SlideShare uma empresa Scribd logo
Extended Explicit Semantic Analysis for Calculating Semantic Relatedness of Web Resources  Presentation 2010/10/01 EC-TEL, Barcelona 2010-10-01 EC-TEL Presentation Scholl.ppt Recommendation WP WP WP WP WP WP
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Scenario: Crokodil ,[object Object],[object Object],[object Object],[object Object],[object Object]
Study Results: Snippets of Web Resources ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[SBB09] Scholl, P., Benz, B. F., Böhnstedt, D., Rensing, C., Schmitz, B., Steinmetz, R. (2009): Implementation and Evaluation of a Tool for Setting Goals  in Self-Regulated Learning with Web Resources, In:  Learning in the Synergy of Multiple Disciplines, EC-TEL 2009 , pp. 521-534, Springer-Verlag Berlin/Heidelberg
Structural Recommendations ,[object Object],[object Object],[object Object],Recommendation Blog entry: Visualization of  Learning with Web 2.0 Paper excerpt: Social Network Analysis  and Visualizations for Learning  Web 2.0 Life long learning EC-TEL 2010 E-Learning TEL
Challenge: Sparse Knowledge Networks ,[object Object],[object Object],Goal: semantic recommendation based on snippets.    Some  measure of similarity / relatedness  between snippets is needed for recommendation Blog entry: e-learning in Web 2.0 Paper excerpt: Web 2.0 for learning Web 2.0 Life long learning TEL E-learning Recommendation ?
Implications for Recommending Snippets ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],“ TEL  refers to the  assistance  of  activities   in  knowledge acquisition  through  technology ” “ E-Learning  comprises all forms of  electronically   supported   learning  and  teaching .” ?
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],Base Approach: Explicit Semantic Analysis ESA* x = |terms|×1 n×1 document d 1 n documents from corpus Preprocessing steps* Semantic interpretation Matrix M int ,[object Object],[object Object],[object Object],[object Object],Semantic interpretation vector i esa n×|terms| n 1×|terms| vectors document d 2 comparison [GM07] Gabrilovich, E. & Markovitch, S. (2007): Computing semantic relatedness using wikipedia-based explicit semantic analysis.  In:  Proceedings of the 20th International Joint Conference on Artificial Intelligence,  pp. 6-12
Wikipedia as Reference Corpus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Source: wikipedia.org
Observation and Hypothesis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
XESA – Overview ESA XESA AG XESA CAT XESA AG+CAT Article content Article Graph Category Information
Article Graph Extension ,[object Object],[object Object],[object Object],General Relativity Albert Einstein Gravitation Space Matter Curvature Black Hole Catholic School Jewish Ulm Article Graph Matrix A |articles|×1 Semantic  interpretation  vector i esa x |articles|×|articles| = |articles|×1 i esa_AG
Category Graph Extension ,[object Object],General Relativity Fundamental Physics Concepts General Relativity Misner Space Anti-Gravity Atom Heat Concepts of Heaven Relativity Theories of Gravitation Physics Concepts by Field Frames of Reference Category Graph Matrix A |art|×1 Semantic  interpretation  vector i esa x |cat+art|×|art| = |cat+art|×1 i esa_AG
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation: Development of an Own Corpus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation: Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],0.595
Evaluation: Comparing Approaches ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],0.643 0.641 0.620 0.543
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Recommending via Semantic Relatedness Recommendation Semantic Relatedness (XESA) WP WP WP WP WP WP Paper excerpt: Social Network Analysis  and Visualizations for Learning  Web 2.0 Life long learning E-Learning TEL Blog entry: Visualization of  Learning with Web 2.0
Conclusions and Future Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions? … Thank you for your attention! This work was supported by funds from the German Federal Ministry of Education and Research under the mark 01 PF 08015 A and from the European Social Fund of the European Union (ESF).

Mais conteúdo relacionado

Mais procurados

2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...
2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...
2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...eMadrid network
 
CID presentation för VINNOVA 2003-03-28
CID presentation för VINNOVA 2003-03-28CID presentation för VINNOVA 2003-03-28
CID presentation för VINNOVA 2003-03-28Mikael Nilsson
 
Adoption of Digital Learning Objects
Adoption of Digital Learning ObjectsAdoption of Digital Learning Objects
Adoption of Digital Learning ObjectsShalin Hai-Jew
 
Making the Most of the New File Upload Question Feature in an LMS: Nine Appl...
Making the Most of the New File Upload Question Feature in an LMS:  Nine Appl...Making the Most of the New File Upload Question Feature in an LMS:  Nine Appl...
Making the Most of the New File Upload Question Feature in an LMS: Nine Appl...Shalin Hai-Jew
 
