Search (382 results, page 4 of 20)

  • × theme_ss:"Automatisches Indexieren"
  1. Hersh, W.R.; Hickam, D.H.: ¬A comparison of two methods for indexing and retrieval from a full-text medical database (1992) 0.00 
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    Abstract
    Reports results of a study of 2 information retrieval systems on a 2.000 document full text medical database. The first system, SAPHIRE, features concept based automatic indexing and statistical retrieval techniques, while the second system, SWORD, features traditional word based Boolean techniques, 16 medical students at Oregon Health Sciences Univ. each performed 10 searches and their results, recorded in terms of recall and precision, showed nearly equal performance for both systems. SAPHIRE was also compared with a version of SWORD modified to use automatic indexing and ranked retrieval. Using batch input of queries, the latter method performed slightly better
    Type
    a
  2. O'Kane, K.C.: Generating hierarchical document indices from common denominators in large document collections (1996) 0.00 
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    Abstract
    Describes an effective, simple and efficient algorithm for computer generation of hierarchical indices from Document Term matrices by means of calculating common denominator vectors from the document vector set. This procedure produces an intuitive, user friendly hierarchical index of a document collection not unlike that which would be expected had a manual indexer set about to create an index or outline of a collection. The resulting index, when presented with a graphical user interface, provides the user with a natural easily comprehended view of the document collection, permits general browsing and informal search activities with an access method that requires no keyboard entry or prior knowledge of the vocabulary
    Type
    a
  3. Lassalle, E.: Text retrieval : from a monolingual system to a multilingual system (1993) 0.00 
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    Abstract
    Describes the TELMI monolingual text retrieval system and its future extension, a multilingual system. TELMI is designed for medium sized databases containing short texts. The characteristics of the system are fine-grained natural language processing (NLP); an open domain and a large scale knowledge base; automated indexing based on conceptual representation of texts and reusability of the NLP tools. Discusses the French MINITEL service, the MGS information service and the TELMI research system covering the full text system; NLP architecture; the lexical level; the syntactic level; the semantic level and an example of the use of a generic system
    Type
    a
  4. Hlava, M.M.K.: Machine aided indexing (MAI) in a multilingual environment (1993) 0.00 
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    Abstract
    The machine aided indexing (MAI) software devloped by Access Innovations, Inc., is a semantic based, Boolean statement, rule interpreting application with 3 modules: the MA engine which accepts input files, matches terms in the knowledge base, interprets rules, and outputs a text file with suggested indexing terms; a rule building application allowing each Boolean style rule in the knowledge base to be created or modifies; and a statistical computation module which analyzes performance of the MA software against text manually indexed by professional human indexers. The MA software can be applied across multiple languages and can be used where the text to be searched is in one language and the indexes to be output are in another
    Type
    a
  5. Pulgarin, A.; Gil-Leiva, I.: Bibliometric analysis of the automatic indexing literature : 1956-2000 (2004) 0.00 
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    Abstract
    We present a bibliometric study of a corpus of 839 bibliographic references about automatic indexing, covering the period 1956-2000. We analyse the distribution of authors and works, the obsolescence and its dispersion, and the distribution of the literature by topic, year, and source type. We conclude that: (i) there has been a constant interest on the part of researchers; (ii) the most studied topics were the techniques and methods employed and the general aspects of automatic indexing; (iii) the productivity of the authors does fit a Lotka distribution (Dmax=0.02 and critical value=0.054); (iv) the annual aging factor is 95%; and (v) the dispersion of the literature is low.
    Type
    a
  6. Wolfe, EW.: a case study in automated metadata enhancement : Natural Language Processing in the humanities (2019) 0.00 
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    Abstract
    The Black Book Interactive Project at the University of Kansas (KU) is developing an expanded corpus of novels by African American authors, with an emphasis on lesser known writers and a goal of expanding research in this field. Using a custom metadata schema with an emphasis on race-related elements, each novel is analyzed for a variety of elements such as literary style, targeted content analysis, historical context, and other areas. Librarians at KU have worked to develop a variety of computational text analysis processes designed to assist with specific aspects of this metadata collection, including text mining and natural language processing, automated subject extraction based on word sense disambiguation, harvesting data from Wikidata, and other actions.
