Search (163 results, page 1 of 9)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.09
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    Series
    Communications in computer and information science; 672
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  2. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.09
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    Series
    Communications in computer and information science; 672
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  3. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.07
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    Abstract
    A new search paradigm, in which the primary user activity is the guided exploration of a complex information space rather than the retrieval of items based on precise specifications, is proposed. The author claims that this paradigm is the norm in most practical applications, and that solutions based on traditional search methods are not effective in this context. He then presents a solution based on dynamic taxonomies, a knowledge management model that effectively guides users to reach their goal while giving them total freedom in exploring the information base. Applications, benefits, and current research are discussed.
    Date
    22. 7.2006 17:56:22
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.792-796
  4. Faaborg, A.; Lagoze, C.: Semantic browsing (2003) 0.06
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    Series
    Lecture notes in computer science; vol.2769
    Source
    Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
  5. Koike, A.; Takagi, T.: Knowledge discovery based on an implicit and explicit conceptual network (2007) 0.06
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    Abstract
    The amount of knowledge accumulated in published scientific papers has increased due to the continuing progress being made in scientific research. Since numerous papers have only reported fragments of scientific facts, there are possibilities for discovering new knowledge by connecting these facts. We therefore developed a system called BioTermNet to draft a conceptual network with hybrid methods of information extraction and information retrieval. Two concepts are regarded as related in this system if (a) their relationship is clearly described in MEDLINE abstracts or (b) they have distinctively co-occurred in abstracts. PRIME data, including protein interactions and functions extracted by NLP techniques, are used in the former, and the Singhalmeasure for information retrieval is used in the latter. Relationships that are not clearly or directly described in an abstract can be extracted by connecting multiple concepts. To evaluate how well this system performs, Swanson's association between Raynaud's disease and fish oil and that between migraine and magnesium were tested with abstracts that had been published before the discovery of these associations. The result was that when start and end concepts were given, plausible and understandable intermediate concepts connecting them could be detected. When only the start concept was given, not only the focused concept (magnesium and fish oil) but also other probable concepts could be detected as related concept candidates. Finally, this system was applied to find diseases related to the BRCA1 gene. Some other new potentially related diseases were detected along with diseases whose relations to BRCA1 were already known.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.1, S.51-65
  6. Greenberg, J.: Automatic query expansion via lexical-semantic relationships (2001) 0.06
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    Abstract
    Structured thesauri encode equivalent, hierarchical, and associative relationships and have been developed as indexing/retrieval tools. Despite the fact that these tools provide a rich semantic network of vocabulary terms, they are seldom employed for automatic query expansion (QE) activities. This article reports on an experiment that examined whether thesaurus terms, related to query in a specified semantic way (as synonyms and partial-synonyms (SYNs), narrower terms (NTs), related terms (RTs), and broader terms (BTs)), could be identified as having a more positive impact on retrieval effectiveness when added to a query through automatic QE. The research found that automatic QE via SYNs and NTs increased relative recall with a decline in precision that was not statistically significant, and that automatic QE via RTs and BTs increased relative recall with a decline in precision that was statistically significant. Recallbased and a precision-based ranking orders for automatic QE via semantically encoded thesauri terminology were identified. Mapping results found between enduser query terms and the ProQuest Controlled Vocabulary (1997) (the thesaurus used in this study) are reported, and future research foci related to the investigation are discussed
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.5, S.402-415
  7. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.05
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    Date
    16.11.2008 16:22:48
    Series
    Lecture notes in computer science; vol.3232
    Source
    Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
  8. Tudhope, D.; Blocks, D.; Cunliffe, D.; Binding, C.: Query expansion via conceptual distance in thesaurus indexed collections (2006) 0.05
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    Abstract
    Purpose - The purpose of this paper is to explore query expansion via conceptual distance in thesaurus indexed collections Design/methodology/approach - An extract of the National Museum of Science and Industry's collections database, indexed with the Getty Art and Architecture Thesaurus (AAT), was the dataset for the research. The system architecture and algorithms for semantic closeness and the matching function are outlined. Standalone and web interfaces are described and formative qualitative user studies are discussed. One user session is discussed in detail, together with a scenario based on a related public inquiry. Findings are set in context of the literature on thesaurus-based query expansion. This paper discusses the potential of query expansion techniques using the semantic relationships in a faceted thesaurus. Findings - Thesaurus-assisted retrieval systems have potential for multi-concept descriptors, permitting very precise queries and indexing. However, indexer and searcher may differ in terminology judgments and there may not be any exactly matching results. The integration of semantic closeness in the matching function permits ranked results for multi-concept queries in thesaurus-indexed applications. An in-memory representation of the thesaurus semantic network allows a combination of automatic and interactive control of expansion and control of expansion on individual query terms. Originality/value - The application of semantic expansion to browsing may be useful in interface options where thesaurus structure is hidden.