Online Learning and Linked Data: An Introduction
Online Learning and Linked Data: An IntroductionOnline Learning and Linked Data: An Introduction
Online Learning and Linked Data: An IntroductionEUCLID project
 
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3meMadrid network
 
Linked Data for Knowledge Discovery: Introduction
Linked Data for Knowledge Discovery: IntroductionLinked Data for Knowledge Discovery: Introduction
Linked Data for Knowledge Discovery: IntroductionMathieu d'Aquin
 
A Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolA Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolRalf Klamma
 
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)Stefan Dietze
 
Leveraging Flat Files from the Canvas LMS Data Portal at K-State
Leveraging Flat Files from the Canvas LMS Data Portal at K-StateLeveraging Flat Files from the Canvas LMS Data Portal at K-State
Leveraging Flat Files from the Canvas LMS Data Portal at K-StateShalin Hai-Jew
 
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courseseMadrid network
 
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...maurice.vanderfeesten
 
Combining content analytics and activity tracking to mine user interests and ...
Combining content analytics and activity tracking to mine user interests and ...Combining content analytics and activity tracking to mine user interests and ...
Combining content analytics and activity tracking to mine user interests and ...Andrii Vozniuk
 
WWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & EducationWWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & EducationStefan Dietze
 
Evaluation framework linkedup_amsterdam
Evaluation framework linkedup_amsterdamEvaluation framework linkedup_amsterdam
Evaluation framework linkedup_amsterdamHendrik Drachsler
 
Data4Ed - How data sharing, curation and analytics support innovation in educ...
Data4Ed - How data sharing, curation and analytics support innovation in educ...Data4Ed - How data sharing, curation and analytics support innovation in educ...
Data4Ed - How data sharing, curation and analytics support innovation in educ...Mathieu d'Aquin
 
LAK Dataset and Challenge (April 2013)
LAK Dataset and Challenge (April 2013)LAK Dataset and Challenge (April 2013)
LAK Dataset and Challenge (April 2013)Stefan Dietze
 
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...Shalin Hai-Jew
 
Linked Data for Federation of OER Data & Repositories
Linked Data for Federation of OER Data & RepositoriesLinked Data for Federation of OER Data & Repositories
Linked Data for Federation of OER Data & RepositoriesStefan Dietze
 

Mais procurados (20)

2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...
2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...
2014 04 03 (educon2014) emadrid upm supporting openness of moo cs contents th...
 
CID presentation för VINNOVA 2003-03-28
CID presentation för VINNOVA 2003-03-28CID presentation för VINNOVA 2003-03-28
CID presentation för VINNOVA 2003-03-28
 
Adoption of Digital Learning Objects
Adoption of Digital Learning ObjectsAdoption of Digital Learning Objects
Adoption of Digital Learning Objects
 
Making the Most of the New File Upload Question Feature in an LMS: Nine Appl...
Making the Most of the New File Upload Question Feature in an LMS:  Nine Appl...Making the Most of the New File Upload Question Feature in an LMS:  Nine Appl...
Making the Most of the New File Upload Question Feature in an LMS: Nine Appl...
 
Online Learning and Linked Data: An Introduction
Online Learning and Linked Data: An IntroductionOnline Learning and Linked Data: An Introduction
Online Learning and Linked Data: An Introduction
 
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m
2013 03-14 (educon2013) emadrid uc3m learning analytics uc3m
 
Linked Data for Knowledge Discovery: Introduction
Linked Data for Knowledge Discovery: IntroductionLinked Data for Knowledge Discovery: Introduction
Linked Data for Knowledge Discovery: Introduction
 
A Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolA Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning Pool
 
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)
 
Leveraging Flat Files from the Canvas LMS Data Portal at K-State
Leveraging Flat Files from the Canvas LMS Data Portal at K-StateLeveraging Flat Files from the Canvas LMS Data Portal at K-State
Leveraging Flat Files from the Canvas LMS Data Portal at K-State
 
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses
2014 04 03 (educon2014) emadrid uc3m about moo cs spocs and other online courses
 
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...
Enhanced Publications - Guest Lecture @Utrecht University - Design of Interac...
 
Combining content analytics and activity tracking to mine user interests and ...
Combining content analytics and activity tracking to mine user interests and ...Combining content analytics and activity tracking to mine user interests and ...
Combining content analytics and activity tracking to mine user interests and ...
 
WWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & EducationWWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & Education
 
PLE
PLEPLE
PLE
 
Evaluation framework linkedup_amsterdam
Evaluation framework linkedup_amsterdamEvaluation framework linkedup_amsterdam
Evaluation framework linkedup_amsterdam
 
Data4Ed - How data sharing, curation and analytics support innovation in educ...
Data4Ed - How data sharing, curation and analytics support innovation in educ...Data4Ed - How data sharing, curation and analytics support innovation in educ...
Data4Ed - How data sharing, curation and analytics support innovation in educ...
 
LAK Dataset and Challenge (April 2013)
LAK Dataset and Challenge (April 2013)LAK Dataset and Challenge (April 2013)
LAK Dataset and Challenge (April 2013)
 
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...
 
Linked Data for Federation of OER Data & Repositories
Linked Data for Federation of OER Data & RepositoriesLinked Data for Federation of OER Data & Repositories
Linked Data for Federation of OER Data & Repositories
 

Semelhante a Semantic Relatedness of Web Resources by XESA - Philipp Scholl

Semantic Text Processing Powered by Wikipedia
Semantic Text Processing Powered by WikipediaSemantic Text Processing Powered by Wikipedia
Semantic Text Processing Powered by WikipediaMaxim Grinev
 
Towards optimize-ESA for text semantic similarity: A case study of biomedical...
Towards optimize-ESA for text semantic similarity: A case study of biomedical...Towards optimize-ESA for text semantic similarity: A case study of biomedical...
Towards optimize-ESA for text semantic similarity: A case study of biomedical...IJECEIAES
 
IEEE FIE 2008 Saratoga Paper 1197
IEEE FIE 2008 Saratoga  Paper 1197IEEE FIE 2008 Saratoga  Paper 1197
IEEE FIE 2008 Saratoga Paper 1197Miguel R. Artacho
 
Improving Text Categorization with Semantic Knowledge in Wikipedia
Improving Text Categorization with Semantic Knowledge in WikipediaImproving Text Categorization with Semantic Knowledge in Wikipedia
Improving Text Categorization with Semantic Knowledge in Wikipediachjshan
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information RetrievalBhaskar Mitra
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information RetrievalBhaskar Mitra
 
IRJET- Short-Text Semantic Similarity using Glove Word Embedding
IRJET- Short-Text Semantic Similarity using Glove Word EmbeddingIRJET- Short-Text Semantic Similarity using Glove Word Embedding
IRJET- Short-Text Semantic Similarity using Glove Word EmbeddingIRJET Journal
 
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAM
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAMMULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAM
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAMeMadrid network
 
Effective Extraction of Thematically Grouped Key Terms From Text
Effective Extraction of Thematically Grouped Key Terms From TextEffective Extraction of Thematically Grouped Key Terms From Text
Effective Extraction of Thematically Grouped Key Terms From Textmaria.grineva
 
Ay3313861388
Ay3313861388Ay3313861388
Ay3313861388IJMER
 
Towards Ontology Development Based on Relational Database
Towards Ontology Development Based on Relational DatabaseTowards Ontology Development Based on Relational Database
Towards Ontology Development Based on Relational Databaseijbuiiir1
 
Extracting Key Terms From Noisy and Multi-theme Documents
Extracting Key Terms From Noisy and Multi-theme DocumentsExtracting Key Terms From Noisy and Multi-theme Documents
Extracting Key Terms From Noisy and Multi-theme Documentsmaria.grineva
 
G04124041046
G04124041046G04124041046
G04124041046IOSR-JEN
 
SE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
SE@M 2010: Automatic Keywords Extraction - a Basis for Content RecommendationSE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
SE@M 2010: Automatic Keywords Extraction - a Basis for Content RecommendationIvana Bosnic
 
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...ijaia
 
Progress in semantic mapping - NKOS
Progress in semantic mapping - NKOSProgress in semantic mapping - NKOS
Progress in semantic mapping - NKOSAntoine Isaac
 
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITION
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITIONSEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITION
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITIONcscpconf
 
Text Mining for Lexicography
Text Mining for LexicographyText Mining for Lexicography
Text Mining for LexicographyLeiden University
 
Zeroshot multimodal named entity disambiguation for noisy social media posts
Zeroshot multimodal named entity disambiguation for noisy social media postsZeroshot multimodal named entity disambiguation for noisy social media posts
Zeroshot multimodal named entity disambiguation for noisy social media postsSyo Kyojin
 
