• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Semantic tagging for crowd computing - SEBD 2010
 

Semantic tagging for crowd computing - SEBD 2010

on

  • 812 views

The recent blow up of crowd computing initiatives on the web calls for smarter methodologies and tools to annotate, query and explore repositories. ...

The recent blow up of crowd computing initiatives on the web calls for smarter methodologies and tools to annotate, query and explore repositories.
There is the need for scalable techniques able to return also approximate results with respect to a given query as a ranked set of promising alternatives.
In this paper we concentrate on annotation and retrieval of software components, exploiting semantic tagging relying on DBpedia.
We propose a new hybrid methodology to rank resources in this dataset. Inputs of our ranking system are (i) the DBpedia dataset; (ii) external information sources such as classical search engine results, social tagging systems and wikipedia-related information.
We compare our approach with other RDF similarity measures, proving the validity of our algorithm with an extensive evaluation involving real users.
The system is available at http://sisinflab.poliba.it/not-only-tag/

SEBD 2010 - 18th Italian Symposium on Advanced Database Systems

presented by Roberto Mirizzi (http://sisinflab.poliba.it/mirizzi -
roberto.mirizzi -at- gmail.com)

Rimini (ITALY), June 20-23, 2010

Statistics

Views

Total Views
812
Views on SlideShare
778
Embed Views
34

Actions

Likes
0
Downloads
5
Comments
0

4 Embeds 34

http://sisinflab.poliba.it 28
http://localhost 3
http://www.linkedin.com 2
https://www.linkedin.com 1

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Semantic tagging for crowd computing - SEBD 2010 Semantic tagging for crowd computing - SEBD 2010 Presentation Transcript

    • Semantictaggingforcrowdcomputing
      Roberto Mirizzi1, Azzurra Ragone1,2,
      Tommaso Di Noia1, Eugenio Di Sciascio1
      1Politecnico di Bari
      Via Orabona, 4
      70125 Bari (ITALY)
      2Universityof Trento
      Via Sommarive, 14
      38100 Trento (ITALY)
    • Who is using tags?
      and manymore…
    • WhynottouseSemantictags?
      Pluggedinto the Web 3.0
      Disambiguation
      Relations amongtags
      Machineunderstandable
      NOT:NotOnlyTag
      http://sisinflab.poliba.it/not-only-tag/
    • DBpedia-Ranker: architecture
      Runtimesearch
      Offline classification
      System architecture
      Linked Data graph exploration
      Rank nodes exploiting
      external information
      Store results as pairs of nodes together with their similarity
      Start typing a tag
      Query the system for relevant tags (corresponding to DBpedia resources)
      Show the semantic tag cloud
      DBpedia
      1
      2
      1
      SPARQL
      3
      1
      1
      GRAPH EXPLORER
      TAGS
      ExternalInformation Sources
      2
      3
      2
      3
      Google
      3
      2
      WEB INTERFACE
      STORAGE
      Yahoo!
      RANKER
      Bing
      Delicious
    • DBpedia-Ranker: ranking
      ?r1
      ?r2
      isSimilar
      hasValue
      v
    • DBpedia-Ranker: contextanalysis
      The samesimilaritymeasureisused in the contextanalysis
      C
      ?c1
      Algorithm:
      If(v>THRESHOLD) then
      r1belongsto the context;
      add r1to the graphexplorationqueue
      Else
      r1doesnotbelongto the context;
      exclude r1fromgraphexploration
      EndIf
      ?c2
      belongsTo
      ?r1
      ?c…
      ?cN
      hasValue
      Example:
      C = {ProgrammingLanguages, Databases, Software}
      DoesDennis Ritchiebelongsto the givencontext?
      v
    • Evaluation (I)
      http://sisinflab.poliba.it/evaluation
    • Evaluation (II)
      http://sisinflab.poliba.it/evaluation/data
    • Future work
      • Test ouralgorithmswithdifferentdomains
      • Extract more fine grainedcontexts
      • Enrich the extractedcontextusingalsorelevantproperties
      • Integrateourapproachwithrealexistingsystems
      • Use the core system toautomaticallyextractrelevanttags (concepts) from a document (or from a collectionofdocuments) exploitingtoolsfornamedentitiesextraction
    • Q&A
      Thankyouforyourattention!
      Semantictaggingforcrowdcomputing
      Roberto Mirizzi, AzzurraRagone, Tommaso Di Noia, Eugenio Di Sciascio
      mirizzi@deemail.poliba.it, ragone@disi.unitn.it, {ragone,dinoia,disciascio}@poliba.it