Folksonomy based collabulary learning
This presentation is the property of its rightful owner.
Sponsored Links
1 / 26

Folksonomy-Based Collabulary Learning PowerPoint PPT Presentation


  • 37 Views
  • Uploaded on
  • Presentation posted in: General

Folksonomy-Based Collabulary Learning. Leandro Balby Marinho, Krisztian Buza, Lars Schmidt-Thieme {marinho,buza,[email protected] Information Systems and Machine Learning Lab (ISMLL) University of Hildesheim, Germany. Chill out. Classic Music. Jazz. Chopin.

Download Presentation

Folksonomy-Based Collabulary Learning

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Folksonomy based collabulary learning

Folksonomy-Based Collabulary Learning

Leandro Balby Marinho, Krisztian Buza, Lars Schmidt-Thieme

{marinho,buza,[email protected]

Information Systems and Machine Learning Lab (ISMLL)

University of Hildesheim, Germany


Motivation scenario

Chill out

Classic Music

Jazz

Chopin

Bossa Nova

Girl from Ipanema

Motivation Scenario


Motivation scenario1

Motivation Scenario


Outline

Outline

  • Problem Definition

  • Collabulary Learning

    • Folksonomy Enrichment

    • Frequent Itemset Mining for Ontology Learning from Folksonomies

  • Recommender Systems for Ontology Evaluation

  • Experiments and Results

  • Conclusions and future work


Problem definition

Problem Definition

  • Semantic Web suffers from knowledge bottleneck

  • Folksonomies can help

  • How?

    • Voluntary annotators

  • Educated towards shareable annotation

  • How?

    • Through a collabulary


Problem definition1

Problem Definition

  • “A possible solution to the shortcomings of folksonomies and controlled vocabulary is a collabulary, which can be conceptualized as a compromise between the two: a team of classification experts collaborates with content consumers to create rich, but more systematic content tagging systems.”

    Wikipedia article on Folksonomies

    (http://en.wikipedia.org/wiki/Folksonomy)


Problem definition2

Problem Definition

  • An ontology with concepts and a knowledge base with f is called a collabulary over and

  • Problem:

    • Learn a collabulary that best represents folksonomy and domain-expert vocabulary


Collabulary learning

Collabulary Learning


Folksonomy to trivial ontology

stuff_to_chill

Res 1

Res 2

Res 3

makes_me_happy

User 3

awesome_artists

User 2

User 4

Res 5

Res 7

Res 8

User 1

Folksonomy to trivial ontology

User

Resource

Tag


Matching concepts

Matching Concepts


Additional tag assignments

Res 5

User 1

stuff_to_chill

Res 1

alternative

Additional tag assignments


Expert conceptualization

Res 5

User 1

stuff_to_chill

Res 1

alternative

Expert

Res5

Res6

Res7

Res8

Res1

Res4

Rockabilly

Emo

Expert conceptualization


Frequent itemsets for learning ontologies from folksonomies

Frequent Itemsets for Learning Ontologies from Folksonomies

  • Most of the approaches rely on co-occurrence models

  • In sparse structures positive correlations carry essential information about the data

  • Project folksonomy to transactional database and use state of the art frequent itemsets mining algorithms


Frequent itemsets for learning ontologies from folksonomies1

Frequent Itemsets for Learning Ontologies from Folksonomies

  • Assumptions for relation extraction from frequent intemsets

    • High Level Tag

      • The more popular a tag is, the more general it is

      • A tag x is a super-concept of a tag y if there are frequent itemsets containing both tags such that sup({x})≥sup({y})

    • Frequency

      • The higher the support of an itemset, stronger correlated are the items on it

    • Large Itemset

      • Preference is given for items contained in larger itemsets


Frequent itemsets for learning ontologies from folksonomies2

Frequent Itemsets for Learning Ontologies from Folksonomies


Recommender systems for ontology evaluation

Recommender Systems for Ontology Evaluation

  • Ontologies can facilitate browsing, search and information finding in folksonomies

  • They should be evaluated in this respect

  • Recommender Systems are programs for personalized information finding

  • Let the recommender tell which is the best ontology


Recommender systems for ontology evaluation1

Recommender Systems for Ontology Evaluation

  • Task

    • Recommend useful resources

  • Application

    • Ontology-based collaborative filtering

  • Ontologies

    • A trivial ontology (folksonomy), domain-expert and collabulary

  • Gold Standard

    • Test Set

Porzel, R., Malaka, R.: A task-based approach for ontology evaluation. In: Proc. of ECAI 2004, Workshop on Ontology Learning and Population, Valencia, Spain


Recommender systems for ontology evaluation2

User 1

Res 1

User := (emo:=53.3, alternative:=26.6, rock:=13.3, root:=6.6)T

Recommender Systems for Ontology Evaluation

User 1 := (res1:=1)T

Ziegler, C., Schmidt-Thieme, L., Lausen, G.: Exploiting semantic product descriptions for recommender systems. In: Proc. of the 2nd ACM SIGIR Semantic Web and Information Retrieval Workshop (SWIR 2004), Sheffield, UK


Experiments and results

Experiments and results

  • Datasets

    • Last.fm (folksonomy)

    • Musicmoz (domain-expert ontology)

  • Only the resources contained in both were considered


Experiments and results1

alternative

electronica

chillout

depeche mode

electro

experimental rock

anything else but death

hip hop

heavy metal

old skool dance

house

Experiments and results

  • Folksonomy Enrichment

    • Edit distance to handle duplications


Frequent itemsets for learning ontologies from folksonomies3

Frequent Itemsets for Learning Ontologies from Folksonomies


Frequent itemsets for learning ontologies from folksonomies4

Frequent Itemsets for Learning Ontologies from Folksonomies


Recommender systems for ontology evaluation3

Recommender Systems for Ontology Evaluation

Top-10 best recommendations / Allbut1 protocol

Neighborhood size 20

Recall:=Number of hits / Number test users

Recall


Conclusions and future work

Conclusions and Future work

  • Conclusions

    • Folksonomies can alleviate knowledge bottleneck

    • Users need to be educated towards more shareble vocabulary though

    • Collabularies can help

  • Our Contributions

    • Definition of the collabulary learning problem

    • An approach for enriching folksonomies with domain expert knowledge

    • A new algorithm for learning ontologies from folksonomies

    • A new benchmark for task-based ontology evaluation

  • Future Work

    • Non-taxonomic relations ?

    • Different enrichment strategies ?

    • Optimized structure for the task with constraints ?


Thanks for your attention

Thanks for your attention! 


Frequent itemsets for learning ontologies from folksonomies5

Frequent Itemsets for Learning Ontologies from Folksonomies


  • Login