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Towards a folksonomy graph-based context-aware recommender system of annotated books
2021
Journal of Big Data
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The generated graphs express the semantic relatedness between these resources, i.e. books, by effectively modeling the folksonomy relationship between user-resource-tag and integrating contextual information ...
In this regard, this article presents a folksonomy graphs based context-aware recommender system (CARS) of annotated books. ...
Collaborative tagging techniques are useful for enhancing the recommendation of learning resources [4] . ...
doi:10.1186/s40537-021-00457-3
fatcat:iwudkpm6gfeqti3p2wmmcgb4oy
Towards Ranking in Folksonomies for Personalized Recommender Systems in E-Learning
2011
International Semantic Web Conference
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This paper proposes a conceptual architecture describing how these semantics can be integrated in a personalized recommender system for learning purposes. ...
Recommender systems offer the opportunity for users to no longer have to search for resources but rather have these resources offered to them considering their personal needs and contexts. ...
The responsibility for the contents of this publication lies with the authors. ...
dblp:conf/semweb/AnjorinRS11
fatcat:nt4mdbyrgraglevcjxxgjxunvq
Towards a Semantic Graph-based Recommender System. A Case Study of Cultural Heritage
2021
Journal of universal computer science (Online)
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Our proposed approach represents a semantic graph-based recommender system of cultural heritage places through two steps; (1) constructing an emergent semantic description that semantically augments the ...
However, collaborative tagging uses uncontrolled vocabulary which semanti- cally weakens the description of resources, consequently decreases their classification, clustering, thereby their recommendation ...
Figure 1: Emergent Semantic of resources towards a Semantic graph-based recommender system The emergent semantic of resources is modeled using a conceptual model (see Figure 2 ). ...
doi:10.3897/jucs.70330
fatcat:7m7h5whp4jhvzatit5hbd6hdu4
Creating knowledge graphs for geographic data on the web
2022
ACM SIGWEB Newsletter
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2023 pre-print arXiv:2302.08823v1 fatcat:y3nmxuwdundjvmtoteiisoztq4
Verification, enrichment and semantic representation are essential for making geographic data accessible for the Semantic Web and machine learning. ...
Geographic data plays an essential role in various Web, Semantic Web and machine learning applications. ...
ACKNOWLEDGMENTS This work was partially funded by DFG, German Research Foundation ("WorldKG", 424985896), the Federal Ministry for Economic Affairs and Climate Action (BMWK), Germany ("d-E-mand", 01ME19009B ...
doi:10.1145/3522598.3522602
fatcat:i3a3fqzb2zgzjgemnlzmqmzqxm
Folksonomy-Based Recommender Systems: A State-of-the-Art Review
2015
International Journal of Intelligent Systems
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Web pages, pictures and video) using open-ended tags. ...
In this context, tripartite relationships between users, resources and tags contained in folksonomies set new challenges for knowledge discovery approaches to be applied with recommendation purposes. ...
[82] adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. GroupMe! ...
doi:10.1002/int.21753
fatcat:ylf6d4a3ybdkpjrytblvgkvbuu
Tag Recommendation by Link Prediction Based on Supervised Machine Learning
2021
Proceedings of the ... International AAAI Conference on Weblogs and Social Media
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The tagging history of the identified set of users is merged in one temporal sequence on bipartite graphs. The obtained sequence is used to learn a model of link prediction in bipartite graphs. ...
The learned model is then applied to predict tags to be linked to the target resource and a list of top similar resources. ...
These graphs are combined to create a single resource-tag bipartite graph for training (G learn ). ...
doi:10.1609/icwsm.v6i1.14315
fatcat:tihqu7k5o5bpfg7a5yz336d4sa
Frontiers in multimedia search
2011
Proceedings of the 19th ACM international conference on Multimedia - MM '11
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Larson • Making the most of the user • Making the most of the collection and search environment • Making the most of multimedia items • Integration towards useful MIR systems • Making impact M. ...
Larson • Making the most of the user • Making the most of the collection and search environment • Making the most of multimedia items • Integration towards useful MIR systems • Making impact M. Larson ...
Frontiers in Multimedia Search, ACM Multimedia, Scottsdale, US, November 2011
Revealing Hidden Cool Places Near2Me video (9 minutes) ...
doi:10.1145/2072298.2072398
dblp:conf/mm/HanjalicL11
fatcat:txi4arbwdfcyhgqk25cdqfvxbm
Web Resources Annotation for the Web of Learning
2013
International Journal of Advanced Computer Science and Applications
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In the education field, reusing hypermedia web resources can support to a great deal the design of modern instructional environments and the development of interactive and non-linear material for learning ...
