Search (3 results, page 1 of 1)

  • × theme_ss:"Automatisches Indexieren"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Ma, N.; Zheng, H.T.; Xiao, X.: ¬An ontology-based latent semantic indexing approach using long short-term memory networks (2017) 0.11 
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    Abstract
    Nowadays, online data shows an astonishing increase and the issue of semantic indexing remains an open question. Ontologies and knowledge bases have been widely used to optimize performance. However, researchers are placing increased emphasis on internal relations of ontologies but neglect latent semantic relations between ontologies and documents. They generally annotate instances mentioned in documents, which are related to concepts in ontologies. In this paper, we propose an Ontology-based Latent Semantic Indexing approach utilizing Long Short-Term Memory networks (LSTM-OLSI). We utilize an importance-aware topic model to extract document-level semantic features and leverage ontologies to extract word-level contextual features. Then we encode the above two levels of features and match their embedding vectors utilizing LSTM networks. Finally, the experimental results reveal that LSTM-OLSI outperforms existing techniques and demonstrates deep comprehension of instances and articles.
    Object
    Latent Semantic Indexing
  2. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.03 
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    Abstract
    We propose a method for improving access to scientific literature by analyzing the content of research papers beyond citation links and topic tracking. Our model relies on a typology of explicit semantic relations. These relations are instantiated in the abstract/introduction part of the papers and can be identified automatically using textual data and external ontologies. Preliminary results show a promising precision in unsupervised relationship classification.
  3. Harman, D.: Automatic indexing (1994) 0.02 
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    Content
    Enthält die Abschnitte: What constitutes a record; What constitutes a word and what 'words' to index; Use of stop lists; Use of suffixing or stemming; Advanced automatic indexing techniques (term weighting, query expansion, the use of multiple-word phrases for indexing)
    Source
    Challenges in indexing electronic text and images. Ed.: R. Fidel et al

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