Search (35 results, page 1 of 2)

  • × year_i:[1990 TO 2000}
  • × theme_ss:"Automatisches Klassifizieren"
  1. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.03 
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    Abstract
    The Wolverhampton Web Library (WWLib) is a WWW search engine that provides access to UK based information. The experimental version developed in 1995, was a success but highlighted the need for a much higher degree of automation. An interesting feature of the experimental WWLib was that it organised information according to DDC. Discusses the advantages of classification and describes the automatic classifier that is being developed in Java as part of the new, fully automated WWLib
    Date
    1. 8.1996 22:08:06
    Footnote
    Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia; vgl. auch: http://www7.scu.edu.au/programme/posters/1846/com1846.htm.
    Type
    a
  2. Dubin, D.: Dimensions and discriminability (1998) 0.03 
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    Abstract
    Visualization interfaces can improve subject access by highlighting the inclusion of document representation components in similarity and discrimination relationships. Within a set of retrieved documents, what kinds of groupings can index terms and subject headings make explicit? The role of controlled vocabulary in classifying search output is examined
    Date
    22. 9.1997 19:16:05
    Imprint
    Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Graduate School of Library and Information Science
    Source
    Visualizing subject access for 21st century information resources: Papers presented at the 1997 Clinic on Library Applications of Data Processing, 2-4 Mar 1997, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign. Ed.: P.A. Cochrane et al
    Type
    a
  3. Ardö, A.; Koch, T.: Automatic classification applied to full-text Internet documents in a robot-generated subject index (1999) 0.01 
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    Imprint
    Hinskey Hill : Learned Information
    Source
    Online information 99: 23rd International Online Information Meeting, Proceedings, London, 7-9 December 1999. Ed.: D. Raitt et al
    Type
    a
  4. Dolin, R.; Agrawal, D.; El Abbadi, A.; Pearlman, J.: Using automated classification for summarizing and selecting heterogeneous information sources (1998) 0.01 
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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) [10], 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).
    Type
    a
  5. Möller, G.: Automatic classification of the World Wide Web using Universal Decimal Classification (1999) 0.01 
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    Imprint
    Hinskey Hill : Learned Information
    Source
    Online information 99: 23rd International Online Information Meeting, Proceedings, London, 7-9 December 1999. Ed.: D. Raitt et al
    Type
    a
  6. Rose, J.R.; Gasteiger, J.: HORACE: an automatic system for the hierarchical classification of chemical reactions (1994) 0.01 
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    Abstract
    Describes an automatic classification system for classifying chemical reactions. A detailed study of the classification of chemical reactions, based on topological and physicochemical features, is followed by an analysis of the hierarchical classification produced by the HORACE algorithm (Hierarchical Organization of Reactions through Attribute and Condition Eduction), which combines both approaches in a synergistic manner. The searching and updating of reaction hierarchies is demonstrated with the hierarchies produced for 2 data sets by the HORACE algorithm. Shows that reaction hierarchies provide an efficient access to reaction information and indicate the main reaction types for a given reaction scheme, define the scope of a reaction type, enable searchers to find unusual reactions, and can help in locating the reactions most relevant for a given problem
    Source
    Journal of chemical information and computer sciences. 34(1994) no.1, S.74-90
    Type
    a
  7. Losee, R.M.; Haas, S.W.: Sublanguage terms : dictionaries, usage, and automatic classification (1995) 0.01 
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    Abstract
    The use of terms from natural and social science titles and abstracts is studied from the perspective of sublanguages and their specialized dictionaries. Explores different notions of sublanguage distinctiveness. Object methods for separating hard and soft sciences are suggested based on measures of sublanguage use, dictionary characteristics, and sublanguage distinctiveness. Abstracts were automatically classified with a high degree of accuracy by using a formula that condsiders the degree of uniqueness of terms in each sublanguage. This may prove useful for text filtering of information retrieval systems
    Source
    Journal of the American Society for Information Science. 46(1995) no.7, S.519-529
    Type
    a
  8. May, A.D.: Automatic classification of e-mail messages by message type (1997) 0.01 
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    Abstract
    This article describes a system that automatically classifies e-mail messages in the HUMANIST electronic discussion group into one of 4 classes: questions, responses, announcement or administartive. A total of 1.372 messages were analyzed. The automatic classification of a message was based on string matching between a message text and predefined string sets for each of the massage types. The system's automated ability to accurately classify a message was compared against manually assigned codes. The Cohen's Kappa of .55 suggested that there was a statistical agreement between the automatic and manually assigned codes
    Source
    Journal of the American Society for Information Science. 48(1997) no.1, S.32-39
    Type
    a
  9. McKiernan, G.: Automated categorisation of Web resources : a profile of selected projects, research, products, and services (1996) 0.01 
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    Source
    New review of information networking. 1996, no.2, S.15-40
    Type
    a
  10. Shafer, K.E.: Evaluating Scorpion results (1998) 0.01 
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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.
  11. Losee, R.M.: Text windows and phrases differing by discipline, location in document, and syntactic structure (1996) 0.01 
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    Abstract
    Knowledge of window style, content, location, and grammatical structure may be used to classify documents as originating within a particular discipline or may be used to place a document on a theory vs. practice spectrum. Examines characteristics of phrases and text windows, including their number, location in documents, and grammatical construction, in addition to studying variations in these window characteristics across disciplines. Examines some of the linguistic regularities for individual disciplines, and suggests families of regularities that may provide helpful for the automatic classification of documents, as well as for information retrieval and filtering applications
    Source
    Information processing and management. 32(1996) no.6, S.747-767
    Type
    a
  12. Dolin, R.; Agrawal, D.; El Abbadi, A.; Pearlman, J.: Using automated classification for summarizing and selecting heterogeneous information sources (1998) 0.01 
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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.
    Type
    a
  13. Orwig, R.E.; Chen, H.; Nunamaker, J.F.: ¬A graphical, self-organizing approach to classifying electronic meeting output (1997) 0.01 
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    Abstract
    Describes research in the application of a Kohonen Self-Organizing Map (SOM) to the problem of classification of electronic brainstorming output and an evaluation of the results. Describes an electronic meeting system and describes the classification problem that exists in the group problem solving process. Surveys the literature concerning classification. Describes the application of the Kohonen SOM to the meeting output classification problem. Describes an experiment that evaluated the classification performed by the Kohonen SOM by comparing it with those of a human expert and a Hopfield neural network. Discusses conclusions and directions for future research
    Source
    Journal of the American Society for Information Science. 48(1997) no.2, S.157-170
    Type
    a
  14. Huang, Y.-L.: ¬A theoretic and empirical research of cluster indexing for Mandarine Chinese full text document (1998) 0.01 
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    Abstract
    Since most popular commercialized systems for full text retrieval are designed with full text scaning and Boolean logic query mode, these systems use an oversimplified relationship between the indexing form and the content of document. Reports the use of Singular Value Decomposition (SVD) to develop a Cluster Indexing Model (CIM) based on a Vector Space Model (VSM) in orer to explore the index theory of cluster indexing for chinese full text documents. From a series of experiments, it was found that the indexing performance of CIM is better than traditional VSM, and has almost equivalent effectiveness of the authority control of index terms
    Source
    Bulletin of library and information science. 1998, no.24, S.44-68
    Type
    a
  15. Koch, T.: Experiments with automatic classification of WAIS databases and indexing of WWW : some results from the Nordic WAIS/WWW project (1994) 0.01 
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    Abstract
    The Nordic WAIS/WWW project sponsored by NORDINFO is a joint project between Lund University Library and the National Technological Library of Denmark. It aims to improve the existing networked information discovery and retrieval tools Wide Area Information System (WAIS) and World Wide Web (WWW), and to move towards unifying WWW and WAIS. Details current results focusing on the WAIS side of the project. Describes research into automatic indexing and classification of WAIS sources, development of an orientation tool for WAIS, and development of a WAIS index of WWW resources
    Type
    a
  16. Cheng, P.T.K.; Wu, A.K.W.: ACS: an automatic classification system (1995) 0.01 
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    Abstract
    In this paper, we introduce ACS, an automatic classification system for school libraries. First, various approaches towards automatic classification, namely (i) rule-based, (ii) browse and search, and (iii) partial match, are critically reviewed. The central issues of scheme selection, text analysis and similarity measures are discussed. A novel approach towards detecting book-class similarity with Modified Overlap Coefficient (MOC) is also proposed. Finally, the design and implementation of ACS is presented. The test result of over 80% correctness in automatic classification and a cost reduction of 75% compared to manual classification suggest that ACS is highly adoptable
    Source
    Journal of information science. 21(1995) no.4, S.289-299
    Type
    a
  17. Ruocco, A.S.; Frieder, O.: Clustering and classification of large document bases in a parallel environment (1997) 0.01 
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    Abstract
    Proposes the use of parallel computing systems to overcome the computationally intense clustering process. Examines 2 operations: clustering a document set and classifying the document set. Uses a subset of the TIPSTER corpus, specifically, articles from the Wall Street Journal. Document set classification was performed without the large storage requirements for ancillary data matrices. The time performance of the parallel systems was an improvement over sequential systems times, and produced the same clustering and classification scheme. Results show near linear speed up in higher threshold clustering applications
    Source
    Journal of the American Society for Information Science. 48(1997) no.10, S.932-943
    Type
    a
  18. Ingwersen, P.; Wormell, I.: Ranganathan in the perspective of advanced information retrieval (1992) 0.01 
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    Abstract
    Examnines Ranganathan's approach to knowledge organisation and its relevance to intellectual accessibility in libraries. Discusses the current and future developments of his methodology and theories in knowledge-based systems. Topics covered include: semi-automatic classification and structure of thesauri; user-intermediary interactions in information retrieval (IR); semantic value-theory and uncertainty principles in IR; and case grammar
    Type
    a
  19. Savic, D.: Automatic classification of office documents : review of available methods and techniques (1995) 0.01 
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    Abstract
    Classification of office documents is one of the administrative functions carried out by almost every organization and institution which sends and receives correspondence. Processing of this increasing amount of information coming and out going mail, in particular its classification, is time consuming and expensive. More and more organizations are seeking a solution for meeting this challenge by designing computer based systems for automatic classification. Examines the present status of available knowledge and methodology which can be used for automatic classification of office documents. Besides a review of classic methods and techniques, the focus id also placed on the application of artificial intelligence
    Type
    a
  20. Mostafa, J.; Quiroga, L.M.; Palakal, M.: Filtering medical documents using automated and human classification methods (1998) 0.01 
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    Abstract
    The goal of this research is to clarify the role of document classification in information filtering. An important function of classification, in managing computational complexity, is described and illustrated in the context of an existing filtering system. A parameter called classification homogeneity is presented for analyzing unsupervised automated classification by employing human classification as a control. 2 significant components of the automated classification approach, vocabulary discovery and classification scheme generation, are described in detail. Results of classification performance revealed considerable variability in the homogeneity of automatically produced classes. Based on the classification performance, different types of interest profiles were created. Subsequently, these profiles were used to perform filtering sessions. The filtering results showed that with increasing homogeneity, filtering performance improves, and, conversely, with decreasing homogeneity, filtering performance degrades
    Source
    Journal of the American Society for Information Science. 49(1998) no.14, S.1304-1318
    Type
    a

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