled information services into the public eye as never before, and information professionals are sought out in all walks of life to assist people with work, learning and play in the information environment. Classical information retrieval has yielded novel techniques for applying computers to retrieval problems, including WWW search engines. The classical model of retrieval is one of matching queries to documents and ranking these matches. It is apparent, however, that a new model of retrieval is needed as people access large-scale digital libraries of multimedia content and vast collections of unstructured data in the WWW. What is needed are ways to bring human intelligence and attention more actively into the search process. To this end, researchers are beginning to combine the lessons from designing highly interactive user interfaces with the lessons from human information behavior to create new kinds of search systems that depend on continuous human control of the search process. I call this hybrid approach to the challenges of information seeking, human-computer information retrieval (HCIR). Though human-computer information interaction is perhaps a more expansive and appropriate phrase, the HCIR phrase unites two well-known fields/communities of practice and is thus adopted here. HCIR aims to empower people to explore large-scale information bases but demands that people also take responsibility for this control by expending cognitive and physical energy. This paper outlines the basic motivations and concepts of HCIR and presents design goals and challenges that are informed by two ongoing HCIR projects.

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Abstract

Purpose - The purpose of this paper is to determine whether a faceted OPAC interface offers improvements to information discovery in scholarly research. Design/methodology/approach - The 5.2 million records of an entire library catalog were loaded into a faceted navigation interface and an attractive search term suggestion tool. Humanities PhD students at the dissertation level and familiar with this collection were observed while using this interface to continue their research into the literature on their dissertation topic. Findings - From a group of 12 subjects, nine reported finding materials that they had not found in their previous use of the traditional catalog interface. Research limitations/implications - No attempt is made to isolate the effects of relevance ranking on discovery from those of faceted navigation or the search term suggestions. The differences between the circumstances of scholars who did and did not find previously undiscovered materials are not examined. Practical implications - Faceted interface and search term suggestion in a library catalog may enable those scholars who are highly dependent on library materials to find materials that would remain hidden in a traditional library catalog. Originality/value - This article considers whether faceted navigation increases the range of relevant materials that scholars discover, and is of interest to libraries which are considering adding faceted navigation and other features to their catalog interface.

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Abstract

The author describes some of the challenges, decisions, and processes that affected the design and development of the search user interface for Version 2 of the Digital Library for Earth System Education (DLESE; www.dlese.org), released July 29, 2003. The DLESE is a community-led effort funded by the National Science Foundation and is part of the National Science Digital Library (NSDL).

Date

22. 7.2006 17:48:54

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Abstract

The recent explosion of the Internet and the WWW has made digital libraries popular. Easy access to a digital library is provided by commercially available Web browsers, which provide a user-friendly interface. To retrieve documents of interest, the user is provided with a search interface that may only consist of one input field and one push button. Most users type in a single keyword, click the button, and hope for the best. The result of a query using this kind of search interface can consist of a large unordered set of documents, or a ranked list of documents based on the freuqency of the keywords. Both lists can contain articles unrelated to the user's inquiry unless a sophisticated search was performed and the user knows exactly what to look for. More sophisticated algorithms for ranking the search results according to how well they meet the users needs as expressed in the search input may help. However, what is desperately needed are software tools that can analyze the search result and manipulate large hierarchies of data graphically. In this article we describe the design of a language-independent document classification systems being developed to help users of the Florida Center for Library Automation analyze search query results. Easy access through the Web is provided, as well as a graphical user interface to display the classification results. We also describe the use of this system to retrieve and analyze sets of documents from public Web sites

