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DIVINE Research Project

WU Wien, webLyzard technology, MODUL University Vienna, Know-Center, Gentics

FIT-IT Semantic Systems Program Line
Dynamic Integration and Visualization of Information
from Multiple Evidence Sources

www.weblyzard.com/divine/

Content providers and analysts alike increasingly rely on combining multiple data sources to build comprehensive, up-to-date and properly interlinked information spaces. These organizations critically depend on technologies for integrating these sources and tracking their evolution.

DIVINE aims to provide such technologies, with a lightweight seed ontology acting as the focal point for integrating new evidence derived from multiple, evolving data sources. As such, the project advances ontology evolution research characterized by single-source solutions, which exploit mostly textual and rather static data. DIVINE integrates structured and unstructured information resources. A modular and scalable portfolio of evidence acquisition services crawls public Web documents, queries Linked Open Data repositories, aggregates resource annotations from social media, and triggers validation processes for missing or conflicting evidence. Since evidence from third-party sources is inherently uncertain, source-specific transformation rules and impact factors assign a confidence value to each new fact. A spreading activation network utilizes the collected evidence in conjunction with the confidence values for extending the seed ontology.

Knowledge Evolution Patterns

DIVINE will monitor domain changes over time to derive knowledge evolution patterns. This domain-centric view makes DIVINE novel among existing change detection approaches, which tend to be domain-agnostic. Each ontology element is assigned a confidence matrix, which records the changes in confidence values over time. Data services and dynamic visualizations reveal rising, declining or cyclic patterns in the confidence matrices. Such patterns are important indicators – the rate of change or the date of a concept’s first appearance, for example, shed light on the evolution of knowledge and on the underlying processes that drive this evolution.

Use Cases and Prototypes

Two use cases on news media monitoring and environmental knowledge management demonstrate and evaluate the system’s capabilities to structure large knowledge repositories in a scalable manner, uncover and manage flows of relevant information between stakeholders, and measure how well an organization’s external communication is received, understood, and remembered. The use cases will be pursued in close collaboration with the project’s industry and associate partners.

Refereed Publications

  • Braşoveanu, A.M.P., Hubmann-Haidvogel, A. and Scharl, A. (2012). Interactive Visualization of Emerging Topics in Multiple Social Media Streams. ACM Working Conference on Advanced Visual Interfaces (AVI-2012). G. Tortora et al. Capri, Italy: ACM: 530-533.
  • Hubmann-Haidvogel, A., Brasoveanu, A., Scharl, A., Sabou, M. and Gindl, S. (2012). Visualizing Contextual and Dynamic Features of Micropost Streams. 2nd Workshop on Making Sense of Microposts (MSM-2012), 21st International World Wide Web Conference. M. Rowe et al. Lyon, France: CEUR Proceedings: 34-40.
  • Scharl, A., Hubmann-Haidvogel, A., Weichselbraun, A., Wohlgenannt, G., Lang, H.-P. and Sabou, M. (2012). Extraction and Interactive Exploration of Knowledge from Aggregated News and Social Media Content. ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS-2012). J.C. Campos et al. Copenhagen, Denmark: Association for Computing Machinery: 163-168.
  • Scharl, A., Sabou, M., Gindl, S., Rafelsberger, W. and Weichselbraun, A. (2012). Leveraging the Wisdom of the Crowds for the Acquisition of Multilingual Language Resources. 8th International Conference on Language Resources and Evaluation (LREC-2012). N. Calzolari et al. Instanbul, Turkey: European Language Resources Association: 379-383.
  • Syed, K.A.A., Kröll, M., Sabol, V., Scharl, A., Gindl, S., Granitzer, M. and Weichselbraun, A. (2012). Dynamic Topography Information Landscapes – An Incremental Approach to Visual Knowledge Discovery. 14th International Conference on Data Warehousing and Knowledge Discovery (DaWaK-2012). Vienna, Austria: Forthcoming.
  • Wohlgenannt, G., Weichselbraun, A., Scharl, A. and Sabou, M. (2012). Confidence Management for Learning Ontologies from Dynamic Web Sources. 4th International Conference on Knowledge Engineering and Ontology Development (KEOD-2012). Barcelona, Spain: Forthcoming.

Project Partners

    • Research Institute for Computational Methods,
      Vienna University of Economics & Business
    • Department of New Media Technology,
      MODUL University Vienna (Sub-Contractor)
    • Know-Center GmbH
    • Gentics Software GmbH
    • webLyzard Technology GmbH
https://www.weblyzard.com/data/sites/21/divine-logo-square.png 180 180 Arno Scharl https://www.weblyzard.com/data/sites/21/weblyzard-logo-2020.png Arno Scharl2013-04-23 21:12:132021-05-08 17:22:30DIVINE Research Project
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About

webLyzard technology is an Austrian SME founded in 2008. The unique capabilities of its big data platform are based on a strong R&D track record in the fields of knowledge extraction, artificial intelligence, visualization and the integration of geospatial and semantic Web technologies.

web·Lyz·ard

Function: intelligence platform; Etymology: composed from web (as in World Wide Web) and lyzard (as in analyzer). 1 : (broadly) enriches digital content; identified by its speed, accuracy and scalability. 2 : predicts trends to gain a deeper understanding of information flows.

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