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

Dominik Kowald, Emanuel Lacic, Dieter Theiler, Elisabeth Lex
2018 arXiv   pre-print
Furthermore, AFEL-REC can cope with any kind of data that is present in social learning environments such as resource metadata, user interactions or social tags.  ...  AFEL-REC is build upon a scalable software architecture to provide recommendations of learning resources in near real-time.  ...  While most recommender systems rely on rating-based data, AFEL-REC is also capable of processing relevant social information such as tags.  ... 
arXiv:1808.04603v1 fatcat:ymzv7gwiozetln76qbnfnh4hra

Tag-Based Resource Recommendation in Social Annotation Applications [chapter]

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin Burke
2011 Lecture Notes in Computer Science  
In this paper, we examine the specific case of tag-based resource recommendation and propose a linear-weighted hybrid for the task.  ...  Many researchers have concentrated on the important problem of tag recommendation. Less attention has been paid to the recommendation of resources in the context of social annotation systems.  ...  Tag-Based Resource Recommendation Algorithms Our definition of resource recommendation centers on the function φ, which assigns a real-valued score to each resource describing the relevance of the resource  ... 
doi:10.1007/978-3-642-22362-4_10 fatcat:jtq7jdgzsnb6jfhlr3ng4f4ueq

Long Time No See: The Probability of Reusing Tags as a Function of Frequency and Recency [article]

Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley
2013 arXiv   pre-print
In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory.  ...  By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as FolkRank, Pairwise Interaction Tensor Factorization and  ...  MostPopularr (MPr): The most popular tags by resource algorithm weights the tags based on their frequency in the tag assignments of the resource [16] .  ... 
arXiv:1312.5111v1 fatcat:shxup7nzubf3tlwzvzqeefrjiy

Long time no see

Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory.  ...  By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as FolkRank, Pairwise Interaction Tensor Factorization and  ...  MostPopularr (MPr): The most popular tags by resource algorithm weights the tags based on their frequency in the tag assignments of the resource [16] .  ... 
doi:10.1145/2567948.2576934 dblp:conf/www/KowaldSTL14 fatcat:zdt2itnu75agdcx53p2p3wpnzu

Recommendation by Example in Social Annotation Systems [chapter]

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin Burke
2011 Lecture Notes in Business Information Processing  
Recommendation by example is common in contemporary Internet applications providing resources similar to a user-selected example.  ...  Second, the manner in which users interact with social annotation systems vary producing datasets with variable characteristics and requiring different recommendation strategies to best satisfy their needs  ...  We use a recommender based on cosine similarity as a starting point, a simple algorithm that one might expect in a recommendation by example scenario.  ... 
doi:10.1007/978-3-642-23014-1_18 fatcat:ewx3y6q5zfcwxg37x2mpijljie

Resource recommendation in social annotation systems: A linear-weighted hybrid approach

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin Burke
2012 Journal of computer and system sciences (Print)  
To date, most efforts have concentrated on the problem of tag recommendation -personalized suggestions for possible annotations.  ...  and tagspecific resource recommendation.  ...  The aggregation of resources and tags used to describe them produces a rich information space in which users can interact [3] .  ... 
doi:10.1016/j.jcss.2011.10.006 fatcat:igzwkksfqzcx5fkwpbwbemcrti

Folksonomy Graphs Based Context-Aware Recommender System Using Spectral Clustering

Sara Qassimi, the Laboratory LISI, Department of Informatics, Faculty of Sciences Semlalia Marrakesh FSSM, Cadi Ayyad University, Morocco, El Hassan Abdelwahed, Meriem Hafidi
2020 International Journal of Machine Learning and Computing  
This article presents a folksonomy graphs based context-aware recommender system of resources.  ...  The generated graphs express the semantic relatedness between resources by effectively modelling the folksonomy relationship between user-resource-tag and integrating contextual information.  ...  Step 4: Recommendation Algorithm The recommender system will take advantage of emergent graphs of resources and tags (see Algorithm 1 Folksonomy Graph-based recommendations).  ... 
doi:10.18178/ijmlc.2020.10.1.899 fatcat:pdzjn2dipbdmjigby7zlivf5yq

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender [article]

Dominik Kowald, Paul Seitlinger, Christoph Trattner, Tobias Ley
2014 arXiv   pre-print
We assume that recommender systems are more successful, when they are based on a thorough understanding of how people process information.  ...  Second, an extensive evaluation based on this observation shows that a tag recommender interconnecting both levels and integrating time dependent forgetting on the lexical level results in high accuracy  ...  Acknowledgments: The authors would like to thank Andreas Hotho and Denis Parra for many valuable comments on this work.  ... 
arXiv:1402.0728v2 fatcat:6gcdfeu73fbebdp4s4hbcyazlq

Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender [chapter]

Dominik Kowald, Paul Seitlinger, Simone Kopeinik, Tobias Ley, Christoph Trattner
2014 Lecture Notes in Computer Science  
We assume that recommender systems are more successful, when they are based on a thorough understanding of how people process information.  ...  Second, an extensive evaluation based on this observation shows that a tag recommender interconnecting the semantic and lexical level based on a theory of human categorization and integrating time-dependent  ...  Based on our previous research and other incentives from related work, we introduce in this work a novel time-based tag recommender algorithm (= 3LT tag ) based on the MINERVA2 theory of human categorization  ... 
doi:10.1007/978-3-319-14723-9_5 fatcat:s6ulpjl7tvg5zekh65i2w3jajm

Hybrid Content and Tag-based Profiles for Recommendation in Collaborative Tagging Systems

Daniela Godoy, Analía Amandi
2008 2008 Latin American Web Conference  
On the other hand, numerous content-based profiling techniques have been developed to address the problem of obtaining accurate models of user information preferences in order to assist users with information-related  ...  In this paper we propose a hybrid user profiling strategy that takes advantage of both content-based profiles describing long-term information interests that a recommender system can acquired along time  ...  capturing the user interaction with one or more collaborative tagging systems.  ... 
doi:10.1109/la-web.2008.15 dblp:conf/la-web/GodoyA08 fatcat:zv2lomvvmbb63d5gzvaarqtkgm

Friend Recommendation in a Social Bookmarking System: Design and Architecture Guidelines [chapter]

Matteo Manca, Ludovico Boratto, Salvatore Carta
2015 Studies in Computational Intelligence  
Social media systems allow users to share resources with the people connected to them.  ...  As social media systems with different purposes arose, also different types of social recommender systems were developed in order to filter the specific information that each domain handles.  ...  Systems Based on the Interactions with the Content Quercia et al. [23] describe a user recommender system based on collocation.  ... 
doi:10.1007/978-3-319-14654-6_14 fatcat:x6umt2lmcnbarixm3iinrlgenu

Leveraging User-Interactions for Time-Aware Tag Recommendations

Daniel Zoller, Stephan Doerfel, Christian Pölitz, Andreas Hotho
2017 ACM Conference on Recommender Systems  
For the popular task of tag recommendation, various (complex) approaches have been proposed.  ...  Here, we follow up on these results by presenting another time-aware approach leveraging userinteraction data in an easily interpretable, on-the-y computable approach that can successfully be combined  ...  As for all recommender domains, tag recommender algorithms can roughly be classi ed into three classes: Content-based algorithms use the content of resources, for instance to compute similarities between  ... 
dblp:conf/recsys/ZollerDPH17 fatcat:mqtjtaxgizcttdfwsa4ehcofre

Hybrid tag recommendation for social annotation systems

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin Burke
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
Among these approaches are recommendation models based on matrix factorization.  ...  Social annotation systems allow users to annotate resources with personalized tags and to navigate large and complex information spaces without the need to rely on predefined hierarchies.  ...  While such an algorithm would include tags frequently applied by the user, it does not consider the resource information and may recommend tags irrelevant to the current resource.  ... 
doi:10.1145/1871437.1871543 dblp:conf/cikm/GemmellSMB10 fatcat:6cquugopcndrxe3nnrwvucg4fu

Research on Personalized Recommendation of Educational Resources Based on Big Data

Dewen Seng, Xiuli Chen, Xujian Fang, Xuefeng Zhang, Jing Chen
2018 Educational Sciences: Theory & Practice  
With the rapid development of Internet technology, the era of education informationization has arrived. With massive education resources, users are faced with the problem of information overload.  ...  This essay takes the management of educational resources and the big data which form the platform as the background, and designs a personalized recommendation algorithm of educational resources according  ...  User -Item Rating Estimation ProcessUser interest model based on topic modelAnalyze hash-tag (system information and user-defined label) under educational resources based on LDA topic model; establish  ... 
doi:10.12738/estp.2018.5.094 fatcat:5jzvjycrprc6pnhqx32y46cgpm

Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics [article]

Paul Seitlinger, Dominik Kowald, Simone Kopeinik, Ilire Hasani-Mavriqi, Tobias Ley, Elisabeth Lex
2015 arXiv   pre-print
Classic resource recommenders like Collaborative Filtering (CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and interpretation.  ...  In this paper, we propose a novel hybrid recommendation strategy that refines CF by capturing these dynamics.  ...  CF aims to recommend resources to a user based on the digital traces she leaves behind on the Web, i.e., her interactions with resources and the interactions of other similar users.  ... 
arXiv:1501.07716v1 fatcat:bvrxaiju4zdbpbjit24e6hv7xm
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