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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
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SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Semantic tagging for crowd computing
Roberto Mirizzi1, Azzurra Ragone1,2, Tommaso Di Noia1, Eugenio Di Sciascio1
1Politecnico di BariVia Orabona, 470125 Bari (ITALY)
2University of TrentoVia Sommarive, 14
38100 Trento (ITALY)
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Who is using tags?
and many
more…
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Why not to use Semantic tags?
Plugged into the Web 3.0DisambiguationRelations among tagsMachine understandable
NOT: Not Only Tag
http://sisinflab.poliba.it/not-only-tag/
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
DBpedia-Ranker: architectureSystem 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
1
2
3
1
2
3
SPARQL
Runtime searchOffline classification
1
External Information
Sources
2 3
1
2 3
STORAGE
Delicious
Yahoo!
GRAPH EXPLORER
RANKER
DBpedia
TAGS
WEB INTERFACE
Bing
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
DBpedia-Ranker: ranking
?r1 ?r2isSimilar
v
hasValue
)(
),(
)(
),(),(
2
21
1
2121 rf
rrf
rf
rrfrrsim
),()()(
),(),(
2121
2121 rrfrfrf
rrfrrcoOcc
)}(log),(min{loglog
),(log)(log),(logmax),(
21
212121 rfrfN
rrfrfrfrrngd
viceversaand r and rbetween wikilink,2
saor vicever r and rbetween k wikilin,1
r and rbetween wikilink no ,0
),(
21
21
21
21 rrorewikilinkSc
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1221 rl
rrlrroreabstractSc
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
DBpedia-Ranker: context analysis
The same similarity measure is used in the context analysis
?r1
?c1
belongsTo
v
hasValue
?c2
?c…
?cN
C
Example:
C = {Programming Languages, Databases, Software}
Does Dennis Ritchie belongs to the given context?
Algorithm:
If(v>THRESHOLD) then r1 belongs to the context; add r1 to the graph exploration queueElse r1 does not belong to the context; exclude r1 from graph explorationEndIf
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Evaluation (I)
http://sisinflab.poliba.it/evaluation
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Evaluation (II)
http://sisinflab.poliba.it/evaluation/data
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Future work
Test our algorithms with different domains
Extract more fine grained contexts
Enrich the extracted context using also relevant properties
Integrate our approach with real existing systems
Use the core system to automatically extract relevant tags (concepts) from a document (or from a collection of documents) exploiting tools for named entities extraction
SEBD 2010 - Holiday Inn Hotel, RiminiJune 21, 2010
Q&A
Semantic tagging for crowd computingRoberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciascio
mirizzi@deemail.poliba.it, ragone@disi.unitn.it, {ragone,dinoia,disciascio}@poliba.it
Thank you for your attention!
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