Search (103 results, page 2 of 6)

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Abstract

Film, videotape and multimedia archive systems must address the issues of editing, authoring and searching at the media (i.e. tape) or sub media (i.e. scene) level in addition to the traditional inventory management capabilities associated with the physical media. This paper describes a prototype of a database design for the storage, search and retrieval of multimedia and its related information. It also provides a process by which legacy data can be imported to this schema. The Continuous Media Index, or Comix system is the name of the prototype. An implementation of such a digital library solution incorporates multimedia objects, hierarchical relationships and timecode in addition to traditional attribute data. Present video and multimedia archive systems are easily migrated to this architecture. Comix was implemented for a videotape archiving system. It was written for, and implemented using IBM Digital Library version 1.0. A derivative of Comix is currently in development for customer specific applications. Principles of the Comix design as well as the importation methods are not specific to the underlying systems used.

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Abstract

The term information design is being offered in this volume as a disignator of a new area of activity. Part of the logic inherent in the presentation is the assumption that as a species we face altered circumstances which demand this new practice

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Abstract

Current user interfaces for textual database searching leave much to be desired: individually, they are often confusing, and as a group, they are seriously inconsistent. We propose a four- phase framework for user-interface design: the framework provides common structure and terminology for searching while preserving the distinct features of individual collections and search mechanisms. Users will benefit from faster learning, increased comprehension, and better control, leading to more effective searches and higher satisfaction.

Type

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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

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 is the second part of two articles about reference linking in hybrid digital libraries. The first part, Frameworks for Linking described the current state-of-the-art and contrasted various approaches to the problem. It identified static and dynamic linking solutions, as well as open and closed linking frameworks. It also included an extensive bibliography. The second part describes our work at the University of Ghent to address these issues. SFX is a generic linking system that we have developed for our own needs, but its underlying concepts can be applied in a wide range of digital libraries. This is a description of the approach to the creation of extended services in a hybrid library environment that has been taken by the Library Automation team at the University of Ghent. The ongoing research has been grouped under the working title Special Effects (SFX). In order to explain the SFX-concepts in a comprehensive way, the discussion will start with a brief description of pre-SFX experiments. Thereafter, the basics of the SFX-approach are explained briefly, in combination with concrete implementation choices taken for the Elektron SFX-linking experiment. Elektron was the name of a modest digital library collaboration between the Universities of Ghent, Louvain and Antwerp.

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Abstract

RDF - the Resource Description Framework - is a foundation for processing metadata; it provides interoperability between applications that exchange machine-understandable information on the Web. RDF emphasizes facilities to enable automated processing of Web resources. RDF metadata can be used in a variety of application areas; for example: in resource discovery to provide better search engine capabilities; in cataloging for describing the content and content relationships available at a particular Web site, page, or digital library; by intelligent software agents to facilitate knowledge sharing and exchange; in content rating; in describing collections of pages that represent a single logical "document"; for describing intellectual property rights of Web pages, and in many others. RDF with digital signatures will be key to building the "Web of Trust" for electronic commerce, collaboration, and other applications. Metadata is "data about data" or specifically in the context of RDF "data describing web resources." The distinction between "data" and "metadata" is not an absolute one; it is a distinction created primarily by a particular application. Many times the same resource will be interpreted in both ways simultaneously. RDF encourages this view by using XML as the encoding syntax for the metadata. The resources being described by RDF are, in general, anything that can be named via a URI. The broad goal of RDF is to define a mechanism for describing resources that makes no assumptions about a particular application domain, nor defines the semantics of any application domain. The definition of the mechanism should be domain neutral, yet the mechanism should be suitable for describing information about any domain. This document introduces a model for representing RDF metadata and one syntax for expressing and transporting this metadata in a manner that maximizes the interoperability of independently developed web servers and clients. The syntax described in this document is best considered as a "serialization syntax" for the underlying RDF representation model. The serialization syntax is XML, XML being the W3C's work-in-progress to define a richer Web syntax for a variety of applications. RDF and XML are complementary; there will be alternate ways to represent the same RDF data model, some more suitable for direct human authoring. Future work may lead to including such alternatives in this document.

Content

RDF Data Model At the core of RDF is a model for representing named properties and their values. These properties serve both to represent attributes of resources (and in this sense correspond to usual attribute-value-pairs) and to represent relationships between resources. The RDF data model is a syntax-independent way of representing RDF statements. RDF statements that are syntactically very different could mean the same thing. This concept of equivalence in meaning is very important when performing queries, aggregation and a number of other tasks at which RDF is aimed. The equivalence is defined in a clean machine understandable way. Two pieces of RDF are equivalent if and only if their corresponding data model representations are the same. Table of contents 1. Introduction 2. RDF Data Model 3. RDF Grammar 4. Signed RDF 5. Examples 6. Appendix A: Brief Explanation of XML Namespaces

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Abstract

This working paper describes the creation of a test database to carry out the automatic classification tasks of the DESIRE II work package D3.6a on. It is an improved version of NetLab's existing "All" Engineering database created after a comparative study of the outcome of two different approaches to collecting the documents. These two methods were selected from seven different general methodologies to build robot-generated subject indices, presented in this paper. We found a surprisingly low overlap between the Engineering link collections we used as seed pages for the robot and subsequently an even more surprisingly low overlap between the resources collected by the two different approaches. That inspite of using basically the same services to start the harvesting process from. A intellectual evaluation of the contents of both databases showed almost exactly the same percentage of relevant documents (77%), indicating that the main difference between those aproaches was the coverage of the resulting database.