  9. Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016) 0.05
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    Abstract
    Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
    Content
    Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316300528.
  10. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: FACET: thesaurus retrieval with semantic term expansion (2002) 0.05
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    Abstract
    There are many advantages for Digital Libraries in indexing with classifications or thesauri, but some current disincentive in the lack of flexible retrieval tools that deal with compound descriptors. This demonstration of a research prototype illustrates a matching function for compound descriptors, or multi-concept subject headings, that does not rely on exact matching but incorporates term expansion via thesaurus semantic relationships to produce ranked results that take account of missing and partially matching terms. The matching function is based on a measure of semantic closeness between terms.The work is part of the EPSRC funded FACET project in collaboration with the UK National Museum of Science and Industry (NMSI) which includes the National Railway Museum. An export of NMSI's Collections Database is used as the dataset for the research. The J. Paul Getty Trust's Art and Architecture Thesaurus (AAT) is the main thesaurus in the project. The AAT is a widely used thesaurus (over 120,000 terms). Descriptors are organised in 7 facets representing separate conceptual classes of terms.The FACET application is a multi tiered architecture accessing a SQL Server database, with an OLE DB connection. The thesauri are stored as relational tables in the Server's database. However, a key component of the system is a parallel representation of the underlying semantic network as an in-memory structure of thesaurus concepts (corresponding to preferred terms). The structure models the hierarchical and associative interrelationships of thesaurus concepts via weighted poly-hierarchical links. Its primary purpose is real-time semantic expansion of query terms, achieved by a spreading activation semantic closeness algorithm. Queries with associated results are stored persistently using XML format data. A Visual Basic interface combines a thesaurus browser and an initial term search facility that takes into account equivalence relationships. Terms are dragged to a direct manipulation Query Builder which maintains the facet structure.
  11. Sebastian, Y.: Literature-based discovery by learning heterogeneous bibliographic information networks (2017) 0.05
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    Abstract
    Literature-based discovery (LBD) research aims at finding effective computational methods for predicting previously unknown connections between clusters of research papers from disparate research areas. Existing methods encompass two general approaches. The first approach searches for these unknown connections by examining the textual contents of research papers. In addition to the existing textual features, the second approach incorporates structural features of scientific literatures, such as citation structures. These approaches, however, have not considered research papers' latent bibliographic metadata structures as important features that can be used for predicting previously unknown relationships between them. This thesis investigates a new graph-based LBD method that exploits the latent bibliographic metadata connections between pairs of research papers. The heterogeneous bibliographic information network is proposed as an efficient graph-based data structure for modeling the complex relationships between these metadata. In contrast to previous approaches, this method seamlessly combines textual and citation information in the form of pathbased metadata features for predicting future co-citation links between research papers from disparate research fields. The results reported in this thesis provide evidence that the method is effective for reconstructing the historical literature-based discovery hypotheses. This thesis also investigates the effects of semantic modeling and topic modeling on the performance of the proposed method. For semantic modeling, a general-purpose word sense disambiguation technique is proposed to reduce the lexical ambiguity in the title and abstract of research papers. The experimental results suggest that the reduced lexical ambiguity did not necessarily lead to a better performance of the method. This thesis discusses some of the possible contributing factors to these results. Finally, topic modeling is used for learning the latent topical relations between research papers. The learned topic model is incorporated into the heterogeneous bibliographic information network graph and allows new predictive features to be learned. The results in this thesis suggest that topic modeling improves the performance of the proposed method by increasing the overall accuracy for predicting the future co-citation links between disparate research papers.