An efficient approach for semantically enhanced document clustering by using ...
An efficient approach for semantically enhanced document clustering by using ...An efficient approach for semantically enhanced document clustering by using ...
An efficient approach for semantically enhanced document clustering by using ...ijaia
 

Semelhante a Semantic Relatedness of Web Resources by XESA - Philipp Scholl (20)

Semantic Text Processing Powered by Wikipedia
Semantic Text Processing Powered by WikipediaSemantic Text Processing Powered by Wikipedia
Semantic Text Processing Powered by Wikipedia
 
Towards optimize-ESA for text semantic similarity: A case study of biomedical...
Towards optimize-ESA for text semantic similarity: A case study of biomedical...Towards optimize-ESA for text semantic similarity: A case study of biomedical...
Towards optimize-ESA for text semantic similarity: A case study of biomedical...
 
IEEE FIE 2008 Saratoga Paper 1197
IEEE FIE 2008 Saratoga  Paper 1197IEEE FIE 2008 Saratoga  Paper 1197
IEEE FIE 2008 Saratoga Paper 1197
 
Improving Text Categorization with Semantic Knowledge in Wikipedia
Improving Text Categorization with Semantic Knowledge in WikipediaImproving Text Categorization with Semantic Knowledge in Wikipedia
Improving Text Categorization with Semantic Knowledge in Wikipedia
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information Retrieval
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information Retrieval
 
IRJET- Short-Text Semantic Similarity using Glove Word Embedding
IRJET- Short-Text Semantic Similarity using Glove Word EmbeddingIRJET- Short-Text Semantic Similarity using Glove Word Embedding
IRJET- Short-Text Semantic Similarity using Glove Word Embedding
 
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAM
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAMMULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAM
MULTI-LEARNING SPECIAL SESSION / EDUCON 2018 / EMADRID TEAM
 
Effective Extraction of Thematically Grouped Key Terms From Text
Effective Extraction of Thematically Grouped Key Terms From TextEffective Extraction of Thematically Grouped Key Terms From Text
Effective Extraction of Thematically Grouped Key Terms From Text
 
Ay3313861388
Ay3313861388Ay3313861388
Ay3313861388
 
Towards Ontology Development Based on Relational Database
Towards Ontology Development Based on Relational DatabaseTowards Ontology Development Based on Relational Database
Towards Ontology Development Based on Relational Database
 
Extracting Key Terms From Noisy and Multi-theme Documents
Extracting Key Terms From Noisy and Multi-theme DocumentsExtracting Key Terms From Noisy and Multi-theme Documents
Extracting Key Terms From Noisy and Multi-theme Documents
 
G04124041046
G04124041046G04124041046
G04124041046
 
SE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
SE@M 2010: Automatic Keywords Extraction - a Basis for Content RecommendationSE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
SE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
 
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...
AN EFFICIENT APPROACH FOR SEMANTICALLYENHANCED DOCUMENT CLUSTERING BY USING W...
 
Progress in semantic mapping - NKOS
Progress in semantic mapping - NKOSProgress in semantic mapping - NKOS
Progress in semantic mapping - NKOS
 
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITION
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITIONSEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITION
SEMANTIC NETWORK BASED MECHANISMS FOR KNOWLEDGE ACQUISITION
 
Text Mining for Lexicography
Text Mining for LexicographyText Mining for Lexicography
Text Mining for Lexicography
 
Zeroshot multimodal named entity disambiguation for noisy social media posts
Zeroshot multimodal named entity disambiguation for noisy social media postsZeroshot multimodal named entity disambiguation for noisy social media posts
Zeroshot multimodal named entity disambiguation for noisy social media posts
 
An efficient approach for semantically enhanced document clustering by using ...
An efficient approach for semantically enhanced document clustering by using ...An efficient approach for semantically enhanced document clustering by using ...
An efficient approach for semantically enhanced document clustering by using ...
 

Último

Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀DianaGray10
 
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomSalesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomCzechDreamin
 
Enterprise Security Monitoring, And Log Management.
Enterprise Security Monitoring, And Log Management.Enterprise Security Monitoring, And Log Management.
Enterprise Security Monitoring, And Log Management.Boni Yeamin
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoTAnalytics
 
Motion for AI: Creating Empathy in Technology
Motion for AI: Creating Empathy in TechnologyMotion for AI: Creating Empathy in Technology
Motion for AI: Creating Empathy in TechnologyUXDXConf
 
Transforming The New York Times: Empowering Evolution through UX
Transforming The New York Times: Empowering Evolution through UXTransforming The New York Times: Empowering Evolution through UX
Transforming The New York Times: Empowering Evolution through UXUXDXConf
 