.Sharing and reusing these resources by different web applications and services presupposes that they are visible for retrieval through a semantic description of their content, function and relations ...
Semantic annotation is very practical for organizing web resources as it improves the search of resources on the web and provides useful recommendations based on the resource content and correlations between ...
doi:10.14569/ijacsa.2013.041118
fatcat:vyulhfb345byzhkbnppuk34tni
Recommender Systems, Semantic-Based
[chapter]
2014
Encyclopedia of Social Network Analysis and Mining
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In the context of semantic-based recommenders, social data such as tagging data can be combined with other types of information such as content data [14] or data from the Semantic Web [15] . ...
The recommendations of an RS can be based on different types of information. ...
doi:10.1007/978-1-4614-6170-8_116
fatcat:qdiedjovxrauxjitbpjx7zi3qe
A Proposed Model for Improving the Performance of Knowledge Bases in Real-World Applications by Extracting Semantic Information
2022
International Journal of Advanced Computer Science and Applications
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The results are then used to explore the feasibility of applying knowledge bases to real-world tasks such as user-centric information access by encoding entities with deep semantic knowledge. ...
such as content recommendation during a web search. ...
The role of knowledge bases in utilizing semantic information generated from knowledge graphs to enrich search results is an important milestone towards the transformation of text-based search engines ...
doi:10.14569/ijacsa.2022.0130214
fatcat:h6vbprjcg5gexkcsmllnftxsqa
Tagmantic
2010
Proceedings of the fourth ACM conference on Recommender systems - RecSys '10
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The methodology can be applied to different types of folksonomies which implies an enormous potential for future development of new recommender engines. ...
Tagmantic is a web based social recommendation and search service which exploits the rich information within folksonomies. ...
They enable the development of ontology based recommendation engines for arbitrary types of entities. ...
doi:10.1145/1864708.1864784
dblp:conf/recsys/MoldvayBFS10
fatcat:r27hnq32jrgkliccacucmeyrq4
Sound and Music Recommendation with Knowledge Graphs
2016
ACM Transactions on Intelligent Systems and Technology
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Tags and textual descriptions are exploited to extract and link entities to external graphs such as WordNet and DBpedia which are in turn used to semantically enrich the initial data. ...
Knowledge graphs are currently used, e.g., to explain search results, to explore knowledge spaces, to semantically enrich textual documents or to feed knowledge intensive applications such as recommender ...
ACKNOWLEDGMENTS The authors would like to thank Gabriel Vigliensoni for providing the user's listening habits corpus. ...
doi:10.1145/2926718
fatcat:z4m4rqda65g45ju46j4dybyq3y
Hybrid Music Recommendation Algorithm Based on Music Gene and Improved Knowledge Graph
2022
Security and Communication Networks
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Combining music as a specific recommendation object, a hybrid recommendation algorithm based on music genes and improved knowledge graph is proposed for the traditional single recommendation algorithm ...
In addition, deep learning method is applied to extract low-dimensional, abstract deep semantic features of users and items, based on which, score prediction is performed. ...
Tag2word models further discover the semantics of tag information to improve recommendation methods. Deep learning is widely adopted in tag-based recommender systems. ...
doi:10.1155/2022/5889724
fatcat:x6xngsp5grdurpziwg3tqvi72m
Media Authoring with Ontological Reasoning: Use Case for Multimedia Information Extraction
[chapter]
2012
Multimedia Information Extraction
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We work towards modeling a deep structure for content networks. ...
A navigation scheme with dynamic GUI shifts the interaction paradigm for content query and sharing. MF adopts a multimodal architecture anticipating emerging use cases and genres. ...
Acknowledgement The Authors wish to thank Allan Walker for international partnership initiatives; Jeff Meyers, Allen Fairchild, Aaron Phillips, and Angel Petrov for technology support. ...
doi:10.1002/9781118219546.ch23
fatcat:o6e3mhr3rzfftcfuytv5hhudfy
A Survey on Decision Support Systems in Social Media
2015
International Journal of Computer Applications Technology and Research
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Recommendations in social web are used to personalize the web [20] . Social Tagging System is one type of social media. ...
In this paper we present the survey of various recommendations in Social Tagging Systems (STSs) like tag, item, user and unified recommendations along with semantic web and also discussed about major thrust ...
Therefore, network-based methods are widely used to describe the tag-based graph. ...
doi:10.7753/ijcatr0409.1008
fatcat:zguexhxslvexxfpzdnnr2r4uma
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