Tagonto Otm
Upcoming SlideShare
Loading in...5
×
 

Tagonto Otm

on

  • 399 views

 

Statistics

Views

Total Views
399
Views on SlideShare
399
Embed Views
0

Actions

Likes
0
Downloads
1
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

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

Tagonto Otm Tagonto Otm Presentation Transcript

  • 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
  • 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
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Introduction Aim: Improve web search and navigation
  • 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.
  • 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. • Reflect collective intelligence and emergent semantics. • Tipically unstructured and uncontrolled.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Tagonto Overview Tagonto can be described as a folksonomy aggregator which offers:
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Tagonto Overview Tagonto can be described as a folksonomy aggregator which offers: Tagonto Functionalities • A tag-based search engine. • Ontology-based query refinement. • Visual, ontology-based navigation of tags.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Tagonto Overview Tagonto can be described as a folksonomy aggregator which offers: Tagonto Functionalities • A tag-based search engine. • Ontology-based query refinement. • 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) refine the query and repeat from 2.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Matching tags and concepts Definition: 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.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Matching tags and concepts Definition: 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. Definition: Matching • A matching between O and F is defined as a relation M⊆F ×C allowing multiple associations among tags and concepts. • ∀m ∈ M we associate a similarity degree s : F × C → [0, 1]
  • 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.
  • 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.
  • 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
  • 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.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Disambiguation The disambiguation process is carried out in two steps:
  • 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.
  • 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 filters: e.g., top-k, treshold, etc. 2. Semantic filters (i.e., ontology-based disambiguation)
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Ontology-based disambiguation Definition: Root concepts Any concept in O associated to tags in F by means of M
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Ontology-based disambiguation Definition: 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 α · i ; decrease of the same factor otherwise. • selects the matching with maximum similarity degree.
  • 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.
  • 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.
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work User Interface
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Performance I We measured Tagonto’s response time during: • Ontology loading 800 800 700 700 600 600 500 500 time(s) time(s) 400 400 300 300 200 200 100 100 0 0 0 200 400 600 800 1000 1200 1400 1600 0 200 400 600 800 1000 1200 #CONCEPTS + #INSTANCES  INSTANCES + #PROPERTIES
  • Introduction Tagonto Overview Matching and Disambiguation Tagonto Implementation Conclusion and Future Work Performance II • Matching generation and resources retrieval 100 80 response time(s) 60 40 20 0 0 50 100 150 200 250 300 350 trial
  • 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.
  • 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.
  • 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?