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DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
LivingKnowledge Project




  http://livingknowledge-project.eu

   • EC FP7 FET Proposal
   • CALL 6 ICT Forever Yours


   DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Consortium
•   UNIVERSITÀ DEGLI STUDI DI TRENTO, Trento - ITALY
•   FUNDACIÓ BARCELONA MEDIA UNIVERSITAT POMPEU FABRA,
    Barcelona – SPAIN
•   SORA, Vienna – AUSTRIA
•   CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE
    TELECOMUNICAZIONI, Parma ITALY
•   STICHTING EUROPEAN ARCHIVE, Amsterdam – NETHERLANDS
•   UNIVERSITÀ DEGLI STUDI DI PAVIA, Pavia – ITALY
•   UNIVERSITY OF SOUTHAMPTON, Southampton, UNITED
    KINDOM
•   DOCUMENTATION RESEARCH AND TRAINING CENTRE, INDIAN
    STATISTICAL INSTITUTE, Bangalore, INDIA
•   GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET Hannover,
    GERMANY.
•   MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER
    WISSENSCHAFTEN E.V., Muenchen – GERMANY.
Objectives

 Investigate diverse disciplines with a view to
  a multi-disciplinary understanding of evolution,
  diversity and bias, and their impact on
  knowledge;

 Develop a formal knowledge model which
  makes it possible to represent, manage and
  maintain over time knowledge that reflects
  evolution, diversity and bias.


          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Goals

•    Creating a deep understanding of
     diversity
    – interdisciplinary approach combining
        know-how and experiences from
        areas such as media research,
        multimodal information theory, library
        science, natural language processing
        and multimedia data analysis


          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Goals

•   Developing methods of detecting Bias
•   Exploring the temporal dimension of
    diversity
•   Making bias, diversity and evolution
    tangible and digestible by a new
    generation of search technologies that
    supports opinion-aware, diversity-aware
    and time-aware aggregation and
    exploration of knowledge

         DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Research Challenges



Information Extraction: extraction of facts and
entities from web pages and documents,
opinion mining, integration of related and
complementary knowledge fragments




          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Research Challenges



Understanding and detecting bias and
diversity: which includes understanding
interdisciplinary foundation of diversity and bias
expressed in text and multimedia




          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Research Challenges


Knowledge Evolution: which includes
analysis of evolution of classification
patterns and hierarchies; opinion
evolution; diversity aware knowledge
representation etc



        DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Research Challenges



Enhanced search and retrieval technology:
which includes information aggregation and
summarization




         DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Research Areas - RAs

RA1: Foundations of Evolution, Diversity and
  Bias in knowledge
RA2: Information Extraction
RA3: Knowledge Evolution
RA4: Bias and Diversity
RA5: Clustering and Aggregation
RA6: Enhanced Search and Retrieval
        Technology


          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
The proposed framework
                             Media Content Analysis


                                    Research
                                    questions

                                           STATISTICAL ANALYSIS


        Facet Analysis
                                  CODEBOOK
                                                         FEATURE
                                variables
                                                       EXTRACTION
                                indicators
         FACETED
      CLASSIFICATIONS

                                           ANNOTATION




             DOCUMENT
              CORPUS                                   Multimodal
                                                      Genre Analysis




                  DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Raw Data                             Human
                                         Representation
                                                      Annotators
      Subjective Sentence                                Fact:
      - Can be explicit/implicit                         -Source independent
      -has polarity / intensity       Statement
                                      -Time dependent    -No polarity by itself
      (pos-neg)                                          -Can be true/false
      -can have many                  (changes over
                                      time)              -has values (measures)
      diversity dimensions                               -could be represented as
      -can be expressed with                             vector
      images (or manipulation                            -has no bias (the source
      of images)                                         could be biased by
                                                         presenting olnly some
Opinion                                                  facts)
Source:                                                  -can be expressed with
                                   Relevance             images (and manipolation
Journalist,     Opinion Leader:
community,                                               can be objective)
                Analysing time      Query
organization... dimension?
                                                          (Opinion) Target: entities,
                                                          persons, abstract topic
                                    13                             16. Februar 2010
Media Content Analyzer (MCA)



 LK MCA to emulate the SORA method




       DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Multi-pronged approach
•   Bias and Diversity detection: L3S
•   Evolution studies and modeling: Max Plank Institute
•   Multimodal Semiotic Analysis: Pavia
•   Multimedia Media Analysis: CNIT, Southampton
•   Facet Modeling : DRTC/ISI and Unitn
•   Image Forensics and analysis: CNIT and Southampton
•   Media Content analysis: SORA
•   Future Predictor: Yahoo!
•   Multi-domain data sets: European Archives




           DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Future Predictor
•   Searching the future: searching current
    references for explicit mentions of plans
    and estimates for future events
•   Predicting the future: Inferring new implicit
    future events based on past occurrences,
    trends and plans for the future
•   Mining the future(temporal evolution) :
    finding the most important topics
    associated with a given time segment.

          DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
Thank you!

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Diversiweb2011 02 Opening- Devika P. Madalli

  • 1. DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 2. LivingKnowledge Project http://livingknowledge-project.eu • EC FP7 FET Proposal • CALL 6 ICT Forever Yours DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 3. Consortium • UNIVERSITÀ DEGLI STUDI DI TRENTO, Trento - ITALY • FUNDACIÓ BARCELONA MEDIA UNIVERSITAT POMPEU FABRA, Barcelona – SPAIN • SORA, Vienna – AUSTRIA • CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI, Parma ITALY • STICHTING EUROPEAN ARCHIVE, Amsterdam – NETHERLANDS • UNIVERSITÀ DEGLI STUDI DI PAVIA, Pavia – ITALY • UNIVERSITY OF SOUTHAMPTON, Southampton, UNITED KINDOM • DOCUMENTATION RESEARCH AND TRAINING CENTRE, INDIAN STATISTICAL INSTITUTE, Bangalore, INDIA • GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET Hannover, GERMANY. • MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V., Muenchen – GERMANY.
  • 4. Objectives  Investigate diverse disciplines with a view to a multi-disciplinary understanding of evolution, diversity and bias, and their impact on knowledge;  Develop a formal knowledge model which makes it possible to represent, manage and maintain over time knowledge that reflects evolution, diversity and bias. DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 5. Goals • Creating a deep understanding of diversity – interdisciplinary approach combining know-how and experiences from areas such as media research, multimodal information theory, library science, natural language processing and multimedia data analysis DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 6. Goals • Developing methods of detecting Bias • Exploring the temporal dimension of diversity • Making bias, diversity and evolution tangible and digestible by a new generation of search technologies that supports opinion-aware, diversity-aware and time-aware aggregation and exploration of knowledge DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 7. Research Challenges Information Extraction: extraction of facts and entities from web pages and documents, opinion mining, integration of related and complementary knowledge fragments DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 8. Research Challenges Understanding and detecting bias and diversity: which includes understanding interdisciplinary foundation of diversity and bias expressed in text and multimedia DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 9. Research Challenges Knowledge Evolution: which includes analysis of evolution of classification patterns and hierarchies; opinion evolution; diversity aware knowledge representation etc DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 10. Research Challenges Enhanced search and retrieval technology: which includes information aggregation and summarization DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 11. Research Areas - RAs RA1: Foundations of Evolution, Diversity and Bias in knowledge RA2: Information Extraction RA3: Knowledge Evolution RA4: Bias and Diversity RA5: Clustering and Aggregation RA6: Enhanced Search and Retrieval Technology DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 12. The proposed framework Media Content Analysis Research questions STATISTICAL ANALYSIS Facet Analysis CODEBOOK FEATURE variables EXTRACTION indicators FACETED CLASSIFICATIONS ANNOTATION DOCUMENT CORPUS Multimodal Genre Analysis DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 13. Raw Data Human Representation Annotators Subjective Sentence Fact: - Can be explicit/implicit -Source independent -has polarity / intensity Statement -Time dependent -No polarity by itself (pos-neg) -Can be true/false -can have many (changes over time) -has values (measures) diversity dimensions -could be represented as -can be expressed with vector images (or manipulation -has no bias (the source of images) could be biased by presenting olnly some Opinion facts) Source: -can be expressed with Relevance images (and manipolation Journalist, Opinion Leader: community, can be objective) Analysing time Query organization... dimension? (Opinion) Target: entities, persons, abstract topic 13 16. Februar 2010
  • 14. Media Content Analyzer (MCA) LK MCA to emulate the SORA method DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 15. Multi-pronged approach • Bias and Diversity detection: L3S • Evolution studies and modeling: Max Plank Institute • Multimodal Semiotic Analysis: Pavia • Multimedia Media Analysis: CNIT, Southampton • Facet Modeling : DRTC/ISI and Unitn • Image Forensics and analysis: CNIT and Southampton • Media Content analysis: SORA • Future Predictor: Yahoo! • Multi-domain data sets: European Archives DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad
  • 16. Future Predictor • Searching the future: searching current references for explicit mentions of plans and estimates for future events • Predicting the future: Inferring new implicit future events based on past occurrences, trends and plans for the future • Mining the future(temporal evolution) : finding the most important topics associated with a given time segment. DiversiWeb2011 Workshop on Knowledge Diversity, Mar 28 th,2011, Hyderabad