Search (235 results, page 1 of 12)

  • × type_ss:"a"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Zarri, G.P.: Utilisation de structures conceptuelles complexes pour représenter le "contenu sémantique" de textes narratifs (1999) 0.06 
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    Imprint
    Lille : Université Charles-de-Gaulle
    Source
    Organisation des connaissances en vue de leur intégration dans les systèmes de représentation et de recherche d'information. Ed.: J. Maniez, et al
    Type
    a
  2. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.06 
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    Abstract
    A substantial fraction of web search queries contain references to entities, such as persons, organizations, and locations. Recently, methods that exploit named entities have been shown to be more effective for query expansion than traditional pseudorelevance feedback methods. In this article, we introduce a supervised learning approach that exploits named entities for query expansion using Wikipedia as a repository of high-quality feedback documents. In contrast with existing entity-oriented pseudorelevance feedback approaches, we tackle query expansion as a learning-to-rank problem. As a result, not only do we select effective expansion terms but we also weigh these terms according to their predicted effectiveness. To this end, we exploit the rich structure of Wikipedia articles to devise discriminative term features, including each candidate term's proximity to the original query terms, as well as its frequency across multiple article fields and in category and infobox descriptors. Experiments on three Text REtrieval Conference web test collections attest the effectiveness of our approach, with gains of up to 23.32% in terms of mean average precision, 19.49% in terms of precision at 10, and 7.86% in terms of normalized discounted cumulative gain compared with a state-of-the-art approach for entity-oriented query expansion.
    Date
    22. 8.2014 17:07:50
    Type
    a
  3. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.04 
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    Date
    30. 3.2001 13:32:22
    Type
    a
  4. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.03 
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
    Type
    a
  5. Colace, F.; Santo, M. De; Greco, L.; Napoletano, P.: Weighted word pairs for query expansion (2015) 0.03 
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    Abstract
    This paper proposes a novel query expansion method to improve accuracy of text retrieval systems. Our method makes use of a minimal relevance feedback to expand the initial query with a structured representation composed of weighted pairs of words. Such a structure is obtained from the relevance feedback through a method for pairs of words selection based on the Probabilistic Topic Model. We compared our method with other baseline query expansion schemes and methods. Evaluations performed on TREC-8 demonstrated the effectiveness of the proposed method with respect to the baseline.
    Type
    a
  6. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.03 
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Type
    a
  7. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.03 
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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
    Type
    a
  8. Colace, F.; Santo, M. de; Greco, L.; Napoletano, P.: Improving relevance feedback-based query expansion by the use of a weighted word pairs approach (2015) 0.03 
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    Abstract
    In this article, the use of a new term extraction method for query expansion (QE) in text retrieval is investigated. The new method expands the initial query with a structured representation made of weighted word pairs (WWP) extracted from a set of training documents (relevance feedback). Standard text retrieval systems can handle a WWP structure through custom Boolean weighted models. We experimented with both the explicit and pseudorelevance feedback schemas and compared the proposed term extraction method with others in the literature, such as KLD and RM3. Evaluations have been conducted on a number of test collections (Text REtrivel Conference [TREC]-6, -7, -8, -9, and -10). Results demonstrated that the QE method based on this new structure outperforms the baseline.
    Type
    a
  9. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.02 
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    Date
    1. 2.2016 18:25:22
    Type
    a
  10. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.02 
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    Date
    1. 2.2016 18:25:22
    Type
    a
  11. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.02 
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Type
    a
  12. Bräscher, M.: Semantic relations in knowledge organization systems (2014) 0.02 
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    Abstract
    Semantic relations in knowledge organization systems (KOS) are discussed as well as the need to analyze and systematize the contributions from different areas of knowledge that are devoted to semantic studies in order to collaborate in the definition of a theoretical framework for the study of types of relations included in KOS. Partial results of a survey reveal that, in general, standards and guidelines for developing thesauri are limited to defining and exemplifying types of relationships without guidance concerning the theoretical underpinning of these definitions. The possibilities of a compositional approach to defining the meaning of syntagmatic relations is discussed. Studies on the theoretical foundations that guide the establishment of semantic relations and approaches to be adopted for the preparation of KOS certainly contribute to consolidating a theoretical framework for the area of knowledge organization.
    Footnote
    Papers from the 2nd ISKO-Brazil Conference, Rio de Janeiro, May, 2013.
    Type
    a
  13. Ferreira, R.S.; Graça Pimentel, M. de; Cristo, M.: ¬A wikification prediction model based on the combination of latent, dyadic, and monadic features (2018) 0.02 
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    Abstract
    Considering repositories of web documents that are semantically linked and created in a collaborative fashion, as in the case of Wikipedia, a key problem faced by content providers is the placement of links in the articles. These links must support user navigation and provide a deeper semantic interpretation of the content. Current wikification methods exploit machine learning techniques to capture characteristics of the concepts and its associations. In previous work, we proposed a preliminary prediction model combining traditional predictors with a latent component which captures the concept graph topology by means of matrix factorization. In this work, we provide a detailed description of our method and a deeper comparison with a state-of-the-art wikification method using a sample of Wikipedia and report a gain up to 13% in F1 score. We also provide a comprehensive analysis of the model performance showing the importance of the latent predictor component and the attributes derived from the associations between the concepts. Moreover, we include an analysis that allows us to conclude that the model is resilient to ambiguity without including a disambiguation phase. We finally report the positive impact of selecting training samples from specific content quality classes.