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Abstract

For more than ten years, the Perseus Project has been developing a digital library in the humanities. Initial work concentrated exclusively on ancient Greek culture, using this domain as a case study for a compact, densely hypertextual library on a single, but interdisciplinary, subject. Since it has achieved its initial goals with the Greek materials, however, Perseus is using the existing library to study the new possibilities (and limitations) of the electronic medium and to serve as the foundation for work in new cultural domains: Perseus has begun coverage of Roman and now Renaissance materials, with plans for expansion into other areas of the humanities as well. Our goal is not only to help traditional scholars conduct their research more effectively but, more importantly, to help humanists use the technology to redefine the relationship between their work and the broader intellectual community.

Type

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Abstract

The object of Information Retrieval is to retrieve all relevant documents for a user query and only those relevant documents. Much research has focused on achieving this objective with little regard for storage overhead or performance. In the paper we evaluate the use of Part of Speech Tagging to improve, the index storage overhead and general speed of the system with only a minimal reduction to precision recall measurements. We tagged 500Mbs of the Los Angeles Times 1990 and 1989 document collection provided by TREC for parts of speech. We then experimented to find the most relevant part of speech to index. We show that 90% of precision recall is achieved with 40% of the document collections terms. We also show that this is a improvement in overhead with only a 1% reduction in precision recall.

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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.

Type

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Abstract

As the name of the article implies this site has a list of 20 good tips and tricks to assist you in the search process. Note: the tips and tricks are .gifs of what appears to be a PowerPoint presentation and thus can take time to download

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Abstract

Provides a table of the results from over 100 questions actually asked at a library reference desk: The summary notes the average number of relevant 'hits' for all investigated search engines are: AltaVista: 9.3; InfoSeek: 8.3; Lycos: 8.1; Magellan: 7.8; Point: 2.1

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Abstract

This article presents our exploration of computer science clustering algorithms as they relate to the Scorpion system. Scorpion is a research project at OCLC that explores the indexing and cataloging of electronic resources. For a more complete description of the Scorpion, please visit the Scorpion Web site at <http://purl.oclc.org/scorpion>

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Abstract

Scorpion is a research project at OCLC that builds tools for automatic subject assignment by combining library science and information retrieval techniques. A thesis of Scorpion is that the Dewey Decimal Classification (Dewey) can be used to perform automatic subject assignment for electronic items.

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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.
We are currently experimenting with newsgroups as collections. We have built an initial prototype which automatically classifies and summarizes newsgroups within the LCC. (The prototype can be tested below, and more details may be found at http://pharos.alexandria.ucsb.edu/). The prototype uses electronic library catalog records as a `training set' and Latent Semantic Indexing (LSI) for IR. We use the training set to build a rich set of classification terminology, and associate these terms with the relevant categories in the LCC. This association between terms and classification categories allows us to relate users' queries to nodes in the LCC so that users can select appropriate query categories. Newsgroups are similarly associated with classification categories. Pharos then matches the categories selected by users to relevant newsgroups. In principle, this approach allows users to exclude newsgroups that might have been selected based on an unintended meaning of a query term, and to include newsgroups with relevant content even though the exact query terms may not have been used. This work is extensible to other types of classification, including geographical, temporal, and image feature. Before discussing the methodology of the collection summarization and selection, we first present an online demonstration below. The demonstration is not intended to be a complete end-user interface. Rather, it is intended merely to offer a view of the process to suggest the "look and feel" of the prototype. The demo works as follows. First supply it with a few keywords of interest. The system will then use those terms to try to return to you the most relevant subject categories within the LCC. Assuming that the system recognizes any of your terms (it has over 400,000 terms indexed), it will give you a list of 15 LCC categories sorted by relevancy ranking. From there, you have two choices. The first choice, by clicking on the "News" links, is to get a list of newsgroups which the system has identified as relevant to the LCC category you select. The other choice, by clicking on the LCC ID links, is to enter the LCC hierarchy starting at the category of your choice and navigate the tree until you locate the best category for your query. From there, again, you can get a list of newsgroups by clicking on the "News" links. After having shown this demonstration to many people, we would like to suggest that you first give it easier examples before trying to break it. For example, "prostate cancer" (discussed below), "remote sensing", "investment banking", and "gershwin" all work reasonably well.

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Abstract

Lists around 4.000 titles, it is actually produced by Resource International Publishing, Inc., with a wrapper from Walnut Creek CDROM; updated quarterly