Search (42 results, page 2 of 3)

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Date

16. 2.1997 16:22:51

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Date

13. 3.1996 21:22:40

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Date

13. 3.1996 21:22:40

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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

Encoded Archival Description (EAD) is an emerging standard used internationally in an increasing number of archives and manuscripts libraries to encode data describing corporate records and personal papers. The individual descriptions are variously called finding aids, guides, handlists, or catalogs. While archival description shares many objectives with bibliographic description, it differs from it in several essential ways. From its inception, EAD was based on SGML, and, with the release of EAD version 1.0 in 1998, it is also compliant with XML. EAD was, and continues to be, developed by the archival community. While development was initiated in the United States, international interest and contribution are increasing. EAD is currently administered and maintained jointly by the Society of American Archivists and the United States Library of Congress. Developers are currently exploring ways to internationalize the administration and maintenance of EAD to reflect and represent the expanding base of users.

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Abstract

Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word-word and passage-word lexical priming data; and as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.

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Abstract

Here is an interactive introduction to neural nets and how to apply them that is easy to understand and use. Neural nets are information processing systems that mimic the basic structure of the human brain. They learn by adjusting the interaction of their individual components (neurons). A neural net can learn from patterns of information supplied as input to generate useful output that can serve as a basis for decision making. Numerous multimedia and interactive components give the learning program an almost game-like feel as it takes the learner from the basics to the use of neural nets for real projects

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Abstract

Information retrieval over the Internet increasingly requires the filtering of thousands of heterogeneous information sources. Important sources of information include not only traditional databases with structured data and queries, but also increasing numbers of non-traditional, semi- or unstructured collections such as Web sites, FTP archives, etc. As the number and variability of sources increases, new ways of automatically summarizing, discovering, and selecting collections relevant to a user's query are needed. One such method involves the use of classification schemes, such as the Library of Congress Classification (LCC), within which a collection may be represented based on its content, irrespective of the structure of the actual data or documents. For such a system to be useful in a large-scale distributed environment, it must be easy to use for both collection managers and users. As a result, it must be possible to classify documents automatically within a classification scheme. Furthermore, there must be a straightforward and intuitive interface with which the user may use the scheme to assist in information retrieval (IR). Our work with the Alexandria Digital Library (ADL) Project focuses on geo-referenced information, whether text, maps, aerial photographs, or satellite images. As a result, we have emphasized techniques which work with both text and non-text, such as combined textual and graphical queries, multi-dimensional indexing, and IR methods which are not solely dependent on words or phrases. Part of this work involves locating relevant online sources of information. In particular, we have designed and are currently testing aspects of an architecture, Pharos, which we believe will scale up to 1.000.000 heterogeneous sources. Pharos accommodates heterogeneity in content and format, both among multiple sources as well as within a single source. That is, we consider sources to include Web sites, FTP archives, newsgroups, and full digital libraries; all of these systems can include a wide variety of content and multimedia data formats. Pharos is based on the use of hierarchical classification schemes. These include not only well-known 'subject' (or 'concept') based schemes such as the Dewey Decimal System and the LCC, but also, for example, geographic classifications, which might be constructed as layers of smaller and smaller hierarchical longitude/latitude boxes. Pharos is designed to work with sophisticated queries which utilize subjects, geographical locations, temporal specifications, and other types of information domains. The Pharos architecture requires that hierarchically structured collection metadata be extracted so that it can be partitioned in such a way as to greatly enhance scalability. Automated classification is important to Pharos because it allows information sources to extract the requisite collection metadata automatically that must be distributed.

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Abstract

In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want

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Abstract

This technical note describes straightforward techniques for document indexing and retrieval that have been solidly established through extensive testing and are easy to apply. They are useful for many different types of text material, are viable for very large files, and have the advantage that they do not require special skills or training for searching, but are easy for end users. The document and text retrieval methods described here have a sound theoretical basis, are well established by extensive testing, and the ideas involved are now implemented in some commercial retrieval systems. Testing in the last few years has, in particular, shown that the methods presented here work very well with full texts, not only title and abstracts, and with large files of texts containing three quarters of a million documents. These tests, the TREC Tests (see Harman 1993 - 1997; IP&M 1995), have been rigorous comparative evaluations involving many different approaches to information retrieval. These techniques depend an the use of simple terms for indexing both request and document texts; an term weighting exploiting statistical information about term occurrences; an scoring for request-document matching, using these weights, to obtain a ranked search output; and an relevance feedback to modify request weights or term sets in iterative searching. The normal implementation is via an inverted file organisation using a term list with linked document identifiers, plus counting data, and pointers to the actual texts. The user's request can be a word list, phrases, sentences or extended text.

