wis2011_presentation_realtime_events_on_lod

RealTime Social Events onLinked 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

ScenarioGive me the names of Give me the names of

People and People and Organization Organization

mentioned in the past mentioned in the past two hours related to two hours related to

India Against India Against CorruptionCorruption

Journalist

Scenario – SPARQL 1.1SELECT ?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 ?dateFILTER {

?date < “current time”^^xsd:date &&?date > “current time - 2hrs”^^xsd:date}

} GOURP BY ?obj

TwitrisEvent

Descriptors

MetadataExtractions

RDFTransformati

ons

Twitter Storm

(Future Extension)

RDFStore

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