Search (62 results, page 2 of 4)

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Abstract

Seit 3. Juli 2006 stellt das ZPID eine verbesserte Suchoberfläche für die Recherche in der bibliographischen Psychologie-Datenbank PSYNDEX zur Verfügung. Hauptmerkmal der neuen Version 1.1 des 'ZPID-Retrieval für PSYNDEX' ist die Einbindung von 'PSYNDEX Terms', dem kontrollierten Wortschatz der psychologischen Fachsprache. PSYNDEX Terms basiert auf dem 'Thesaurus of Psychological Index Terms' der American Psychological Association (APA) und enthält im Moment über 5.400 Deskriptoren. Zu jedem Deskriptor werden ggf. Oberbegriffe, Unterbegriffe und verwandte Begriffe angezeigt. Wer die Suchoberfläche nutzt, kann entweder im Thesaurus blättern oder gezielt nach Thesaurusbegriffen suchen. Kommt der eigene frei gewählte Suchbegriff nicht im Thesaurus vor, macht das System selbsttätig Vorschläge für passende Thesaurusbegriffe. DerThesaurus ist komplett zweisprachig (deutsch/englisch) implementiert, sodass er auch als Übersetzungshilfe dient. Weitere Verbesserungen der Suchoberfläche betreffen die Darstellbarkeit in unterschiedlichen Web-Browsern mit dem Ziel der Barrierefreiheit, die Erweiterung der OnlineHilfe mit Beispielen für erfolgreiche Suchstrategien, die Möglichkeit, zu speziellen Themen vertiefte Informationen abzurufen (den Anfang machen psychologische Behandlungsprogramme) und die Bereitstellung eines Export-Filters für EndNote. Zielgruppe des ZPID-Retrieval sind Einzelpersonen, die keinen institutionellen PSYNDEX-Zugang, z.B. am Campus einer Universität, nutzen können. Sie können das kostenpflichtige Retrieval direkt online erwerben und werden binnen weniger Minuten freigeschaltet. Kunden mit existierendem Vertrag kommen automatisch in den Genuss der verbesserten Suchoberfläche.

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Abstract

The Electronic Libraries and Information Highways MITRE Sponsored Research project aims to help searchers working in digital libraries increase their chance of matching the language of authors. Focuses on whether query formulation can be improved through the addition of semantic knowledge that is interactively gathered from a thesaurus that exists in a distributed, interoperating, cooperative environment. A prototype, ELVIS, was built that improves information retrieval through query expansion and is based on publicly available Z39.50 standard thesauri integrated with networked information discovery and retrieval tools

Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Abstract

The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.

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Abstract

There are many advantages for Digital Libraries in indexing with classifications or thesauri, but some current disincentive in the lack of flexible retrieval tools that deal with compound descriptors. This paper discusses a matching function for compound descriptors, or multi-concept subject headings, that does not rely an exact matching but incorporates term expansion via thesaurus semantic relationships to produce ranked results that take account of missing and partially matching terms. The matching function is based an a measure of semantic closeness between terms, which has the potential to help with recall problems. The work reported is part of the ongoing FACET project in collaboration with the National Museum of Science and Industry and its collections database. The architecture of the prototype system and its Interface are outlined. The matching problem for compound descriptors is reviewed and the FACET implementation described. Results are discussed from scenarios using the faceted Getty Art and Architecture Thesaurus. We argue that automatic traversal of thesaurus relationships can augment the user's browsing possibilities. The techniques can be applied both to unstructured multi-concept subject headings and potentially to more syntactically structured strings. The notion of a focus term is used by the matching function to model AAT modified descriptors (noun phrases). The relevance of the approach to precoordinated indexing and matching faceted strings is discussed.

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Abstract

"Thesaurus linguae latinae" - so heißt eine der frühesten Wort-Sammlungen. Seit Alters her beschäftigen sich Menschen mit der qualifizierten Aufbereitung von Information. Noch älter ist sogar das Konzept der Ontologie (wörtlich: die "Lehre vom Sein"), die sich als Disziplin der Philosophie bereits seit Aristoteles (384-322 v. Chr.) mit einer objektivistischen Beschreibung der Wirklichkeit beschäftigt. Ontologien - als Disziplin des modernen Wissensmanagements-sind eine Methode, in möglichst kompakter Form, d.h. unter Verwendung von Konzepten in verschiedenen Meta-Ebenen die reale Welt zu beschreiben. Thesaurus und Ontologie stellen zwei Konzepte dar, die auch heute noch in der Wissenschaft - und in jüngster Zeit mit zunehmender Bedeutung auch in der Wirtschaft - im Bereich des Informationsund Wissensmanagements zum Einsatz kommen. Beide spannen gewissermaßen den konzeptionellen Bogen, an dem sich ein pragmatisches Wissensmanagement heutzutage ausrichtet und sich in Form sogenannter semantischer Netze - auch Wissensnetze genannt - wiederfindet.