  12. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.04
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
    Series
    Lecture notes in computer science; 2539
  13. Hancock-Beaulieu, M.: Query expansion : advances in research in online catalogues (1992) 0.04
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    Source
    Journal of information science. 18(1992), S.99-103
  14. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.04
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    Abstract
    Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies
    Source
    Journal of information science. 24(1998) no.1, S.3-18
  15. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.04
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    Abstract
    Reports on the design of a GUI for the Okapi 'best match' retrieval system developed at the Centre for Interactive Systems Research, City University, UK, for online library catalogues. The X-Windows interface includes an interactive query expansion (IQE) facilty which involves the user in the selection of query terms to reformulate a search. Presents the design rationale, based on a game board metaphor, and describes the features of each of the stages of the search interaction. Reports on the early operational field trial and discusses relevant evaluation issues and objectives
    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  16. Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008) 0.04
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    Abstract
    This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2171-2185
  17. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.04
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    Date
    1. 2.2016 18:25:22
    Series
    Lecture notes in computer science ; 9398
  18. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.04
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    Date
    1. 2.2016 18:25:22
    Series
    Lecture notes in computer science ; 9398
  19. Efthimiadis, E.N.: Query expansion (1996) 0.03
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    Abstract
    State of the art review of query expansion (or term expansion) as the process of supplementing the original query with additional terms in order to improve retrieval performance. Research in the subject is presented in a highly structured way and is presented according to 3 types of query expansion; manual query expansion; automatic query expansion; and interactive query expansion
    Source
    Annual review of information science and technology. 31(1996), S.121-187
  20. Surfing versus Drilling for knowledge in science : When should you use your computer? When should you use your brain? (2018) 0.03
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    Abstract
    For this second Special Issue of Infozine, we have invited students, teachers, researchers, and software developers to share their opinions about one or the other aspect of this broad topic: how to balance drilling (for depth) vs. surfing (for breadth) in scientific learning, teaching, research, and software design - and how the modern digital-liberal system affects our ability to strike this balance. This special issue is meant to provide a wide and unbiased spectrum of possible viewpoints on the topic, helping readers to define lucidly their own position and information use behavior.
    Content
    Editorial: Surfing versus Drilling for Knowledge in Science: When should you use your computer? When should you use your brain? Blaise Pascal: Les deux infinis - The two infinities / Philippe Hünenberger and Oliver Renn - "Surfing" vs. "drilling" in the modern scientific world / Antonio Loprieno - Of millimeter paper and machine learning / Philippe Hünenberger - From one to many, from breadth to depth - industrializing research / Janne Soetbeer - "Deep drilling" requires "surfing" / Gerd Folkers and Laura Folkers - Surfing vs. drilling in science: A delicate balance / Alzbeta Kubincová - Digital trends in academia - for the sake of critical thinking or comfort? / Leif-Thore Deck - I diagnose, therefore I am a Doctor? Will drilling computer software replace human doctors in the future? / Yi Zheng - Surfing versus drilling in fundamental research / Wilfred van Gunsteren - Using brain vs. brute force in computational studies of biological systems / Arieh Warshel - Laboratory literature boards in the digital age / Jeffrey Bode - Research strategies in computational chemistry / Sereina Riniker - Surfing on the hype waves or drilling deep for knowledge? A perspective from industry / Nadine Schneider and Nikolaus Stiefl - The use and purpose of articles and scientists / Philip Mark Lund - Can you look at papers like artwork? / Oliver Renn - Dynamite fishing in the data swamp / Frank Perabo 34 Streetlights, augmented intelligence, and information discovery / Jeffrey Saffer and Vicki Burnett - "Yes Dave. Happy to do that for you." Why AI, machine learning, and blockchain will lead to deeper "drilling" / Michiel Kolman and Sjors de Heuvel - Trends in scientific document search ( Stefan Geißler - Power tools for text mining / Jane Reed 42 Publishing and patenting: Navigating the differences to ensure search success / Paul Peters

Years

Languages

  • e 152
  • d 8
  • chi 1
  • f 1
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Types

  • a 142
  • el 14
  • m 10
  • r 5
  • x 3
  • s 2
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