| Nome |
# |
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Personalized Finance Advisory through Case-based Recommender Systems and Diversification Strategies, file dd9e0c6b-d85d-1e9c-e053-3a05fe0a45ef
|
240
|
|
An Investigation on the Serendipity Problem in Recommender Systems, file 05f3c001-f4e8-4b28-8bf6-69afad67272b
|
154
|
|
Linked open data-based explanations for transparent recommender systems, file dd9e0c6b-e15d-1e9c-e053-3a05fe0a45ef
|
107
|
|
Introducing linked open data in graph-based recommender systems, file dd9e0c6b-cd47-1e9c-e053-3a05fe0a45ef
|
99
|
|
Concept-based item representations for a cross-lingual content-based recommendation process, file dd9e0c6b-aa55-1e9c-e053-3a05fe0a45ef
|
71
|
|
CrowdPulse: A framework for real-time semantic analysis of social streams, file 119dd791-daaf-4765-a96e-7d69581ee197
|
64
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|
TV-Program Retrieval and Classification: A Comparison of Approaches based on Machine Learning, file dd9e0c6b-cc74-1e9c-e053-3a05fe0a45ef
|
34
|
|
null, file dd9e0c6b-e528-1e9c-e053-3a05fe0a45ef
|
29
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|
null, file dd9e0c6c-01e2-1e9c-e053-3a05fe0a45ef
|
20
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Semantics-aware Recommender Systems exploiting Linked Open Data and graph-based features, file 61886673-34bb-4e7b-9803-9b3b76155bcb
|
18
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Recognizing users feedback from non-verbal communicative acts in conversational recommender systems, file dd9e0c6b-cc6f-1e9c-e053-3a05fe0a45ef
|
16
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Social question answering: Textual, user, and network features for best answer prediction, file dd9e0c63-f1c9-1e9c-e053-3a05fe0a45ef
|
13
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Playing with Knowledge: A Virtual Player for "Who Wants to Be a Millionaire?" that Leverages Question Answering Techniques, file dd9e0c62-85ab-1e9c-e053-3a05fe0a45ef
|
12
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|
null, file dd9e0c64-9152-1e9c-e053-3a05fe0a45ef
|
12
|
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Personalized Finance Advisory through Case-based Recommender Systems and Diversification Strategies, file dd9e0c67-1d4e-1e9c-e053-3a05fe0a45ef
|
12
|
|
Playing with Knowledge: A Virtual Player for "Who Wants to Be a Millionaire?" that Leverages Question Answering Techniques, file dd9e0c69-fca7-1e9c-e053-3a05fe0a45ef
|
12
|
|
null, file dd9e0c67-19a2-1e9c-e053-3a05fe0a45ef
|
11
|
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Power to the patients: The HealthNet social network, file dd9e0c64-8fdf-1e9c-e053-3a05fe0a45ef
|
10
|
|
null, file dd9e0c62-f248-1e9c-e053-3a05fe0a45ef
|
9
|
|
Concept-based item representations for a cross-lingual content-based recommendation process, file dd9e0c63-8f49-1e9c-e053-3a05fe0a45ef
|
9
|
|
TV-Program Retrieval and Classification: A Comparison of Approaches based on Machine Learning, file dd9e0c64-98fa-1e9c-e053-3a05fe0a45ef
|
8
|
|
Recognizing users feedback from non-verbal communicative acts in conversational recommender systems, file dd9e0c67-1d47-1e9c-e053-3a05fe0a45ef
|
8
|
|
Linked open data-based explanations for transparent recommender systems, file dd9e0c67-3604-1e9c-e053-3a05fe0a45ef
|
7
|
|
Introducing linked open data in graph-based recommender systems, file dd9e0c63-f8b9-1e9c-e053-3a05fe0a45ef
|
6
|
|
Social question answering: Textual, user, and network features for best answer prediction, file dd9e0c6b-c837-1e9c-e053-3a05fe0a45ef
|
6
|
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Extracting relations from Italian Wikipedia using unsupervised information extraction, file 9965d6c5-b6f9-47eb-9427-30d312554735
|
5
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MyrrorBot: A Digital Assistant Based on Holistic User Models for Personalized Access to Online Services, file dd9e0c6b-4177-1e9c-e053-3a05fe0a45ef
|
5
|
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Extracting relations from Italian wikipedia using self-training, file dd9e0c6b-4d00-1e9c-e053-3a05fe0a45ef
|
4
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Power to the patients: The HealthNet social network, file dd9e0c6b-e3dd-1e9c-e053-3a05fe0a45ef
|
4
|
|
MQALD: Evaluating the impact of modifiers in question answering over knowledge graphs., file dd9e0c6b-eb31-1e9c-e053-3a05fe0a45ef
|
4
|
|
1st Workshop on AI for Public Administration, file 84752cf8-7547-4f45-8127-0ee00f398f51
|
3
|
|
AI-based Decision Support Systems for the Management of E-procurement Procedures, file a6ade350-26ee-4e15-9c27-26717007e58e
|
3
|
|
An investigation on the user interaction modes of conversational recommender systems for the music domain, file dd9e0c66-f0a6-1e9c-e053-3a05fe0a45ef
|
3
|
|
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’21), file dd9e0c6b-6c3a-1e9c-e053-3a05fe0a45ef
|
3
|
|
null, file dd9e0c6c-5c3d-1e9c-e053-3a05fe0a45ef
|
3
|
|
null, file dd9e0c63-aac6-1e9c-e053-3a05fe0a45ef
|
2
|
|
null, file dd9e0c65-bc41-1e9c-e053-3a05fe0a45ef
|
2
|
|
null, file dd9e0c67-320c-1e9c-e053-3a05fe0a45ef
|
2
|
|
null, file dd9e0c67-e7b3-1e9c-e053-3a05fe0a45ef
|
2
|
|
A deep learning model for the analysis of medical reports in ICD-10 clinical coding task, file dd9e0c6a-59cc-1e9c-e053-3a05fe0a45ef
|
2
|
|
Generating post hoc review-based natural language justifications for recommender systems, file dd9e0c6b-5aa5-1e9c-e053-3a05fe0a45ef
|
2
|
|
Improving preference elicitation in a conversational recommender system with active learning strategies, file dd9e0c6b-6bf4-1e9c-e053-3a05fe0a45ef
|
2
|
|
Generating post hoc review-based natural language justifications for recommender systems, file dd9e0c6b-8432-1e9c-e053-3a05fe0a45ef
|
2
|
|
MQALD: Evaluating the impact of modifiers in question answering over knowledge graphs., file dd9e0c6b-d034-1e9c-e053-3a05fe0a45ef
|
2
|
|
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’22), file 71e6c6a5-e4ab-4266-ab8d-7a43636c76bf
|
1
|
|
Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures, file bb8ebb3b-c757-46d3-afa2-50c54306a3b3
|
1
|
|
Combining Graph Neural Networks and Sentence Encoders for Knowledge-aware Recommendations, file c5f8e05a-cd6a-4fe9-aa76-49088d57e65b
|
1
|
|
Learning Customer Profiles Using Unlabelled Data, file dd9e0c62-62a2-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c63-915c-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c63-9d2d-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c63-b1b7-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c63-b26b-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c63-b9a2-1e9c-e053-3a05fe0a45ef
|
1
|
|
Knowledge Infusion into Content-based Recommender Systems, file dd9e0c64-0330-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c64-89c9-1e9c-e053-3a05fe0a45ef
|
1
|
|
A hybrid recommendation framework exploiting linked open data & graph-based features, file dd9e0c64-9831-1e9c-e053-3a05fe0a45ef
|
1
|
|
IntRS 2014 Interfaces and Human Decision Making for Recommender Systems,
Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
co-located with ACM Conference on Recommender Systems (RecSys 2014).
Foster City, Silicon Valley, USA, October 6, 2014, file dd9e0c64-d7cf-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c64-dbfd-1e9c-e053-3a05fe0a45ef
|
1
|
|
Report on RecSys 2016 Workshop on New Trends in Content-Based Recommender Systems, file dd9e0c64-e221-1e9c-e053-3a05fe0a45ef
|
1
|
|
A Content-Collaborative Recommender that Exploits WordNet-based User Profiles for Neighborhood Formation, file dd9e0c64-e6e8-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c64-e79e-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c65-7f2e-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c65-8028-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c65-fa45-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-5412-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-d6f2-1e9c-e053-3a05fe0a45ef
|
1
|
|
A Framework for building Chat-based Recommender Systems, file dd9e0c66-da93-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-ec34-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-ee71-1e9c-e053-3a05fe0a45ef
|
1
|
|
Handling Modifiers in Question Answering over Knowledge Graphs, file dd9e0c66-f3f8-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-f69b-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-f7c1-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c67-2724-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c67-6919-1e9c-e053-3a05fe0a45ef
|
1
|
|
Solving a Complex Language Game by using Knowledge-based Word Associations Discovery, file dd9e0c69-cd0d-1e9c-e053-3a05fe0a45ef
|
1
|
|
A framework for Personalized Wealth Management exploiting Case-Based Recommender Systems, file dd9e0c6a-bcf4-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6b-0d7e-1e9c-e053-3a05fe0a45ef
|
1
|
|
Fairness and Popularity Bias in Recommender Systems: an Empirical Evaluation, file dd9e0c6b-f558-1e9c-e053-3a05fe0a45ef
|
1
|
| Totale |
1.076 |