Search (38 results, page 1 of 2)

  • × theme_ss:"Visualisierung"
  • × year_i:[2010 TO 2020}
  1. Aletras, N.; Baldwin, T.; Lau, J.H.; Stevenson, M.: Evaluating topic representations for exploring document collections (2017) 0.05 
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    Abstract
    Topic models have been shown to be a useful way of representing the content of large document collections, for example, via visualization interfaces (topic browsers). These systems enable users to explore collections by way of latent topics. A standard way to represent a topic is using a term list; that is the top-n words with highest conditional probability within the topic. Other topic representations such as textual and image labels also have been proposed. However, there has been no comparison of these alternative representations. In this article, we compare 3 different topic representations in a document retrieval task. Participants were asked to retrieve relevant documents based on predefined queries within a fixed time limit, presenting topics in one of the following modalities: (a) lists of terms, (b) textual phrase labels, and (c) image labels. Results show that textual labels are easier for users to interpret than are term lists and image labels. Moreover, the precision of retrieved documents for textual and image labels is comparable to the precision achieved by representing topics using term lists, demonstrating that labeling methods are an effective alternative topic representation.
  2. Osiñska, V.: Visual analysis of classification scheme (2010) 0.05 
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    Abstract
    This paper proposes a novel methodology to visualize a classification scheme. It is demonstrated with the Association for Computing Machinery (ACM) Computing Classification System (CCS). The collection derived from the ACM digital library, containing 37,543 documents classified by CCS. The assigned classes, subject descriptors, and keywords were processed in a dataset to produce a graphical representation of the documents. The general conception is based on the similarity of co-classes (themes) proportional to the number of common publications. The final number of all possible classes and subclasses in the collection was 353 and therefore the similarity matrix of co-classes had the same dimension. A spherical surface was chosen as the target information space. Classes and documents' node locations on the sphere were obtained by means of Multidimensional Scaling coordinates. By representing the surface on a plane like a map projection, it is possible to analyze the visualization layout. The graphical patterns were organized in some colour clusters. For evaluation of given visualization maps, graphics filtering was applied. This proposed method can be very useful in interdisciplinary research fields. It allows for a great amount of heterogeneous information to be conveyed in a compact display, including topics, relationships among topics, frequency of occurrence, importance and changes of these properties over time.
  3. Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017) 0.04 
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    Abstract
    Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
  4. Braun, S.: Manifold: a custom analytics platform to visualize research impact (2015) 0.04 
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    Abstract
    The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.
  5. Zhang, J.; Zhao, Y.: ¬A user term visualization analysis based on a social question and answer log (2013) 0.03 
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    Abstract
    The authors of this paper investigate terms of consumers' diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers' perspective, and reveal users' diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.
  6. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.02 
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    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
  7. Osinska, V.; Kowalska, M.; Osinski, Z.: ¬The role of visualization in the shaping and exploration of the individual information space : part 1 (2018) 0.01 
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    Abstract
    Studies on the state and structure of digital knowledge concerning science generally relate to macro and meso scales. Supported by visualizations, these studies can deliver knowledge about emerging scientific fields or collaboration between countries, scientific centers, or groups of researchers. Analyses of individual activities or single scientific career paths are rarely presented and discussed. The authors decided to fill this gap and developed a web application for visualizing the scientific output of particular researchers. This free software based on bibliographic data from local databases, provides six layouts for analysis. Researchers can see the dynamic characteristics of their own writing activity, the time and place of publication, and the thematic scope of research problems. They can also identify cooperation networks, and consequently, study the dependencies and regularities in their own scientific activity. The current article presents the results of a study of the application's usability and functionality as well as attempts to define different user groups. A survey about the interface was sent to select researchers employed at Nicolaus Copernicus University. The results were used to answer the question as to whether such a specialized visualization tool can significantly augment the individual information space of the contemporary researcher.
    Date
    21.12.2018 17:22:13
  8. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.01 
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  9. Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010) 0.00 
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    Date
    22. 7.2010 19:36:46
  10. Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013) 0.00 
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    Date
    4. 2.2015 9:22:39
  11. Buchel, O.; Sedig, K.: Extending map-based visualizations to support visual tasks : the role of ontological properties (2011) 0.00 
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    Abstract
    Map-based visualizations of document collections have become popular in recent times. However, most of these visualizations emphasize only geospatial properties of objects, leaving out other ontological properties. In this paper we propose to extend these visualizations to include nongeospatial properties of documents to support users with elementary and synoptic visual tasks. More specifically, additional suitable representations that can enhance the utility of map-based visualizations are discussed. To demonstrate the utility of the proposed solution, we have developed a prototype map-based visualization system using Google Maps (GM), which demonstrates how additional representations can be beneficial.
