1. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work TagOnto Improving
Search and Navigation by Combining Ontologies and Social Tags S.
Bindelli1 , C. Criscione2 , C. A. Curino3 , M. L. Drago3 , D.
Eynard3 ,G. Orsi3 1 Trussardi Company 2 Secure Network S.r.l. 3
Politecnico di Milano ADI Workshop (OTM 2008) Monterrey (Mexico)
November 9, 2008
2. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Outline
Introduction Tagonto Overview Matching and Disambiguation Tagonto
Implementation Conclusion and Future Work
3. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Introduction Aim:
Improve web search and navigation
4. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Introduction Aim:
Improve web search and navigation The high road: The Semantic Web
Mediates the access to existing sources by means of explicit
representation of data semantics (i.e., RDF and OWL). High
switching costs when moving from traditional technologies.
Implementers with considerable skills.
5. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Introduction Aim:
Improve web search and navigation The high road: The Semantic Web
Mediates the access to existing sources by means of explicit
representation of data semantics (i.e., RDF and OWL). High
switching costs when moving from traditional technologies.
Implementers with considerable skills. The low road: Folksonomies
Low commitment technology. Reect collective intelligence and
emergent semantics. Tipically unstructured and uncontrolled.
6. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Tagonto Overview
Tagonto can be described as a folksonomy aggregator which
oers:
7. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Tagonto Overview
Tagonto can be described as a folksonomy aggregator which oers:
Tagonto Functionalities A tag-based search engine. Ontology-based
query renement. Visual, ontology-based navigation of tags.
8. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Tagonto Overview
Tagonto can be described as a folksonomy aggregator which oers:
Tagonto Functionalities A tag-based search engine. Ontology-based
query renement. Visual, ontology-based navigation of tags. Search
process 1. Load a domain ontology O (metrics pre-computation). 2.
Search (keyword-based). 3. Navigate the results. 4. (optional)
add/remove/modify tags associated to Web resources. 5. (optional)
rene the query and repeat from 2.
9. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching tags and
concepts Denition: Folksonomy A Folksonomy in TagOnto is
represented as a set of pairs F = {(t1 , r1 ), . . . , (tn , rm )}
where ti is a term and rj is a web resource.
10. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching tags and
concepts Denition: Folksonomy A Folksonomy in TagOnto is
represented as a set of pairs F = {(t1 , r1 ), . . . , (tn , rm )}
where ti is a term and rj is a web resource. Denition: Matching A
matching between O and F is dened as a relation MF C allowing
multiple associations among tags and concepts. m M we associate a
similarity degree s : F C [0, 1]
11. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching Process
Given a folksonomy F and an ontology O, Tagonto: 1. accesses the
tags in F Web 2.0 APIs. RSS feeds parsing. Page scraping. 2.
matches the tags in F with ontology concepts and instances. 3. for
each tag, computes a set of related (co-occurrent) tags. 4.
disambiguates multiple matchings by updating their similarity
degrees.
12. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching Process
Given a folksonomy F and an ontology O, Tagonto: 1. accesses the
tags in F Web 2.0 APIs. RSS feeds parsing. Page scraping. 2.
matches the tags in F with ontology concepts and instances. 3. for
each tag, computes a set of related (co-occurrent) tags. 4.
disambiguates multiple matchings by updating their similarity
degrees.
13. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching
Computation Tagonto relies on an ontology mapper (X-SOM) to compute
the matchings Language-based Semantic Levenshtein Distance Google
Noise Correction Jaro Distance Wordnet Similarity Jaccard
Similarity Ontology Structure
14. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Matching
Computation Tagonto relies on an ontology mapper (X-SOM) to compute
the matchings Language-based Semantic Levenshtein Distance Google
Noise Correction Jaro Distance Wordnet Similarity Jaccard
Similarity Ontology Structure where: Google Noise: uses the Google
did you mean? functionality. WordNet Similarity: computes the
Leacock-Chodorow distance metric in WordNet.
15. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Disambiguation
The disambiguation process is carried out in two steps:
16. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Disambiguation
The disambiguation process is carried out in two steps:
Co-occurrent tags retrieval Using ontology relationships. Neighbors
in the tag-clouds. Google Tag-indexes.
17. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Disambiguation
The disambiguation process is carried out in two steps:
Co-occurrent tags retrieval Using ontology relationships. Neighbors
in the tag-clouds. Google Tag-indexes. Disambiguation 1. Simple
lters: e.g., top-k, treshold, etc. 2. Semantic lters (i.e.,
ontology-based disambiguation)
18. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Ontology-based
disambiguation Denition: Root concepts Any concept in O associated
to tags in F by means of M
19. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Ontology-based
disambiguation Denition: Root concepts Any concept in O associated
to tags in F by means of M For each multiple matching m M, Tagonto:
matches co-occurrent tags with the concepts in the ontology.
constructs a vector of connectivity degrees v, such that v[i] is
equal to the number of concepts associated to co-occurrent tags and
connected to the root concept i in the ontology. v[i] computes a
correction factor i = max(v) . if i avg(v) then increase the
matching degree of the matching associated to i by a factor i ;
decrease of the same factor otherwise. selects the matching with
maximum similarity degree.
20. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Architecture I
TagontoLIB: Matching algorithms Disambiguation TagontoNET: Core
search engine functionalities. Ontology loading. Plugin-based
communication interfaces with folksonomies.
21. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Architecture II
TagontoWEB: Results Navigation by co-occurent tags. by navigating
ontology concepts. Tags maintenance.
22. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work User
Interface
24. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Performance II
Matching generation and resources retrieval 100 80 responsetime(s)
60 40 20 0 0 50 100 150 200 250 300 350 trial
25. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Conclusion and
Future Work Contributions A search engine which combines ontologies
and tags. A library to compute matchings between tags and ontology
concepts. A service-oriented architecture for folksonomy querying
and aggregation.
26. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Conclusion and
Future Work Contributions A search engine which combines ontologies
and tags. A library to compute matchings between tags and ontology
concepts. A service-oriented architecture for folksonomy querying
and aggregation. Future Work Dynamic ontology loading. Automatic
tagging of Web resources.
27. Introduction Tagonto Overview Matching and Disambiguation
Tagonto Implementation Conclusion and Future Work Thank you More
information at:
http://kid.dei.polimi.it/mediawiki/index.php/TagOnto
Questions?