UiPath Test Automation using UiPath Test Suite series, part 1
UiPath Test Automation using UiPath Test Suite series, part 1UiPath Test Automation using UiPath Test Suite series, part 1
UiPath Test Automation using UiPath Test Suite series, part 1DianaGray10
 
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMsTo Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMsPaul Groth
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backElena Simperl
 
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...CzechDreamin
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxJennifer Lim
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераMark Opanasiuk
 
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsPLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsStefano
 
Designing for Hardware Accessibility at Comcast
Designing for Hardware Accessibility at ComcastDesigning for Hardware Accessibility at Comcast
Designing for Hardware Accessibility at ComcastUXDXConf
 
Strategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering TeamsStrategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering TeamsUXDXConf
 
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for SuccessStructuring Teams and Portfolios for Success
Structuring Teams and Portfolios for SuccessUXDXConf
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaRTTS
 
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya HalderCustom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya HalderCzechDreamin
 
A Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System StrategyA Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System StrategyUXDXConf
 

Último (20)

Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
 
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomSalesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
 
Enterprise Security Monitoring, And Log Management.
Enterprise Security Monitoring, And Log Management.Enterprise Security Monitoring, And Log Management.
Enterprise Security Monitoring, And Log Management.
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024
 
Motion for AI: Creating Empathy in Technology
Motion for AI: Creating Empathy in TechnologyMotion for AI: Creating Empathy in Technology
Motion for AI: Creating Empathy in Technology
 
Transforming The New York Times: Empowering Evolution through UX
Transforming The New York Times: Empowering Evolution through UXTransforming The New York Times: Empowering Evolution through UX
Transforming The New York Times: Empowering Evolution through UX
 
UiPath Test Automation using UiPath Test Suite series, part 1
UiPath Test Automation using UiPath Test Suite series, part 1UiPath Test Automation using UiPath Test Suite series, part 1
UiPath Test Automation using UiPath Test Suite series, part 1
 
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMsTo Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
 
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджера
 
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsPLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. Startups
 
Designing for Hardware Accessibility at Comcast
Designing for Hardware Accessibility at ComcastDesigning for Hardware Accessibility at Comcast
Designing for Hardware Accessibility at Comcast
 
Strategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering TeamsStrategic AI Integration in Engineering Teams
Strategic AI Integration in Engineering Teams
 
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for SuccessStructuring Teams and Portfolios for Success
Structuring Teams and Portfolios for Success
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
 
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya HalderCustom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
 
A Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System StrategyA Business-Centric Approach to Design System Strategy
A Business-Centric Approach to Design System Strategy
 

Semantic Relatedness of Web Resources by XESA - Philipp Scholl

  • 1. Extended Explicit Semantic Analysis for Calculating Semantic Relatedness of Web Resources Presentation 2010/10/01 EC-TEL, Barcelona 2010-10-01 EC-TEL Presentation Scholl.ppt Recommendation WP WP WP WP WP WP
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. XESA – Overview ESA XESA AG XESA CAT XESA AG+CAT Article content Article Graph Category Information
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21. Recommending via Semantic Relatedness Recommendation Semantic Relatedness (XESA) WP WP WP WP WP WP Paper excerpt: Social Network Analysis and Visualizations for Learning Web 2.0 Life long learning E-Learning TEL Blog entry: Visualization of Learning with Web 2.0
  • 22.
  • 23. Questions? … Thank you for your attention! This work was supported by funds from the German Federal Ministry of Education and Research under the mark 01 PF 08015 A and from the European Social Fund of the European Union (ESF).

Notas do Editor

  1. November 19, 2007 | |
  2. November 19, 2007 | |
  3. November 19, 2007 | | What’s different with snippets? Why did they use it?
  4. November 19, 2007 | |
  5. November 19, 2007 | |
  6. November 19, 2007 | | Languages: 29 with more than 1 Mio. articles & categories & administration pages
  7. November 19, 2007 | |
  8. November 19, 2007 | |
  9. November 19, 2007 | | As categories form different concept space, they cannot be applied directly to interpretation vector
  10. November 19, 2007 | | Standard deviation: square root of variance
  11. November 19, 2007 | | Trefferquote ist die Wahrscheinlichkeit, mit der ein relevantes Dokument gefunden wird. Genauigkeit ist die Wahrscheinlichkeit, mit der ein gefundenes Dokument relevant ist.
  12. November 19, 2007 | |
  13. November 19, 2007 | |
  14. November 19, 2007 | |