  12. Salaba, A.; Mercun, T.; Aalberg, T.: Complexity of work families and entity-based visualization displays (2018) 0.00 
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    Abstract
    Conceptual modeling of bibliographic data, including the FR models and the consolidated IFLA LRM, has provided an opportunity to shift focus to entities and relationships and to support hierarchical work-based exploration of bibliographic information. This paper reports on a study examining the complexity of a work's bibliographic family data and user interactions with data visualizations, compared to traditional displays. Findings suggest that the FRBR-based visual bibliographic information system supports work families of different complexities more equally than a traditional system. Differences between the two systems also show that the FRBR-based system was more effective especially for related-works and author-related tasks.
  13. Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016) 0.00 
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    Date
    20. 1.2015 18:30:22
  14. Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018) 0.00 
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    Date
    9.12.2018 16:22:25
  15. Zhu, Y.; Yan, E.; Song, I.-Y..: ¬The use of a graph-based system to improve bibliographic information retrieval : system design, implementation, and evaluation (2017) 0.00 
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    Abstract
    In this article, we propose a graph-based interactive bibliographic information retrieval system-GIBIR. GIBIR provides an effective way to retrieve bibliographic information. The system represents bibliographic information as networks and provides a form-based query interface. Users can develop their queries interactively by referencing the system-generated graph queries. Complex queries such as "papers on information retrieval, which were cited by John's papers that had been presented in SIGIR" can be effectively answered by the system. We evaluate the proposed system by developing another relational database-based bibliographic information retrieval system with the same interface and functions. Experiment results show that the proposed system executes the same queries much faster than the relational database-based system, and on average, our system reduced the execution time by 72% (for 3-node query), 89% (for 4-node query), and 99% (for 5-node query).
  16. Batorowska, H.; Kaminska-Czubala, B.: Information retrieval support : visualisation of the information space of a document (2014) 0.00 
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    Source
    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
  17. Soylu, A.; Giese, M.; Jimenez-Ruiz, E.; Kharlamov, E.; Zheleznyakov, D.; Horrocks, I.: Towards exploiting query history for adaptive ontology-based visual query formulation (2014) 0.00 
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    Abstract
    Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed.
  18. Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014) 0.00 
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    Abstract
    The paper investigates the acceleration of t-SNE-an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots-using two tree-based algorithms. In particular, the paper develops variants of the Barnes-Hut algorithm and of the dual-tree algorithm that approximate the gradient used for learning t-SNE embeddings in O(N*logN). Our experiments show that the resulting algorithms substantially accelerate t-SNE, and that they make it possible to learn embeddings of data sets with millions of objects. Somewhat counterintuitively, the Barnes-Hut variant of t-SNE appears to outperform the dual-tree variant.
  19. Sahib, N.G.; Tombros, A.; Stockman, T.: Evaluating a search interface for visually impaired searchers (2015) 0.00 
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    Abstract
    Understanding the information-seeking behavior of visually impaired users is essential to designing search interfaces that support them during their search tasks. In a previous article, we reported the information-seeking behavior of visually impaired users when performing complex search tasks on the web, and we examined the difficulties encountered when interacting with search interfaces via speech-based screen readers. In this article, we use our previous findings to inform the design of a search interface to support visually impaired users for complex information seeking. We particularly focus on implementing TrailNote, a tool to support visually impaired searchers in managing the search process, and we also redesign the spelling-support mechanism using nonspeech sounds to address previously observed difficulties in interacting with this feature. To enhance the user experience, we have designed interface features to be technically accessible as well as usable with speech-based screen readers. We have evaluated the proposed interface with 12 visually impaired users and studied how they interacted with the interface components. Our findings show that the search interface was effective in supporting participants for complex information seeking and that the proposed interface features were accessible and usable with speech-based screen readers.
  20. Minkov, E.; Kahanov, K.; Kuflik, T.: Graph-based recommendation integrating rating history and domain knowledge : application to on-site guidance of museum visitors (2017) 0.00 
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    Abstract
    Visitors to museums and other cultural heritage sites encounter a wealth of exhibits in a variety of subject areas, but can explore only a small number of them. Moreover, there typically exists rich complementary information that can be delivered to the visitor about exhibits of interest, but only a fraction of this information can be consumed during the limited time of the visit. Recommender systems may help visitors to cope with this information overload. Ideally, the recommender system of choice should model user preferences, as well as background knowledge about the museum's environment, considering aspects of physical and thematic relevancy. We propose a personalized graph-based recommender framework, representing rating history and background multi-facet information jointly as a relational graph. A random walk measure is applied to rank available complementary multimedia presentations by their relevancy to a visitor's profile, integrating the various dimensions. We report the results of experiments conducted using authentic data collected at the Hecht museum. An evaluation of multiple graph variants, compared with several popular and state-of-the-art recommendation methods, indicates on advantages of the graph-based approach.

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