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Abstract

The Dublin Core metadata community and the INDECS/DOI community of authors, rights holders, and publishers are seeking common ground in the expression of metadata for information resources. Recent meetings at the 6th Dublin Core Workshop in Washington DC sketched out common models for semantics (informed by the requirements articulated in the IFLA Functional Requirements for the Bibliographic Record) and conventions for knowledge representation (based on the Resource Description Framework under development by the W3C). Further development of detailed requirements is planned by both communities in the coming months with the aim of fully representing the metadata needs of each. An open "Schema Harmonization" working group has been established to identify a common framework to support interoperability among these communities. The present document represents a starting point identifying historical developments and common requirements of these perspectives on metadata and charts a path for harmonizing their respective conceptual models. It is hoped that collaboration over the coming year will result in agreed semantic and syntactic conventions that will support a high degree of interoperability among these communities, ideally expressed in a single data model and using common, standard tools.

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Footnote

Rez. in: Cataloging and classification quarterly 19(1994) no.1, S.134-137 (M. Carpenter). - Inzwischen existiert auch eine Windows-Version: 'Electronic Dewey for Windows', vgl. Knowledge organization 22(1995) no.1, S.17

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Date

22. 7.2000 18:45:51

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Date

7. 5.2000 10:38:22

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Date

22. 1.2016 17:30:31

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Abstract

We are rapidly constructing an extensive network infrastructure for moving information across national boundaries, but much remains to be done before linguistic barriers can be surmounted as effectively as geographic ones. Users seeking information from a digital library could benefit from the ability to query large collections once using a single language, even when more than one language is present in the collection. If the information they locate is not available in a language that they can read, some form of translation will be needed. At present, multilingual thesauri such as EUROVOC help to address this challenge by facilitating controlled vocabulary search using terms from several languages, and services such as INSPEC produce English abstracts for documents in other languages. On the other hand, support for free text searching across languages is not yet widely deployed, and fully automatic machine translation is presently neither sufficiently fast nor sufficiently accurate to adequately support interactive cross-language information seeking. An active and rapidly growing research community has coalesced around these and other related issues, applying techniques drawn from several fields - notably information retrieval and natural language processing - to provide access to large multilingual collections.

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Abstract

Over the past few months the International DOI Foundation (IDF) has produced a number of discussion papers and other materials about the Digital Object Identifier (DOIsm) initiative. They are all available at the DOI web site, including a brief summary of the DOI origins and purpose. The aim of the present paper is to update those papers, reflecting recent progress, and to provide a summary of the current position and context of the DOI. Although much of the material presented here is the result of a consensus by the organisations forming the International DOI Foundation, some of the points discuss work in progress. The paper describes the origin of the DOI as a persistent identifier for managing copyrighted materials and its development under the non-profit International DOI Foundation into a system providing identifiers of intellectual property with a framework for open applications to be built using them. Persistent identification implementations consistent with URN specifications have up to now been hindered by lack of widespread availability of resolution mechanisms, content typology consensus, and sufficiently flexible infrastructure; DOI attempts to overcome these obstacles. Resolution of the DOI uses the Handle System®, which offers the necessary functionality for open applications. The aim of the International DOI Foundation is to promote widespread applications of the DOI, which it is doing by pioneering some early implementations and by providing an extensible framework to ensure interoperability of future DOI uses. Applications of the DOI will require an interoperable scheme of declared metadata with each DOI; the basis of the DOI metadata scheme is a minimal "kernel" of elements supplemented by additional application-specific elements, under an umbrella data model (derived from the INDECS analysis) that promotes convergence of different application metadata sets. The IDF intends to require declaration of only a minimal set of metadata, sufficient to enable unambiguous look-up of a DOI, but this must be capable of extension by others to create open applications.

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Abstract

Since their inception in the early 1960s the strength and unique aspect of the ISI citation indexes has been their ability to illustrate the conceptual relationships between scholarly documents. When authors create reference lists for their papers, they make explicit links between their own, current work and the prior work of others. The exact nature of these links may not be expressed in the references themselves, and the motivation behind them may vary (this has been the subject of much discussion over the years), but the links embodied in references do exist. Over the past 30+ years, technology has allowed ISI to make the presentation of citation searching increasingly accessible to users of our products. Citation searching and link tracking moved from being rather cumbersome in print, to being direct and efficient (albeit non-intuitive) online, to being somewhat more user-friendly in CD format. But it is the confluence of the hypertext link and development of Web browsers that has enabled us to present to users a new form of citation product -- the Web of Science -- that is intuitive and makes citation indexing conceptually accessible. A cited reference search begins with a known, important (or at least relevant) document used as the search term. The search allows one to identify subsequent articles that have cited that document. This feature adds the dimension of prospective searching to the usual retrospective searching that all bibliographic indexes provide. Citation indexing is a prime example of a concept before its time - important enough to be used in the meantime by those sufficiently motivated, but just waiting for the right technology to come along to expand its use. While it was possible to follow citation links in earlier citation index formats, this required a level of effort on the part of users that was often just too much to ask of the casual user. In the citation indexes as presented in the Web of Science, the relationship between citing and cited documents is evident to users, and a click of the mouse is all it takes to follow a citation link. Citation connections are established between the published papers being indexed from the 8,000+ journals ISI covers and the items their reference lists contain during the data capture process. It is the standardized capture of each of the references included with these documents that enables us to provide the citation searching feature in all the citation index formats, as well as both internal and external links in the Web of Science.

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Date

22. 6.2002 19:35:09