Semantic Tags Generation and Retrieval for Online Advertising - CIKM 2010

CIKM 2010 – 19th ACM Internation Conference on Information and Knowledge ManagementOctober 29, 2010 – Fairmont Royal York, Toronto, Canada

SEMANTIC TAGS GENERATION AND RETRIEVAL FOR ONLINE ADVERTISING

1Politecnico di BariVia Orabona, 470125 Bari (ITALY)

2University of TrentoVia Sommarive, 14

38100 Trento (ITALY)

Roberto Mirizzi1, Azzurra Ragone1,2, Tommaso Di Noia1, Eugenio Di Sciascio1


Outline

Tags in Web 2.0 → 3.0Computational advertising

NOT (Not Only Tag): semantic tag cloud generation

DBpediaRanker: RDF ranking in DBpedia

Conclusion and Future work


Who is using tags nowadays?

and many

more…

http://www.amazon.com/gp/tagging/cloud/

http://delicious.com/search?p=enrico+motta&chk=&context=main%7C&fr=del_icio_us&lc=

http://www.flickr.com/photos/tags/

http://www.faviki.com/tag/Tim%20Berners-Lee

http://www.programmableweb.com/mashup-tag-cloud


What about Tags in Online Advertising?

food

recipes

cooking

dessert

pasta

meat

fish

spag

hetti


BigG (& co.) helps you… in half (i)

…nice, but there is no “semantics” in it.

You can not expand your keywords list exploiting the

meaning of a term (keyword/tag/query)

https://adwords.google.com/select/KeywordToolExternal

Keyword Tool

Based on actual Google search queries

Generates keywords based on the content of a URL, words or phrases

1

2

3


BigG (& co.) helps you… in half (ii)

…nice, but there is no “semantics” in it.

You can not expand your keywords list exploiting the

meaning of a term (keyword/tag/query)

Keyword Tool

Based on actual Google search queries

Generates keywords based on the content of a URL, words or phrases


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/


NOT: Not Only TagObjectives

Assist advertisers to create more efficient ads campaigns

Support ads providers to properly match ads content to keywords in search engines

Improve advertiser experience and ad selection


What is behind NOT? (i)


What is behind NOT? (ii)Comments

DBpedia resources are highly interconnected in the RDF graph

Not all the relevant resources for a given node are its direct neighbors

1. Explore the neighborhood of a resource to discover new relevant resources not directly connected to it

2. Rank the results


DBpedia graph exploration in NOT

Open_source_CMS Web_application_frameworks

Content_management_systems Free_business_software …

…

Web_development Web_applications

JavaServer_Faces Python_web_application_frameworks

Zend_Framework

Joomla_extensions

skos:subject skos:broaderCategoryArticle

Legend

…

……

Magento

…PHP

Drupal

…


The functional architecture

Back-end

Query engine

Storage

Tag Cloud GeneratorGUI

Ext.

Info

Sou

rces

DBpedia Lookup Service

Interface

Delicious

Yahoo!

Bing

Google

Graph Explorer

SPARQLContext Analyzer

Ranker

Offline computation

Linked Data graph exploration

Rank nodes exploiting external information

Store results as pairs of nodes together with their similarity

Runtime SearchStart typing a query

Query the system for relevant tags (corresponding to DBpedia resources)

Show the semantic tag cloud

1

2

3

1

2

3

Offl

ine computation

Runtime search

1

2

3

12

3


DBpediaRanker: ranking

?r1 ?r2isSimilar

v

hasValue

einfo_sourc2

21

1

21einfo_sourc21 )(

),(

)(

),(),(

rf

rrf

rf

rrfrrsim

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

)(

),(),(

2

1221 rl

rrlrroreabstractSc

Graph-based and text-based ranking

Ranking based on external sources


DBpediaRanker: an example (i)

wikilinkScore(Zend_Framework, PHP) = 2 abstractScore(Zend_Framework, PHP) = 1.0


DBpediaRanker: an example (ii)

sim(Zend_Framework, PHP)Google = 1.53e6 / 2.96e6 + 1.53e6 / 1.71e9 ≈ 0.52 + 0

delicious


DBpediaRanker: 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 belong 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


Evaluation (i)

http://sisinflab.poliba.it/evaluation

Comparison of 5 different algorithms 50 volunteers

Researchers in the ICT area 244 votes collected (on average 5 votes for each users)

Average time to vote: 1min and 40secs


Evaluation (ii)

http://sisinflab.poliba.it/evaluation/data

3.91 - Good


Conclusion

NOT: a prototype system for tag cloud generation in semantic advertising

DBpediaRanker: ranking algorithms for resources in DBpedia

Future work Use the back-end of the system to develop new interfaces

for exploratory browsing Improve ranking algorithms Combine a content-based recommendation and a

collaborative-filtering approach Develop a platform to test our system with real ads about

different domains


Q&A

Thanks for your attention!

SEMANTIC TAGS GENERATION AND RETRIEVAL FOR ONLINE ADVERTISING (CIKM 2010)

If you're interested in learning more…1. Roberto Mirizzi, Tommaso Di Noia. From Exploratory Search to Web Search and back. 4th Workshop for Ph.D. Students in Information

and Knowledge Management (PIKM 2010)2. Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciascio. Ranking the Linked Data: the case of DBpedia. 10th

International Conference on Web Engineering (ICWE 2010)3. Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciascio. Semantic tag cloud generation via DBpedia. 11th International

Conference on Electronic Commerce and Web Technologies (EC-Web 2010)4. Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciascio. Semantic tagging for crowd computing. 18th Italian

Symposium on Advanced Database Systems (SEBD 2010)5. Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciascio. Semantic Wonder Cloud: exploratory search in DBpedia. 2th

International Workshop on Semantic Web Information Management (SWIM 2010) - Best Workshop Paper at International Conference on Web Engineering (ICWE 2010)

Roberto Mirizzi - [email protected]

See you tomorrow at PIKM 2010 in Room Alberta at 4pm with…From Exploratory Search to Web Search and back

Semantic Tags Generation and Retrieval for Online Advertising - CIKM 2010

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