• Like
Semantic tagging for crowd computing - SEBD 2010
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

Semantic tagging for crowd computing - SEBD 2010

  • 571 views
Published

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

Published in Technology , Education
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
571
On SlideShare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
6
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. 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)
  • 2. Who is using tags?
    and manymore…
  • 3. WhynottouseSemantictags?
    Pluggedinto the Web 3.0
    Disambiguation
    Relations amongtags
    Machineunderstandable
    NOT:NotOnlyTag
    http://sisinflab.poliba.it/not-only-tag/
  • 4. 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
  • 5. DBpedia-Ranker: ranking
    ?r1
    ?r2
    isSimilar
    hasValue
    v
  • 6. 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
  • 7. Evaluation (I)
    http://sisinflab.poliba.it/evaluation
  • 8. Evaluation (II)
    http://sisinflab.poliba.it/evaluation/data
  • 9. Future work
    • Test ouralgorithmswithdifferentdomains
    • 10. Extract more fine grainedcontexts
    • 11. Enrich the extractedcontextusingalsorelevantproperties
    • 12. Integrateourapproachwithrealexistingsystems
    • 13. 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