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Abstract

From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

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Date

22. 2.2003 17:25:39
22. 2.2003 18:17:40

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Date

30. 3.2001 13:32:22

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Abstract

Knowledge management in digital libraries is a universal problem. Keyword-based searching is applied everywhere no matter whether the resources are indexed databases or full-text Web pages. In keyword matching, the valuable content description and indexing of the metadata, such as the subject descriptors and the classification notations, are merely treated as common keywords to be matched with the user query. Without the support of vocabulary control tools, such as classification systems and thesauri, the intelligent labor of content analysis, description and indexing in metadata production are seriously wasted. New retrieval paradigms are needed to exploit the potential of the metadata resources. Could classification and thesauri, which contain the condensed intelligence of generations of librarians, be used in a digital library to organize the networked information, especially metadata, to facilitate their usability and change the digital library into a knowledge management environment? To examine that question, we designed and implemented a new paradigm that incorporates a classification system, a thesaurus and metadata. The classification and the thesaurus are merged into a concept network, and the metadata are distributed into the nodes of the concept network according to their subjects. The abstract concept node instantiated with the related metadata records becomes a knowledge node. A coherent and consistent knowledge network is thus formed. It is not only a framework for resource organization but also a structure for knowledge navigation, retrieval and learning. We have built an experimental system based on the Chinese Classification and Thesaurus, which is the most comprehensive and authoritative in China, and we have incorporated more than 5000 bibliographic records in the computing domain from the Peking University Library. The result is encouraging. In this article, we review the tools, the architecture and the implementation of our experimental system, which is called Vision.

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Abstract

Structured thesauri encode equivalent, hierarchical, and associative relationships and have been developed as indexing/retrieval tools. Despite the fact that these tools provide a rich semantic network of vocabulary terms, they are seldom employed for automatic query expansion (QE) activities. This article reports on an experiment that examined whether thesaurus terms, related to query in a specified semantic way (as synonyms and partial-synonyms (SYNs), narrower terms (NTs), related terms (RTs), and broader terms (BTs)), could be identified as having a more positive impact on retrieval effectiveness when added to a query through automatic QE. The research found that automatic QE via SYNs and NTs increased relative recall with a decline in precision that was not statistically significant, and that automatic QE via RTs and BTs increased relative recall with a decline in precision that was statistically significant. Recallbased and a precision-based ranking orders for automatic QE via semantically encoded thesauri terminology were identified. Mapping results found between enduser query terms and the ProQuest Controlled Vocabulary (1997) (the thesaurus used in this study) are reported, and future research foci related to the investigation are discussed

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Content

Willkommene Anregung schon am Eingang.- Vertiefung des Wissens während der Ausstellung.- Alles für das Wohlbefinden.- Die Systemstruktur und ihre einzelnen Elemente.- Wovon alles ausgeht.- Den Stoff als Topics und Subtopics strukturieren.- Die Nutshells.- Der Proxy-Text.Der Thesaurus.- Gedankenraumreisen.- Und zurück in die reale Welt.- Weitergehende Produkte.- Das EXPO-Infosystem auf einen Blick.- Register.- Literaturverzeichnis.

Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Abstract

Focuses on the user and human-computer interaction (HCI) aspects of the research based on the Okapi text retrieval system. Describes 3 experiments using different approaches to query expansion, highlighting the relationship between the functionality of a system and different interface designs. These experiments involve both automatic and interactive query expansion, and both character based and GUI (graphical user interface) environments. The effectiveness of the search interaction for query expansion depends on resolving opposing interface and functional aspects, e.g. automatic vs. interactive query expansion, explicit vs. implicit use of a thesaurus, and document vs. query space

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Abstract

Document retrieval is a highly interactive process dealing with large amounts of information. Visual representations can provide both a means for managing the complexity of large information structures and an interface style well suited to interactive manipulation. The system we have designed utilizes visually displayed graphic structures and a direct manipulation interface style to supply an integrated environment for retrieval. A common visually displayed network structure is used for query, document content, and term relations. A query can be modified through direct manipulation of its visual form by incorporating terms from any other information structure the system displays. An associative thesaurus of terms and an inter-document network provide information about a document collection that can complement other retrieval aids. Visualization of these large data structures makes use of fisheye views and overview diagrams to help overcome some of the inherent difficulties of orientation and navigation in large information structures.

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Abstract

Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Date

1. 2.2016 18:25:22

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Date

1. 2.2016 18:25:22

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou