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CORDIS - Résultats de la recherche de l’UE
CORDIS

AFEL - Analytics For Everyday Learning

Livrables

Detection and Enrichment of Learning Patterns/Notions v.1

This deliverable will describe an initial version of the results and methods originating from the detection and enrichment work in WP2 where the key aim is to identify learningrelated notions and patterns in data produced in WP1 WP2 and WP4 That may include automated means of enriching data as well as additional experimental work to identify or verify patternsnotions of learning collaboration or knowledge production

Description of the available social environments and data

This document will specify and describe the social spaces that will be studied in the use case, that is: a) identify and characterise the set of GNOSS-Didactalia communities for the analysis, as main environments of the use case, b) define which other additional potential environments will be employed for the use case, establishing the strategy and methods to obtain their data, perform the integration and evaluate the results. It will also identify which data will be collected from the activity and interactions of the users in the platforms, for their use in WP1, WP2, WP3 and WP4.

Report on the analysis of handling complexity

This deliverable will present a method and results of using the data from the previous three workpackages and from T4.2 in order to analyse how communities deal with complexity, through filtering out certain pieces of information in order to be able to handle those few influences which that system permits.

Specification of data to be collected

Report on the data that will be extracted from every source (data about users’ activity, how they behave, how they interact with each other and with contents, etc.), that could provide information about learning activities.

Further exploitation plan

Based on the experience gained in carrying out in the Integration of the analytic tools and models Tasks T53 and the addition to the GNOSS commercial offering T64 we will here investigate other possible channels of exploitation in the form of other platforms where the tools and models of the project can be integrated Selection of the most promising ones The results will then be incorporated into a further exploitation plan

Development and evaluation of ontological and stochastic methods for recognising and classifying learning activities

Description of a method employing an ontological approach to data capture through integrating the previous data extraction and feature engineering activities with the enrichment provided in WP2 and Markov decision modelbased approaches to aligning them with the model of WP4

Report on the analysis of learning & collaboration

This deliverable will describe methods using the data retrieved and processed in workpackages 1-3 to analyse how knowledge construction in this online social environment occurs, at the community level as well as the individual level.

Report on the analysis of self-organisation

This deliverable will describe a method and the results of using data from the previous three workpackages and from T4.1 to analyse how learning communities maintain themselves by taking up those aspects of communication from the environment that are relevant for its continuance.

Conceptual Framework of Visual analytics of conflicts, problems and barriers

This deliverable introduces a conceptual framework describing visual analytics methods for identifying conflicts, problems and barriers which hinder learning processes in online social environments. An observer (administrator) shall be empowered to make decisions for improving the learning environment and learning experience.

Report describing the analysis of the constitution of meaning

This deliverable will describe methods and results using the data from the previous three workpackages and from T43 in order to analyse how systems select certain parts of the irritations and stimuli from outside and transform them into meaningful information

Integrated model of informal learning in social spaces and evaluation

This deliverable will describe the lessons learnt and an integrated view from the work achieved on different aspects of the analyses of learning activities communities and complexity in online social learning platforms in WP4

First report on dissemination activities

First report on dissemination activities based on the communication and dissemination targetsUpdate and adaptation of the communication and dissemination plan if needed

Final report on exploitation plan and activities
Dissemination plan

Set up of a targeted communication and dissemination plan for the project. An essential part of it is the clear determination of communication and dissemination objectives, the identification of relevant target groups and events as well as the development of a target-group-oriented communication strategy.

First evaluation of the adoption and benefit of analytics in social environments

This report will evaluate the use of learning analytic tools through AFEL tools in social environments with main focus in the analysis of their application in GNOSSDidactalia communities but also in other online social learning platforms that will be defined in D51 This first evaluation will be carried out with intermediary data and tools

Detection and Enrichment of Learning Patterns/Notions v.2

This deliverable describes the second version of D231 and will describe the refined methods and results for detection and enrichment of learning patternsnotions specifically considering visual analytics approaches from WP3

Evaluation results for visual analytics tools

This deliverable provides results on gathered experiences and performed evaluations of the developed visual analytics tools and methods The results will include qualitative and quantitative analyses evaluating the contribution of developed methods in gaining new insights that aid informal learning

Final evaluation of the adoption and benefit of analytics in social environments

This deliverable consists of the second and final report that evaluates the application of learning analytics in social environments with main focus in the analysis of their application in GNOSSDidactalia communities but also in other online social learning platforms that will be defined in D51This report will be carried out on final results of the project and will take into account the evaluations performed in WP3 D37 and WP4 D45

Data management, final report

Final version of the data management report

Data Analytics & Entity Linking for Learning Analytics

This deliverable will describe analytics, enrichment and linking approaches for the data and learning analytics scenarios in the project. This includes methods for analysing and consolidating data produced in WP1 - by automated means as well as through Web-scale crowdsourcing - as well as the derivation of novel analytical approaches for extracting relevant insights, for instance, wrt theories and models produced WP4.

Conceptual Framework of Visual analytics of Communities

This deliverable introduces a conceptual framework describing visual analytics methods for gaining understanding of informal learning processes in online social environments. The focus is on understanding communities and patterns in social learning processes, including analysis of the evolution of learning activity streams, and delivery of a personalized visual environmet enabling user to make progress depending on explicit and implicit (derived) preferences.

Feature definitions and extraction methods

Description of the first layer of data processing, researching the features in the raw data extracted, to obtain information that can be meaningfully processed for analysis and modelling.

Second report on dissemination activities

Final report on dissemination activities based on the communication and dissemination targets

AFEL public online community and external communication tools

A dedicated, public community on GNOSS will be setup to connect with interested parties. Set up of the AFEL project website, as well as of social media (twitter feed, etc.) to connect to the relevant communities.

Web of GNOSS products updated with AFEL tools offer

The AFEL tools integrated into the GNOSS platform will be included in the web of GNOSS products as part of its commercial offering

AFEL-based API, applications and solutions for online social platforms

Development of prototype applications with potential for commercial applications after the projects end This includes application for informal learning of generic social networking platform such as Facebook or LinkedIn as well as the potential development of more dedicated solutions for socialinformal learning to be integrated within schoolsuniversities ICT environments eg SocialLearn httpsociallearnopenacuk and LearnWeb This will also include offering an open source development API for the tools and techniques developed in the project as a simplified version of the technical platform applied on GNOSS and usable to develop applications of other online social systems

Large-Scale Dataset for (Social) Learning Analytics, Release 3

This deliverable describes the second version of the AFEL datasets and will contain an expanded enriched and restructured version of D24

Large-Scale Dataset for (Social) Learning Analytics, Release 2

This deliverable describes the second version of the AFEL datasets and will contain an expanded enriched and restructured version of D22

Complete data extraction and management infrastructure and evaluation

This deliverable presents the second and completed version of the data extraction and management infrastructure of the project

Ontological models of learning activities

An ontological framework for the datamodelling definition of learning activities in such a way that they can be recognised and to a certain extent classified from the data obtained from social media

Integrated feature extraction for analytics and evaluations

This prototype exploits the feedback loop between the later analytics enrichment and modelling tasks of the project to identify base requirements for the identifications of learning activities and address them through employing state of the art clustering natural language processing and data refactoring techniques

Base data management infrastructure and core data model

Data extraction and management infrastructure to collect data from online social environments and make them available to the rest of the project. This includes the core data model of the project (integrating existing models into a linked data-compliant vocabulary), creating extractors for specific sources of data such as the logs of GNOSS, Facebook’s activity streams or LinkedIn skills and education APIs, and deploying a data management platform consisting of a triple store and a data endpoint for supporting convenient use by other processes in the project.

Large-Scale Dataset for (Social) Learning Analytics, Release 1

The first version of the AFEL dataset will consist primarily of data collected as part of data extraction and crawling activities in WP1 and WP2. Data will be enriched and expanded throughout later iterations of the dataset.

Application of analytics tools and models in additional online social platforms

Generic tools developed with the GNOSS platform as a primary testbed will be extracted and tested on other social platforms and made available as reusable components

Publications

Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms

Auteurs: Dominik Kowald, Elisabeth Lex
Publié dans: 2017
Éditeur: arXiv

Fine Grained Citation Span for References in Wikipedia

Auteurs: Besnik Fetahu, Katja Markert, Avishek Anand
Publié dans: 2017
Éditeur: arXiv

Tags, Titles or Q&As? - Choosing Content Descriptors for Visual Recommender Systems

Auteurs: Belgin Mutlu, Eduardo Veas, Christoph Trattner
Publié dans: Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT '17, 2017, Page(s) 265-274, ISBN 9781-450347082
Éditeur: ACM Press
DOI: 10.1145/3078714.3078741

Predicting User Knowledge Gain in Informational Search Sessions

Auteurs: Ran Yu, Ujwal Gadiraju, Peter Holtz, Markus Rokicki, Philipp Kemkes, Stefan Dietze
Publié dans: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18, 2018, Page(s) 75-84, ISBN 9781-450356572
Éditeur: ACM Press
DOI: 10.1145/3209978.3210064

Clarity is a Worthwhile Quality - On the Role of Task Clarity in Microtask Crowdsourcing

Auteurs: Ujwal Gadiraju, Jie Yang, Alessandro Bozzon
Publié dans: Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT '17, 2017, Page(s) 5-14, ISBN 9781-450347082
Éditeur: ACM Press
DOI: 10.1145/3078714.3078715

can bots be better learners than humans?

Auteurs: Wassim Derguech, Mathieu d’Aquin
Publié dans: Proceedings of the Re-coding Black Mirror 2017 Workshop, 2017
Éditeur: CEUR-WS

FuseM: Query-Centric Data Fusion on Structured Web Markup

Auteurs: Ran Yu, Ujwal Gadiraju, Besnik Fetahu, Stefan Dietze
Publié dans: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017, Page(s) 179-182, ISBN 978-1-5090-6543-1
Éditeur: IEEE
DOI: 10.1109/icde.2017.69

Analyzing Knowledge Gain of Users in Informational Search Sessions on the Web

Auteurs: Ujwal Gadiraju, Ran Yu, Stefan Dietze, Peter Holtz
Publié dans: Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - CHIIR '18, 2018, Page(s) 2-11, ISBN 9781-450349253
Éditeur: ACM Press
DOI: 10.1145/3176349.3176381

Supporting virtual integration of Linked Data with just-in-time query recompilation

Auteurs: Alessandro Adamou, Mathieu d'Aquin, Carlo Allocca, Enrico Motta
Publié dans: Proceedings of the 13th International Conference on Semantic Systems - Semantics2017, 2017, Page(s) 112-119, ISBN 9781-450352963
Éditeur: ACM Press
DOI: 10.1145/3132218.3132227

AFEL: Towards Measuring Online Activities Contributions to Self-directed Learning

Auteurs: Mathieu D'Aquin, Alessandro Adamou, Stefan Dietze, Besnik Fetahu, Ujwal Gadiraju, Ilire Hasani-Mavriqi, Peter Holtz, Joachim Kimmerle, Dominik Kowald, Elisabeth Lex, Susana Lopez Sola, Ricardo Maturana, Vedran Sabol, Pinelopi Troullinou, Eduardo Veas
Publié dans: Proceedings of the 7th Workshop on Awareness and Reflection in Technology Enhanced Learning, 2017
Éditeur: CEUR-WS

Improving learning through achievement priming in crowdsourced information finding microtasks

Auteurs: Ujwal Gadiraju, Stefan Dietze
Publié dans: Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17, 2017, Page(s) 105-114, ISBN 9781-450348706
Éditeur: ACM Press
DOI: 10.1145/3027385.3027402

Inferring Missing Categorical Information in Noisy and Sparse Web Markup

Auteurs: Nicolas Tempelmeier, Elena Demidova, Stefan Dietze
Publié dans: Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, 2018, Page(s) 1297-1306, ISBN 9781-450356398
Éditeur: ACM Press
DOI: 10.1145/3178876.3186028

AFEL - Analytics for Everyday Learning

Auteurs: Mathieu d'Aquin, Dominik Kowald, Angela Fessl, Elisabeth Lex, Stefan Thalmann
Publié dans: Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018, Page(s) 439-440, ISBN 9781-450356404
Éditeur: ACM Press
DOI: 10.1145/3184558.3186206

Assessing the Readability of Policy Documents - The Case of Terms of Use of Online Services

Auteurs: Wassim Derguech, Syeda Sana e Zainab, Mathieu D'Aquin
Publié dans: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance - ICEGOV '18, 2018, Page(s) 247-256, ISBN 9781-450354219
Éditeur: ACM Press
DOI: 10.1145/3209415.3209498

Finding traces of self-regulated learning in activity streams

Auteurs: Analía Cicchinelli, Eduardo Veas, Abelardo Pardo, Viktoria Pammer-Schindler, Angela Fessl, Carla Barreiros, Stefanie Lindstädt
Publié dans: Proceedings of the 8th International Conference on Learning Analytics and Knowledge - LAK '18, 2018, Page(s) 191-200, ISBN 9781-450364003
Éditeur: ACM Press
DOI: 10.1145/3170358.3170381

The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations - An Online Study

Auteurs: Dominik Kowald, Paul Seitlinger, Tobias Ley, Elisabeth Lex
Publié dans: Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018, Page(s) 1-2, ISBN 9781-450356404
Éditeur: ACM Press
DOI: 10.1145/3184558.3186899

Trust-based collaborative filtering - tackling the cold start problem using regular equivalence

Auteurs: Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex
Publié dans: Proceedings of the 12th ACM Conference on Recommender Systems - RecSys '18, 2018, Page(s) 446-450, ISBN 9781-450359016
Éditeur: ACM Press
DOI: 10.1145/3240323.3240404

Detecting, Understanding and Supporting Everyday Learning in Web Search

Auteurs: Ran Yu, Ujwal Gadiraju, Stefan Dietze
Publié dans: LILE 2018, 2018
Éditeur: arXiv

Current Challenges for Studying Search as Learning Processes

Auteurs: Anett Hoppe, Peter Holtz, Yvonne Kammerer, Ran Yu, Stefan Dietze, Ralph Ewerth
Publié dans: LILE 2018, 2018
Éditeur: TIB

Wikipedia article measures in relation to content characteristics of lead sections.

Auteurs: Seren Yenikent, Brett Buttliere, Besnik Fetahu, Joachim Kimmerle
Publié dans: LILE 2018, 2018
Éditeur: ResearchGate

Real-time Event-based News Suggestion for Wikipedia Pages from News Streams.

Auteurs: Lijun Lyu and Besnik Fetahu
Publié dans: WikiWorkshop 2018, 2018
Éditeur: ACM

Detecting Biased Statements in Wikipedia.

Auteurs: Christoph Hube and Besnik Fetahu
Publié dans: WikiWorkshop 2018, 2018
Éditeur: ACM

AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments

Auteurs: Kowald, D., Lacic, E., Theiler, D., Lex, E.
Publié dans: Social Interaction-Based Recommender Systems (SIR'2018) Workshop, 2018
Éditeur: arXiv

Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations

Auteurs: Emanuel Lacic, Dominik Kowald, Elisabeth Lex
Publié dans: International Workshop on Entity Retrieval (EYRE'2018) Workshop, 2018
Éditeur: arVix

Evaluating the AFEL learning tools: Didactalia users’ experiences with personalized recommendations and interactive visualizations.

Auteurs: Seren Yenikent, Peter Holtz, Stefan Thalmann, Mathieu D’Aquin, Joachim Kimmerle
Publié dans: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018
Éditeur: CEUR-WS

Analytics for Everyday Learning from two Perspectives: Knowledge Workers and Teachers.

Auteurs: Angela Fessl, Dominik Kowald, Susana López Sola, Ana Moreno, Ricardo Alonso Maturana, Stefan Thalmann
Publié dans: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018
Éditeur: CEUR-WS

Towards a Learning Dashboard for Community Visualization

Auteurs: Belgin Mutlu, Ilija Simic, Analia Cicchinelli, Vedran Sabol, Eduardo Veas
Publié dans: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018
Éditeur: CEUR-WS

Detection of Online Learning Activity Scopes

Auteurs: Syeda Sana E. Zainab, Mathieu D'Aquin
Publié dans: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018
Éditeur: CEUR-WS

Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL

Auteurs: Simone Kopeinik, Dominik Kowald, Elisabeth Lex
Publié dans: Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL, Numéro 11th European Conference on Technology Enhanced Learning, EC-TEL 2016, Lyon, France, September 13-16, 2016, Proceedings, 2016, Page(s) 124-138, ISBN 978-3-319-45152-7
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-45153-4_10

Semantic Stability in Wikipedia

Auteurs: Darko Stanisavljevic, Ilire Hasani-Mavriqi, Elisabeth Lex, Markus Strohmaier, Denis Helic
Publié dans: Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016., Numéro Studies in Computational Intelligence, vol 693, 2017, Page(s) 379-390, ISBN 978-3-319-50900-6
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-50901-3_31

Finding News Citations for Wikipedia

Auteurs: Besnik Fetahu, Katja Markert, Wolfgang Nejdl, Avishek Anand
Publié dans: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16, 2016, Page(s) 337-346, ISBN 9781-450340731
Éditeur: ACM Press
DOI: 10.1145/2983323.2983808

Unlock the Stock: User Topic Modeling for Stock Market Analysis

Auteurs: Patrick Siehndel and Ujwal Gadiraju, L3S Research Center, Leibniz Universität Hannover, Germany
Publié dans: Published in the Workshop Proceedings of the EDBT/ICDT 2016 Joint Conference (March 15, 2016, Bordeaux, France) on CEUR-WS.org (ISSN 1613-0073), Numéro EDBT/ICDT Workshops 2016, 2016, Page(s) 1558, ISSN 1613-0073
Éditeur: CEUR-WS.org

It's getting crowded! - how to use crowdsourcing effectively for web science research

Auteurs: Ujwal Gadiraju, Gianluca Demartini, Djellel Eddine Difallah, Michele Catasta
Publié dans: Proceedings of the 8th ACM Conference on Web Science - WebSci '16, 2016, Page(s) 11-11, ISBN 9781-450342087
Éditeur: ACM Press
DOI: 10.1145/2908131.2908140

Estimating domain specificity for effective crowdsourcing of link prediction and schema mapping

Auteurs: Ujwal Gadiraju, Patrick Siehndel, Stefan Dietze
Publié dans: Proceedings of the 8th ACM Conference on Web Science - WebSci '16, 2016, Page(s) 323-324, ISBN 9781-450342087
Éditeur: ACM Press
DOI: 10.1145/2908131.2908209

Where the Event Lies - Predicting Event Occurrence in Textual Documents

Auteurs: Andrea Ceroni, Ujwal Gadiraju, Jan Matschke, Simon Wingert, Marco Fisichella
Publié dans: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16, 2016, Page(s) 1157-1160, ISBN 9781-450340694
Éditeur: ACM Press
DOI: 10.1145/2911451.2911452

Adaptive Focused Crawling of Linked Data

Auteurs: Ran Yu, Ujwal Gadiraju, Besnik Fetahu, Stefan Dietze
Publié dans: Web Information Systems Engineering – WISE 2015. Lecture Notes in Computer Science, Numéro vol 9418, 2015, Page(s) 554-569, ISBN 978-3-319-26189-8
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-26190-4_37

A Survey on Challenges for Entity Retrieval in Web Markup Data

Auteurs: Ran Yu, Besnik Fetahu, Ujwal Gadiraju and Stefan Dietze
Publié dans: Proceedings of the ISWC 2016 Posters & Demonstrations Track co-located with 15th International Seman, Numéro Vol-1690, 2016, Page(s) paper70
Éditeur: ceur-ws.org

Towards Entity Summarisation on Structured Web Markup

Auteurs: Ran Yu, Ujwal Gadiraju, Xiaofei Zhu, Besnik Fetahu, Stefan Dietze
Publié dans: The Semantic Web. ESWC 2016. Lecture Notes in Computer Science, Numéro vol 9989, 2016, Page(s) 69-73
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-47602-5_15

Towards Embedded Markup of Learning Resources on the Web - An Initial Quantitative Analysis of LRMI Terms Usage

Auteurs: Davide Taibi, Stefan Dietze
Publié dans: Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion, 2016, Page(s) 513-517, ISBN 9781-450341448
Éditeur: ACM Press
DOI: 10.1145/2872518.2890464

Beyond Established Knowledge Graphs-Recommending Web Datasets for Data Linking

Auteurs: Mohamed Ben Ellefi, Zohra Bellahsene, Stefan Dietze, Konstantin Todorov
Publié dans: eb Engineering. ICWE 2016. Lecture Notes in Computer Science, Numéro vol 9671, 2016, Page(s) 262-279, ISBN 978-3-319-38790-1
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-38791-8_15

Supporting collaborative learning with tag recommendations - a real-world study in an inquiry-based classroom project

Auteurs: Simone Kopeinik, Elisabeth Lex, Paul Seitlinger, Dietrich Albert, Tobias Ley
Publié dans: Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17, 2017, Page(s) 409-418, ISBN 9781-450348706
Éditeur: ACM Press
DOI: 10.1145/3027385.3027421

The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems

Auteurs: Dominik Kowald, Simone Kopeinik, Elisabeth Lex
Publié dans: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization - UMAP '17, 2017, Page(s) 23-28, ISBN 9781-450350679
Éditeur: ACM Press
DOI: 10.1145/3099023.3099069

Temporal Effects on Hashtag Reuse in Twitter - A Cognitive-Inspired Hashtag Recommendation Approach

Auteurs: Dominik Kowald, Subhash Chandra Pujari, Elisabeth Lex
Publié dans: Proceedings of the 26th International Conference on World Wide Web - WWW '17, 2017, Page(s) 1401-1410, ISBN 9781-450349130
Éditeur: ACM Press
DOI: 10.1145/3038912.3052605

Analysing and Improving Embedded Markup of Learning Resources on the Web

Auteurs: Stefan Dietze, Davide Taibi, Ran Yu, Phil Barker, Mathieu d'Aquin
Publié dans: Proceeding WWW '17 Companion Proceedings of the 26th International Conference on World Wide Web Companion, 2017, Page(s) Pages 283-292, ISBN 978-1-4503-4914-7
Éditeur: International World Wide Web Conferences Steering Committee Republic
DOI: 10.1145/3041021.3054160

Measuring Accuracy of Triples in Knowledge Graphs

Auteurs: Shuangyan Liu, Mathieu d’Aquin, Enrico Motta
Publié dans: Language, Data, and Knowledge. LDK 2017. Lecture Notes in Computer Science, Numéro vol 10318, 2017, Page(s) 343-357, ISBN 978-3-319-59887-1
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-59888-8_29

Unsupervised learning for understanding student achievement in a distance learning setting

Auteurs: Shuangyan Liu, Mathieu d'Aquin
Publié dans: 2017 IEEE Global Engineering Education Conference (EDUCON), 2017, Page(s) 1373-1377, ISBN 978-1-5090-5467-1
Éditeur: IEEE
DOI: 10.1109/EDUCON.2017.7943026

Dataset Recommendation for Data Linking: An Intensional Approach

Auteurs: Mohamed Ben Ellefi, Zohra Bellahsene, Stefan Dietze, Konstantin Todorov
Publié dans: he Semantic Web. Latest Advances and New Domains. ESWC 2016. Lecture Notes in Computer Science, Numéro vol 9678, 2016, Page(s) 36-51, ISBN 978-3-319-34128-6
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-34129-3_3

SPARQL Query Recommendations by Example

Auteurs: Carlo Allocca, Alessandro Adamou, Mathieu d’Aquin, Enrico Motta
Publié dans: The Semantic Web. ESWC 2016. Lecture Notes in Computer Science, Numéro vol 9989, 2016, Page(s) 128-133, ISBN 978-3-319-47601-8
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-47602-5_26

Using Worker Self-Assessments for Competence-Based Pre-Selection in Crowdsourcing Microtasks

Auteurs: Ujwal Gadiraju, Besnik Fetahu, Ricardo Kawase, Patrick Siehndel, Stefan Dietze
Publié dans: ACM Transactions on Computer-Human Interaction, Numéro 24/4, 2017, Page(s) 1-26, ISSN 1073-0516
Éditeur: Association for Computing Machinary, Inc.
DOI: 10.1145/3119930

The Impact of Topic Characteristics and Threat on Willingness to Engage with Wikipedia Articles: Insights from Laboratory Experiments

Auteurs: Seren Yenikent, Peter Holtz, Joachim Kimmerle
Publié dans: Frontiers in Psychology, Numéro 8, 2017, ISSN 1664-1078
Éditeur: Frontiers Research Foundation
DOI: 10.3389/fpsyg.2017.01960

Modus Operandi of Crowd Workers

Auteurs: Ujwal Gadiraju, Alessandro Checco, Neha Gupta, Gianluca Demartini
Publié dans: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Numéro 1/3, 2017, Page(s) 1-29, ISSN 2474-9567
Éditeur: ACM
DOI: 10.1145/3130914

VizRec

Auteurs: Belgin Mutlu, Eduardo Veas, Christoph Trattner
Publié dans: ACM Transactions on Interactive Intelligent Systems, Numéro 6/4, 2016, Page(s) 1-39, ISSN 2160-6455
Éditeur: Association for Computing Machinery (ACM)
DOI: 10.1145/2983923

KnowMore - Knowledge Base Augmentation with Structured Web Markup

Auteurs: Ran Yu Ujwal Gadiraju Besnik Fetahu Oliver Lehmberg Dominique Ritze Stefan Dietze
Publié dans: Semantic Web Journal, 2017, ISSN 1570-0844
Éditeur: IOS Press

Using big data techniques for measuring productive friction in mass collaboration online environments

Auteurs: Peter Holtz, Joachim Kimmerle, Ulrike Cress
Publié dans: International Journal of Computer-Supported Collaborative Learning, Numéro 13/4, 2018, Page(s) 439-456, ISSN 1556-1607
Éditeur: Springer Verlag
DOI: 10.1007/s11412-018-9285-y

Consensus dynamics in online collaboration systems

Auteurs: Ilire Hasani-Mavriqi, Dominik Kowald, Denis Helic, Elisabeth Lex
Publié dans: Computational Social Networks, Numéro 5/1, 2018, ISSN 2197-4314
Éditeur: SpringerOpen
DOI: 10.1186/s40649-018-0050-1

The triple-filter bubble: Using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers

Auteurs: Daniel Geschke, Jan Lorenz, Peter Holtz
Publié dans: British Journal of Social Psychology, Numéro 58/1, 2019, Page(s) 129-149, ISSN 0144-6665
Éditeur: Wiley-Blackwell
DOI: 10.1111/bjso.12286

Effects of Contributor Experience on the Quality of Health-Related Wikipedia Articles

Auteurs: Peter Holtz, Besnik Fetahu, Joachim Kimmerle
Publié dans: Journal of Medical Internet Research, Numéro 20/5, 2018, Page(s) e171, ISSN 1438-8871
Éditeur: Journal of medical Internet Research
DOI: 10.2196/jmir.9683

The influence of social status and network structure on consensus building in collaboration networks

Auteurs: Ilire Hasani-Mavriqi, Florian Geigl, Subhash Chandra Pujari, Elisabeth Lex, Denis Helic
Publié dans: Social Network Analysis and Mining, Numéro 6/1, 2016, Page(s) Sudies in Computational Intelligence, ISSN 1869-5450
Éditeur: Springer
DOI: 10.1007/s13278-016-0389-y

The Epistemology of Intelligent Semantic Web Systems

Auteurs: Mathieu d'Aquin, Enrico Motta
Publié dans: Synthesis Lectures on the Semantic Web: Theory and Technology, Numéro 6/1, 2016, Page(s) 1-88, ISSN 2160-4711
Éditeur: Morgan & Claypool
DOI: 10.2200/S00708ED1V01Y201603WBE014

How Popper’s ‘Three Worlds Theory’ Resembles Moscovici’s ‘Social Representations Theory’ But Why Moscovici’s Social Psychology of Science Still Differs From Popper’s Critical Approach

Auteurs: Peter HOLTZ, Leibniz-Institut für Wissensmedien IWM (Knowledge Media Research Center) – Knowledge, Construction Lab, Tübingen, Germany.
Publié dans: Papers on Social Representations, Numéro Volume 25, Numéro 1, 2016, Page(s) 13.1-13.24, ISSN 1021-5573
Éditeur: London School of Economics and Political Science

A productive clash of perspectives? The interplay between articles’ and authors’ perspectives and their impact on Wikipedia edits in a controversial domain

Auteurs: Jens Jirschitzka, Joachim Kimmerle, Iassen Halatchliyski, Julia Hancke, Detmar Meurers, Ulrike Cress
Publié dans: PLOS ONE, Numéro 12/6, 2017, Page(s) e0178985, ISSN 1932-6203
Éditeur: Public Library of Science
DOI: 10.1371/journal.pone.0178985

Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning

Auteurs: Simone Kopeinik
Publié dans: Journal of Web Science, Numéro 2/1, 2016, Page(s) 45-61, ISSN 2332-4031
Éditeur: Now Publishers
DOI: 10.1561/106.00000007

Facilitating Scientometrics in Learning Analytics and Educational Data Mining – the LAK Dataset

Auteurs: Stefan Dietze, Davide Taibi, Mathieu d’Aquin
Publié dans: Semantic Web, Numéro 8/3, 2016, Page(s) 395-403, ISSN 1570-0844
Éditeur: IOS Press
DOI: 10.3233/SW-150201

"""Make hay while the crowd shines: towards effective crowdsourcing on the web"" by Ujwal Gadiraju, with Prateek Jain as coordinator"

Auteurs: Ujwal Gadiraju
Publié dans: ACM SIGWEB Newsletter, Numéro Summer, 2016, Page(s) 1-1, ISSN 1931-1745
Éditeur: ACM
DOI: 10.1145/2956573.2956576

Improving Reliability of Crowdsourced Results by Detecting Crowd Workers with Multiple Identities

Auteurs: Ujwal Gadiraju, Ricardo Kawase
Publié dans: Web Engineering, Numéro 10360, 2017, Page(s) 190-205, ISBN 978-3-319-60130-4
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-60131-1_11

On the Use of Linked Open Data in Education: Current and Future Practices

Auteurs: Mathieu d’Aquin
Publié dans: Lecture Notes in Computer Science book series, Numéro LNCS, volume 9500, 2016, Page(s) 3-15, ISBN 978-3-319-30492-2
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-30493-9_1

Educational Linked Data on the Web - Exploring and Analysing the Scope and Coverage

Auteurs: Davide Taibi, Giovanni Fulantelli, Stefan Dietze, Besnik Fetahu
Publié dans: Open Data for Education. Lecture Notes in Computer Science, Numéro vol 9500, 2016, Page(s) 16-37, ISSN 0302-9743
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-30493-9_2

Open Data for Education

Auteurs: Dmitry Mouromtsev, Mathieu d’Aquin
Publié dans: Lecture Notes in Computer Science, 2016, ISBN 978-3-319-30493-9
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-319-30493-9

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