Search (29 results, page 1 of 2)

  • × theme_ss:"Automatisches Klassifizieren"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.24
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  2. Guerrero-Bote, V.P.; Moya Anegón, F. de; Herrero Solana, V.: Document organization using Kohonen's algorithm (2002) 0.02
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    Abstract
    The classification of documents from a bibliographic database is a task that is linked to processes of information retrieval based on partial matching. A method is described of vectorizing reference documents from LISA which permits their topological organization using Kohonen's algorithm. As an example a map is generated of 202 documents from LISA, and an analysis is made of the possibilities of this type of neural network with respect to the development of information retrieval systems based on graphical browsing.
  3. Denoyer, L.; Gallinari, P.: Bayesian network model for semi-structured document classification (2004) 0.01
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    Abstract
    Recently, a new community has started to emerge around the development of new information research methods for searching and analyzing semi-structured and XML like documents. The goal is to handle both content and structural information, and to deal with different types of information content (text, image, etc.). We consider here the task of structured document classification. We propose a generative model able to handle both structure and content which is based on Bayesian networks. We then show how to transform this generative model into a discriminant classifier using the method of Fisher kernel. The model is then extended for dealing with different types of content information (here text and images). The model was tested on three databases: the classical webKB corpus composed of HTML pages, the new INEX corpus which has become a reference in the field of ad-hoc retrieval for XML documents, and a multimedia corpus of Web pages.
  4. Koch, T.; Vizine-Goetz, D.: Automatic classification and content navigation support for Web services : DESIRE II cooperates with OCLC (1998) 0.01
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    Abstract
    Emerging standards in knowledge representation and organization are preparing the way for distributed vocabulary support in Internet search services. NetLab researchers are exploring several innovative solutions for searching and browsing in the subject-based Internet gateway, Electronic Engineering Library, Sweden (EELS). The implementation of the EELS service is described, specifically, the generation of the robot-gathered database 'All' engineering and the automated application of the Ei thesaurus and classification scheme. NetLab and OCLC researchers are collaborating to investigate advanced solutions to automated classification in the DESIRE II context. A plan for furthering the development of distributed vocabulary support in Internet search services is offered.
  5. Koch, T.; Ardö, A.; Brümmer, A.: ¬The building and maintenance of robot based internet search services : A review of current indexing and data collection methods. Prepared to meet the requirements of Work Package 3 of EU Telematics for Research, project DESIRE. Version D3.11v0.3 (Draft version 3) (1996) 0.01
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    Abstract
    After a short outline of problems, possibilities and difficulties of systematic information retrieval on the Internet and a description of efforts for development in this area, a specification of the terminology for this report is required. Although the process of retrieval is generally seen as an iterative process of browsing and information retrieval and several important services on the net have taken this fact into consideration, the emphasis of this report lays on the general retrieval tools for the whole of Internet. In order to be able to evaluate the differences, possibilities and restrictions of the different services it is necessary to begin with organizing the existing varieties in a typological/ taxonomical survey. The possibilities and weaknesses will be briefly compared and described for the most important services in the categories robot-based WWW-catalogues of different types, list- or form-based catalogues and simultaneous or collected search services respectively. It will however for different reasons not be possible to rank them in order of "best" services. Still more important are the weaknesses and problems common for all attempts of indexing the Internet. The problems of the quality of the input, the technical performance and the general problem of indexing virtual hypertext are shown to be at least as difficult as the different aspects of harvesting, indexing and information retrieval. Some of the attempts made in the area of further development of retrieval services will be mentioned in relation to descriptions of the contents of documents and standardization efforts. Internet harvesting and indexing technology and retrieval software is thoroughly reviewed. Details about all services and software are listed in analytical forms in Annex 1-3.
  6. Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.01
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    Date
    5. 5.2003 14:17:22
  7. McKiernan, G.: Automated categorisation of Web resources : a profile of selected projects, research, products, and services (1996) 0.01
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  8. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.01
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    Date
    22. 8.2009 12:54:24
  9. HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  10. Mukhopadhyay, S.; Peng, S.; Raje, R.; Palakal, M.; Mostafa, J.: Multi-agent information classification using dynamic acquaintance lists (2003) 0.01
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    Abstract
    There has been considerable interest in recent years in providing automated information services, such as information classification, by means of a society of collaborative agents. These agents augment each other's knowledge structures (e.g., the vocabularies) and assist each other in providing efficient information services to a human user. However, when the number of agents present in the society increases, exhaustive communication and collaboration among agents result in a [arge communication overhead and increased delays in response time. This paper introduces a method to achieve selective interaction with a relatively small number of potentially useful agents, based an simple agent modeling and acquaintance lists. The key idea presented here is that the acquaintance list of an agent, representing a small number of other agents to be collaborated with, is dynamically adjusted. The best acquaintances are automatically discovered using a learning algorithm, based an the past history of collaboration. Experimental results are presented to demonstrate that such dynamically learned acquaintance lists can lead to high quality of classification, while significantly reducing the delay in response time.
  11. Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989) 0.01
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    Pages
    S.1-22
  12. Dubin, D.: Dimensions and discriminability (1998) 0.01
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    Date
    22. 9.1997 19:16:05
  13. Automatic classification research at OCLC (2002) 0.01
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    Date
    5. 5.2003 9:22:09
  14. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.01
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    Date
    1. 8.1996 22:08:06
  15. Yoon, Y.; Lee, C.; Lee, G.G.: ¬An effective procedure for constructing a hierarchical text classification system (2006) 0.01
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    Date
    22. 7.2006 16:24:52
  16. Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.01
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    Date
    22. 9.2008 18:31:54
  17. Koch, T.; Vizine-Goetz, D.: DDC and knowledge organization in the digital library : Research and development. Demonstration pages (1999) 0.01
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    Content
    1. Increased Importance of Knowledge Organization in Internet Services - 2. Quality Subject Service and the role of classification - 3. Developing the DDC into a knowledge organization instrument for the digital library. OCLC site - 4. DESIRE's Barefoot Solutions of Automatic Classification - 5. Advanced Classification Solutions in DESIRE and CORC - 6. Future directions of research and development - 7. General references
  18. Koch, T.; Ardö, A.; Noodén, L.: ¬The construction of a robot-generated subject index : DESIRE II D3.6a, Working Paper 1 (1999) 0.01
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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.
  19. Golub, K.: Automated subject classification of textual Web pages, based on a controlled vocabulary : challenges and recommendations (2006) 0.01
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    Content
    Beitrag eines Themenheftes "Knowledge organization systems and services"
  20. Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.00
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    Date
    22. 3.2009 19:11:54