Search (232 results, page 12 of 12)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Bando, L.L.; Scholer, F.; Turpin, A.: Query-biased summary generation assisted by query expansion : temporality (2015) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.5, S.961-979
  2. Hendahewa, C.; Shah, C.: Implicit search feature based approach to assist users in exploratory search tasks (2015) 0.00
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    Source
    Information processing and management. 51(2015) no.5, S.643-661
  3. Jiang, Y.; Zhang, X.; Tang, Y.; Nie, R.: Feature-based approaches to semantic similarity assessment of concepts using Wikipedia (2015) 0.00
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    Source
    Information processing and management. 51(2015) no.3, S.215-234
  4. Cai, F.; Rijke, M. de: Learning from homologous queries and semantically related terms for query auto completion (2016) 0.00
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    Source
    Information processing and management. 52(2016) no.4, S.628-643
  5. Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010) 0.00
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    Abstract
    Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.
  6. Ferreira, R.S.; Graça Pimentel, M. de; Cristo, M.: ¬A wikification prediction model based on the combination of latent, dyadic, and monadic features (2018) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.3, S.380-394
  7. Ru, C.; Tang, J.; Li, S.; Xie, S.; Wang, T.: Using semantic similarity to reduce wrong labels in distant supervision for relation extraction (2018) 0.00
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    Source
    Information processing and management. 54(2018) no.4, S.593-608
  8. Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000) 0.00
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    Source
    Journal of the American Society for Information Science. 51(2000) no.11, S.989-1003
  9. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: FACET: thesaurus retrieval with semantic term expansion (2002) 0.00
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    Theme
    Information Gateway
  10. Semantic search over the Web (2012) 0.00
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    Abstract
    The Web has become the world's largest database, with search being the main tool that allows organizations and individuals to exploit its huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree the semantic dimension, i.e., understanding the meaning of the query and of the document content. Combining search and semantics gives birth to the idea of semantic search. Traditional search engines have already advertised some semantic dimensions. Some of them, for instance, can enhance their generated result sets with documents that are semantically related to the query terms even though they may not include these terms. Nevertheless, the exploitation of the semantic search has not yet reached its full potential. In this book, Roberto De Virgilio, Francesco Guerra and Yannis Velegrakis present an extensive overview of the work done in Semantic Search and other related areas. They explore different technologies and solutions in depth, making their collection a valuable and stimulating reading for both academic and industrial researchers. The book is divided into three parts. The first introduces the readers to the basic notions of the Web of Data. It describes the different kinds of data that exist, their topology, and their storing and indexing techniques. The second part is dedicated to Web Search. It presents different types of search, like the exploratory or the path-oriented, alongside methods for their efficient and effective implementation. Other related topics included in this part are the use of uncertainty in query answering, the exploitation of ontologies, and the use of semantics in mashup design and operation. The focus of the third part is on linked data, and more specifically, on applying ideas originating in recommender systems on linked data management, and on techniques for the efficiently querying answering on linked data.
  11. Hazrina, S.; Sharef, N.M.; Ibrahim, H.; Murad, M.A.A.; Noah, S.A.M.: Review on the advancements of disambiguation in semantic question answering system (2017) 0.00
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    Source
    Information processing and management. 53(2017) no.1, S.52-69
  12. Layfield, C.; Azzopardi, J,; Staff, C.: Experiments with document retrieval from small text collections using Latent Semantic Analysis or term similarity with query coordination and automatic relevance feedback (2017) 0.00
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    Series
    Information Systems and Applications, incl. Internet/Web, and HCI; 10151

Years

Languages

  • e 191
  • d 38
  • chi 1
  • f 1
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Types

  • a 201
  • el 20
  • m 16
  • r 5
  • x 4
  • p 2
  • s 2
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