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Web Information Systems 2011 project

Web Information Systems 2011 project



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    Wis2011_presentation_Realtime_Events_on_LOD Wis2011_presentation_Realtime_Events_on_LOD Presentation Transcript

    • RealTime Social Events on Linked Open Data(LOD) Pramod Koneru, Dylan Williams
    • Event Summarization Not Real-Time Semantics Web Technologies Amit Sheth,Hemant Purohit,Ashutosh Jadhav,Pavan Kapanipathi,Lu Chen -- Understanding Events Through Analysis Of Social Media
    • Motivation
      • Real-Time architecture
      • Use of Semantics in Real-time
    • TWARQL (2010)
      • Streaming Annotated tweets
        • Transforms tweets to RDF
          • DBPedia Entities, URLs, metadata from twitter
      • Real-Time
      • Filter Tweets using SPARQL Queries
      Pablo N.Mendes, Pavan Kapanipathi, Alexandre Passant -- Twarql: Tapping into the Wisdom of the Crowd Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi and Amit P. Sheth -- Linked Open Social Signals
    • Concept Feeds Real-Time filtering of twitter feeds based on concepts
    • Event Centric Filtering
      • Twitris + Twarql
      • Streaming Tweets based on Twitris Event Descriptors
        • Transform them to RDF
      • SPARQL (SPARQL 1.1) Queries to filter tweets
        • Faceted Search
    • Scenario Give me the names of People and Organization mentioned in the past two hours related to India Against Corruption Journalist
    • Scenario – SPARQL 1.1 SELECT ?obj (COUNT(?obj) as ?occurrence) FROM <Event Graph -- IAC> WHERE { { SELECT ?obj WHERE { {?obj a < http://dbpedia.org/ontology/Person > } Union { ?obj a < http://dbpedia.org/ontology/Organization > } } } ?tweetid moat:taggedwith ?obj ?tweetid dc:created ?date FILTER { ?date < “ current time ” ^^xsd:date && ?date > “ current time - 2hrs ” ^^xsd:date } } GOURP BY ?obj
    • Twitris Event Descriptors Metadata Extractions RDF Transformations Twitter Storm (Future Extension) RDF Store Architecture
    • Tasks (Pramod)
      • Metadata Extractions/Identification
        • Twarql (A year back) metadata not enough
        • Twitter provides more metadata
          • Entities, URL mentions, user mentions.
      • Schema for the extra Metadata
      • Transform to RDF
      • SPARQL 1.1 Queries for Concept Feed
    • Visualisation
      • Real-Time Visualization of RDF Graphs
      • Top Entities for each event with their relationships
      • Weighted entities
    • Tasks (Dylan)
      • Research on Visualization Libraries from the Web
      • Implement to display JSON data
      • Extend the library for specific needs of project
      • Style the graph (make it look presentable, professional)
      • Implement “pull data” function that serializes data from RDF to JSON
    • Future Work
      • Integrate our work with
        • Kurtis – Work on Twitter Storm
        • Maria – Work on Alchemy API for entity Extraction
    • Thanks
    • SPARQl 1.1
      • A new SPARQL WG was chartered in March 2009 to extend the SPARQL language and landscape. SPARQL 1.1 Query includes these extensions:
      • Projected expressions . SPARQL 1.1 Query adds the ability for query results to contain values derived from constants, function calls, or other expressions in the SELECT list.
      • Aggregates . SPARQL 1.1 Query adds the ability to group results and calculate aggregate values (e.g. count, min, max, avg, sum, ...).
      • Subqueries . SPARQL 1.1 Query allows one query to be embedded within another.
      • Negation . SPARQL 1.1 Query includes improved language syntax for querying negations.
      • Property paths . SPARQL 1.1 Query adds the ability to query arbitrary length paths through a graph via a regular-expression-like syntax known as property paths.
      • Basic federated query . SPARQL 1.1 Query defines a mechanism for splitting a single query among multiple SPARQL endpoints and combining together the results from each