    Type
    a
  14. Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994) 0.02 
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    Abstract
    The process of term selection for query expansion by end-users is discussed within the context of a study of interactive query expansion in a relevance feedback environment. This user study focuses on how users' perceive and understand term relationships, such as hierarchical and associative relationships, in their searches
    Date
    30. 3.2001 13:35:22
    Type
    a
  15. Gnoli, C.; Santis, R. de; Pusterla, L.: Commerce, see also Rhetoric : cross-discipline relationships as authority data for enhanced retrieval (2015) 0.02 
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    Abstract
    Subjects in a classification scheme are often related to other subjects belonging to different hierarchies. This problem was identified already by Hugh of Saint Victor (1096?-1141). Still with present-time bibliographic classifications, a user browsing the class of architecture under the hierarchy of arts may miss relevant items classified in building or in civil engineering under the hierarchy of applied sciences. To face these limitations we have developed SciGator, a browsable interface to explore the collections of all scientific libraries at the University of Pavia. Besides showing subclasses of a given class, the interface points users to related classes in the Dewey Decimal Classification, or in other local schemes, and allows for expanded queries that include them. This is made possible by using a special field for related classes in the database structure which models classification authority data. Ontologically, many relationships between classes in different hierarchies are cases of existential dependence. Dependence can occur between disciplines in such disciplinary classifications as Dewey (e.g. architecture existentially depends on building), or between phenomena in such phenomenon-based classifications as the Integrative Levels Classification (e.g. fishing as a human activity existentially depends on fish as a class of organisms). We provide an example of its representation in OWL and discuss some details of it.
    Source
    Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
    Type
    a
  16. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.02 
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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
    Type
    a
  17. Faaborg, A.; Lagoze, C.: Semantic browsing (2003) 0.02 
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    Abstract
    We have created software applications that allow users to both author and use Semantic Web metadata. To create and use a layer of semantic content on top of the existing Web, we have (1) implemented a user interface that expedites the task of attributing metadata to resources on the Web, and (2) augmented a Web browser to leverage this semantic metadata to provide relevant information and tasks to the user. This project provides a framework for annotating and reorganizing existing files, pages, and sites on the Web that is similar to Vannevar Bushrsquos original concepts of trail blazing and associative indexing.
    Source
    Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
    Type
    a
  18. Lund, K.; Burgess, C.; Atchley, R.A.: Semantic and associative priming in high-dimensional semantic space (1995) 0.02 
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    Abstract
    We present a model of semantic memory that utilizes a high dimensional semantic space constructed from a co-occurrence matrix. This matrix was formed by analyzing a lot) million word corpus. Word vectors were then obtained by extracting rows and columns of this matrix, These vectors were subjected to multidimensional scaling. Words were found to cluster semantically. suggesting that interword distance may be interpretable as a measure of semantic similarity, In attempting to replicate with our simulation the semantic and ...
    Source
    Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society: July 22 - 25, 1995, University of Pittsburgh / ed. by Johanna D. Moore and Jill Fain Lehmann
    Type
    a
  19. Cai, F.; Rijke, M. de: Learning from homologous queries and semantically related terms for query auto completion (2016) 0.02 
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    Abstract
    Query auto completion (QAC) models recommend possible queries to web search users when they start typing a query prefix. Most of today's QAC models rank candidate queries by popularity (i.e., frequency), and in doing so they tend to follow a strict query matching policy when counting the queries. That is, they ignore the contributions from so-called homologous queries, queries with the same terms but ordered differently or queries that expand the original query. Importantly, homologous queries often express a remarkably similar search intent. Moreover, today's QAC approaches often ignore semantically related terms. We argue that users are prone to combine semantically related terms when generating queries. We propose a learning to rank-based QAC approach, where, for the first time, features derived from homologous queries and semantically related terms are introduced. In particular, we consider: (i) the observed and predicted popularity of homologous queries for a query candidate; and (ii) the semantic relatedness of pairs of terms inside a query and pairs of queries inside a session. We quantify the improvement of the proposed new features using two large-scale real-world query logs and show that the mean reciprocal rank and the success rate can be improved by up to 9% over state-of-the-art QAC models.
    Type
    a
  20. Meij, E.; Rijke, M. de: Thesaurus-based feedback to support mixed search and browsing environments (2007) 0.02 
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    Abstract
    We propose and evaluate a query expansion mechanism that supports searching and browsing in collections of annotated documents. Based on generative language models, our feedback mechanism uses document-level annotations to bias the generation of expansion terms and to generate browsing suggestions in the form of concepts selected from a controlled vocabulary (as typically used in digital library settings). We provide a detailed formalization of our feedback mechanism and evaluate its effectiveness using the TREC 2006 Genomics track test set. As to the retrieval effectiveness, we find a 20% improvement in mean average precision over a query-likelihood baseline, whilst increasing precision at 10. When we base the parameter estimation and feedback generation of our algorithm on a large corpus, we also find an improvement over state-of-the-art relevance models. The browsing suggestions are assessed along two dimensions: relevancy and specifity. We present an account of per-topic results, which helps understand for what type of queries our feedback mechanism is particularly helpful.
    Type
    a

Authors

Years

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  • d 31
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