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Date

1. 8.1996 22:08:06
15. 5.1999 14:54:29

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Content

Ausgangspunkt der vorliegenden Arbeit ist die Fragestellung, wie Anwender von Document Retrieval-Systemen bei der Formulierung einer Anfrage unterstützt werden können. Bei der Beantwortung dieser Frage gilt es zunächst, die verschiedenen Modelle des Document Retrieval auf ihre Stärken und Schwächen hin zu untersuchen. Es werden hier drei exemplarische Retrieval-Modelle herausgegriffen, die sich in ihrer Recherchegrundlage und Relevanzbehandlung stark voneinander unterscheiden: das Boolesche, das probabilistische und das vage Retrieval-Modell. Um den Recherchezugang beim Einsatz dieser Retrieval-Modelle anwenderfreundlich zu gestalten, wird auf das Mittel der Visualisierung zurückgegriffen. In ihr wird eine gute Möglichkeit gesehen, mit komplexer Information umzugehen, da sie im Gegensatz zu textbasierten Präsentationsformen der optisch ausgerichteten menschlichen Kognition sehr weit entgegenkommen kann. Jedoch zeigen zahlreiche Beispiele, dass Visualisierung keinesfalls als Allheilmittel gelten kann, sondern im Gegenteil sogar zu einer Komplexitätssteigerung der Materie führen kann. Eine genauere Analyse bereits bestehender Ansätze weist denn auch softwareergonomische Probleme nach und läßt die Neukonzeption einer Visualisierung aus softwareergonomischer Sicht notwendig erscheinen. Neben softwareergonomischen Überlegungen fließen auch Aspekte des Graphik Design in die Konzeption der Visualisierung mit ein. Dies ist insofern ein Novum, als beide Schulen einander bislang weitgehend ignorierten. Mit Hilfe des Graphik Design kann der Visualisierung eine ansprechendere Gestaltung gegeben werden, die eine erhöhte Anwenderakzeptanz bewirkt. Um die Kooperation von Softwareergonomie und Graphik Design auf eine allgemeingültige Basis stellen zu können, wird auch eine theoretische Zusammenführung vorgeschlagen. Auf der Basis dieser Vorüberlegungen wird eine Visualisierung vorgestellt, welche Aspekte der drei Retrieval-Modelle integriert: In ihrer Grundkonzeption ermöglicht sie Boolesche Recherche. In zwei Erweiterungen werden ein probabilistisches Ranking-Verfahren sowie die Möglichkeit der Erweiterung der Ergebnismenge durch vage Methoden zur Verfügung gestellt. Optisch verfolgt die Viz, sualisierung ein minimalistisches Design. Es werden zu eingegebenen Suchkriterien sämtliche möglichen Kombinationen mit der entsprechenden Anzahl der gefundenen Dokumente angezeigt. Die Codierung der Kombinationen erfolgt dabei rein über die Farbgebung, die durch die Farben der enthaltenen Suchkriterien bestimmt wird. Je nachdem, welche Erweiterung verwendet wird, verändert sich die Gestaltung der Visualisierung: Wird das probabilistische Rankigverfahren eingesetzt, so wird die Position der Kombinationen auf dem Bildschirm neu berechnet. Wird vages Retrieval eingesetzt, so erhalten die erweiterten Mengen ein neues graphisches Element. Um die Güte der Visualisierung zu ermitteln, wird sie in einem Nutzertest evaluiert. Es werden klassische Retrieval-Maße wie Recall und Precision ermittelt sowie in einem Fragebogen die Anwenderakzeptanz eruiert. Die Ergebnisse des Tests untermauern die zwei grundlegenden Thesen dieser Arbeit: Visualisierung ist ein sinnvolles Mittel, die Schwierigkeiten der Interaktion mit Document Retrieval-Systemen zu minimieren. Und die Integration von Softwareergonomie und Graphik Design ist nicht nur sowohl theoretisch als auch praktisch möglich, sondern in der Tat auch vorteilhaft

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Date

1. 8.1996 22:08:06

Source

Computer networks and ISDN systems. 29(1997) no.8, S.1327-1342

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Date

22. 2.2003 17:25:39
22. 2.2003 18:16:22

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Date

9. 2.1997 18:44:22

Source

Journal of librarianship and information science. 29(1997) no.3, A.161-162

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Date

22. 3.2008 14:29:25

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Date

22. 2.2003 17:25:39
22. 2.2003 18:13:11

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Source

Program. 26(1992) no.1, S.29-37