    Type
    a
  7. Fuhr, N.; Knorz, G.: Retrieval test evaluation of a rule based automatic indexing (AIR/PHYS) (1984) 0.00 
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  8. Salton, G.; Araya, J.: On the use of clustered file organizations in information search and retrieval (1990) 0.00 
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    Source
    Library classification and its functions. Int. Conf. on ..., 20.-21.6.1989, Edmonton, Alberta. Ed.: A. Nitecki u. T. Fell
    Type
    a
  9. Humphrey, S.M.: Automatic indexing of documents from journal descriptors : a preliminary investigation (1999) 0.00 
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    Abstract
    A new, fully automated approach for indedexing documents is presented based on associating textwords in a training set of bibliographic citations with the indexing of journals. This journal-level indexing is in the form of a consistent, timely set of journal descriptors (JDs) indexing the individual journals themselves. This indexing is maintained in journal records in a serials authority database. The advantage of this novel approach is that the training set does not depend on previous manual indexing of thousands of documents (i.e., any such indexing already in the training set is not used), but rather the relatively small intellectual effort of indexing at the journal level, usually a matter of a few thousand unique journals for which retrospective indexing to maintain consistency and currency may be feasible. If successful, JD indexing would provide topical categorization of documents outside the training set, i.e., journal articles, monographs, Web documents, reports from the grey literature, etc., and therefore be applied in searching. Because JDs are quite general, corresponding to subject domains, their most problable use would be for improving or refining search results
    Type
    a
  10. Selisskaya, M.A.: Ispol'zovanie mashinnogo obucheniya pri avtomaticheskoi klassifikatsii tekstov (1999) 0.00 
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    Footnote
    Übers. des Titels: Machine learning as a tool for development of automated text indexing systems
    Type
    a
  11. Lochbaum, K.E.; Streeter, A.R.: Comparing and combining the effectiveness of latent semantic indexing and the ordinary vector space model for information retrieval (1989) 0.00 
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    Abstract
    A retrievalsystem was built to find individuals with appropriate expertise within a large research establishment on the basis of their authored documents. The expert-locating system uses a new method for automatic indexing and retrieval based on singular value decomposition, a matrix decomposition technique related to the factor analysis. Organizational groups, represented by the documents they write, and the terms contained in these documents, are fit simultaneously into a 100-dimensional "semantic" space. User queries are positioned in the semantic space, and the most similar groups are returned to the user. Here we compared the standard vector-space model with this new technique and found that combining the two methods improved performance over either alone. We also examined the effects of various experimental variables on the system`s retrieval accuracy. In particular, the effects of: term weighting functions in the semantic space construction and in query construction, suffix stripping, and using lexical units larger than a a single word were studied.
    Type
    a
  12. Karpathy, A.; Fei-Fei, L.: Deep visual-semantic alignments for generating image descriptions (2015) 0.00 
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    Abstract
    We present a model that generates free-form natural language descriptions of image regions. Our model leverages datasets of images and their sentence descriptions to learn about the inter-modal correspondences between text and visual data. Our approach is based on a novel combination of Convolutional Neural Networks over image regions, bidirectional Recurrent Neural Networks over sentences, and a structured objective that aligns the two modalities through a multimodal embedding. We then describe a Recurrent Neural Network architecture that uses the inferred alignments to learn to generate novel descriptions of image regions. We demonstrate the effectiveness of our alignment model with ranking experiments on Flickr8K, Flickr30K and COCO datasets, where we substantially improve on the state of the art. We then show that the sentences created by our generative model outperform retrieval baselines on the three aforementioned datasets and a new dataset of region-level annotations.
    Type
    a
  13. Oliver, C.T.: One-eyed king: automated indexing (1989) 0.00 
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    Abstract
    In a work entitled 'Adagia' published in 1508, Erasmus collected ancient Greek and Roman proverbs. He included this proverb: "Among the blind, the one-eyed man is king". In a field where there is little interest in the theoretical research of related fields, and in understanding the theoretical assumptions on which practical activity is based, a one-eyed man, such as autumatic or mechanical indexing, easily appears respectable and becomes widely practiced despite its obvious deficiencies
    Type
    a
  14. Salton, G.: Fast document classification in automatic information retrieval (1978) 0.00 
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    Abstract
    A classified or clustered file is one where related or similar records are grouped into classes or clusters of items in such a way that all itmes within a cluster are jointly retrievable. Clustered files are easily adapted to to broad and narrow search strategies, and simple file updating methods are available. An inexpensive file clustering method applicable to large files is given together with appropriate file search methods
    Type
    a
  15. Keitz, W. von: Automatic indexing and the dissemination of information (1986) 0.00 
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    a
  16. Sparck Jones, K.; Tait, J.I.: Automatic search term variant generation (1984) 0.00 
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  17. Borko, H.; Bernick, M.: Automatic document classification : T.2 (1964) 0.00 
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  18. Garfield, E.; Sher, I.H.: KeyWords Plus: algorithmic derivative indexing (1993) 0.00 
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  19. Gray, W.A.; Harley, A.J.: Computer assisted indexing (1971) 0.00 
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  20. Smart, G.: Using language analysis to manage information (1993) 0.00 
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    Abstract
    The ESPRIT project SIMPR developed software to analyse documents and generate indexes for them. Of immediate application as a document indexing and classification system, this also offers a technology for information modelling that has broader implications, supporting many new uses for information management softeware. The project was based on the assumption that information can only be managed successfully by computer systems that can view the information contained in a document through the language in which the document is written, and that systems need to be sufficiently flexible to respond to the changing requirements of document use
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  • a 364
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