Search (18 results, page 1 of 1)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × type_ss:"a"
  • × year_i:[2010 TO 2020}
  1. Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018) 0.02 
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    Abstract
    A challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academic and industry. To address this challenge, semantic analysis of textual data is focused in this paper. We propose an ontology-based approach to extract semantics of textual data and define the domain of data. In other words, we semantically analyse the social data at two levels i.e. the entity level and the domain level. We have chosen Twitter as a social channel challenge for a purpose of concept proof. Domain knowledge is captured in ontologies which are then used to enrich the semantics of tweets provided with specific semantic conceptual representation of entities that appear in the tweets. Case studies are used to demonstrate this approach. We experiment and evaluate our proposed approach with a public dataset collected from Twitter and from the politics domain. The ontology-based approach leverages entity extraction and concept mappings in terms of quantity and accuracy of concept identification.
  2. Bettencourt, N.; Silva, N.; Barroso, J.: Semantically enhancing recommender systems (2016) 0.02 
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    Abstract
    As the amount of content and the number of users in social relationships is continually growing in the Internet, resource sharing and access policy management is difficult, time-consuming and error-prone. Cross-domain recommendation of private or protected resources managed and secured by each domain's specific access rules is impracticable due to private security policies and poor sharing mechanisms. This work focus on exploiting resource's content, user's preferences, users' social networks and semantic information to cross-relate different resources through their meta information using recommendation techniques that combine collaborative-filtering techniques with semantics annotations, by generating associations between resources. The semantic similarities established between resources are used on a hybrid recommendation engine that interprets user and resources' semantic information. The recommendation engine allows the promotion and discovery of unknown-unknown resources to users that could not even know about the existence of those resources thus providing means to solve the cross-domain recommendation of private or protected resources.
  3. Moreira, W.; Martínez-Ávila, D.: Concept relationships in knowledge organization systems : elements for analysis and common research among fields (2018) 0.01 
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    Abstract
    Knowledge organization systems have been studied in several fields and for different and complementary aspects. Among the aspects that concentrate common interests, in this article we highlight those related to the terminological and conceptual relationships among the components of any knowledge organization system. This research aims to contribute to the critical analysis of knowledge organization systems, especially ontologies, thesauri, and classification systems, by the comprehension of its similarities and differences when dealing with concepts and their ways of relating to each other as well as to the conceptual design that is adopted.
  4. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.01 
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    Date
    1. 2.2016 18:25:22
  5. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.01 
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    1. 2.2016 18:25:22
  6. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.01 
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  7. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.01 
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    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  8. Sanfilippo, M.; Yang, S.; Fichman, P.: Trolling here, there, and everywhere : perceptions of trolling behaviors in context (2017) 0.01 
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    Abstract
    Online trolling has become increasingly prevalent and visible in online communities. Perceptions of and reactions to trolling behaviors varies significantly from one community to another, as trolling behaviors are contextual and vary across platforms and communities. Through an examination of seven trolling scenarios, this article intends to answer the following questions: how do trolling behaviors differ across contexts; how do perceptions of trolling differ from case to case; and what aspects of context of trolling are perceived to be important by the public? Based on focus groups and interview data, we discuss the ways in which community norms and demographics, technological features of platforms, and community boundaries are perceived to impact trolling behaviors. Two major contributions of the study include a codebook to support future analysis of trolling and formal concept analysis surrounding contextual perceptions of trolling.
  9. Xamena, E.; Brignole, N.B.; Maguitman, A.G.: ¬A study of relevance propagation in large topic ontologies (2013) 0.01 
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    Abstract
    Topic ontologies or web directories consist of large collections of links to websites, arranged by topic in different categories. The structure of these ontologies is typically not flat because there are hierarchical and nonhierarchical relationships among topics. As a consequence, websites classified under a certain topic may be relevant to other topics. Although some of these relevance relations are explicit, most of them must be discovered by an analysis of the structure of the ontologies. This article proposes a family of models of relevance propagation in topic ontologies. An efficient computational framework is described and used to compute nine different models for a portion of the Open Directory Project graph consisting of more than half a million nodes and approximately 1.5 million edges of different types. After performing a quantitative analysis, a user study was carried out to compare the most promising models. It was found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural aspects of an ontology. However, there is a clear indication that including transitive relations induced by the nonhierarchical components of the ontology results in relevance propagation models that are superior to more basic approaches.
  10. Pal, D.; Mitra, M.; Datta, K.: Improving query expansion using WordNet (2014) 0.01 
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    Abstract
    This study proposes a new way of using WordNet for query expansion (QE). We choose candidate expansion terms from a set of pseudo-relevant documents; however, the usefulness of these terms is measured based on their definitions provided in a hand-crafted lexical resource such as WordNet. Experiments with a number of standard TREC collections WordNet-based that this method outperforms existing WordNet-based methods. It also compares favorably with established QE methods such as KLD and RM3. Leveraging earlier work in which a combination of QE methods was found to outperform each individual method (as well as other well-known QE methods), we next propose a combination-based QE method that takes into account three different aspects of a candidate expansion term's usefulness: (a) its distribution in the pseudo-relevant documents and in the target corpus, (b) its statistical association with query terms, and (c) its semantic relation with the query, as determined by the overlap between the WordNet definitions of the term and query terms. This combination of diverse sources of information appears to work well on a number of test collections, viz., TREC123, TREC5, TREC678, TREC robust (new), and TREC910 collections, and yields significant improvements over competing methods on most of these collections.
  11. Hendahewa, C.; Shah, C.: Implicit search feature based approach to assist users in exploratory search tasks (2015) 0.01 
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    Abstract
    Analyzing and modeling users' online search behaviors when conducting exploratory search tasks could be instrumental in discovering search behavior patterns that can then be leveraged to assist users in reaching their search task goals. We propose a framework for evaluating exploratory search based on implicit features and user search action sequences extracted from the transactional log data to model different aspects of exploratory search namely uncertainty, creativity, exploration, and knowledge discovery. We show the effectiveness of the proposed framework by demonstrating how it can be used to understand and evaluate user search performance and thereby make meaningful recommendations to improve the overall search performance of users. We used data collected from a user study consisting of 18 users conducting an exploratory search task for two sessions with two different topics in the experimental analysis. With this analysis we show that we can effectively model their behavior using implicit features to predict the user's future performance level with above 70% accuracy in most cases. Further, using simulations we demonstrate that our search process based recommendations improve the search performance of low performing users over time and validate these findings using both qualitative and quantitative approaches.
  12. Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010) 0.01 
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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.
  13. Salaba, A.; Zeng, M.L.: Extending the "Explore" user task beyond subject authority data into the linked data sphere (2014) 0.01 
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    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  14. Mlodzka-Stybel, A.: Towards continuous improvement of users' access to a library catalogue (2014) 0.01 
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    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  15. Zeng, M.L.; Gracy, K.F.; Zumer, M.: Using a semantic analysis tool to generate subject access points : a study using Panofsky's theory and two research samples (2014) 0.00 
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    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  16. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.00 
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    Date
    22. 8.2014 17:07:50
  17. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.00 
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    Date
    20. 1.2015 18:30:22
  18. Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014) 0.00 
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    20. 1.2015 18:30:22

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