| Nome |
# |
|
Towards Consumer-Empowering Artificial Intelligence, file e31e124d-a24d-987f-e053-3705fe0a095a
|
975
|
|
An Argumentation-based Perspective over the Social IoT, file e31e124d-5945-987f-e053-3705fe0a095a
|
543
|
|
Comparing deep learning and statistical methods in forecasting crowd distribution from aggregated mobile phone data, file e31e124e-c74d-987f-e053-3705fe0a095a
|
337
|
|
Deep learning for detecting and explaining unfairness in consumer contracts, file e31e124e-c749-987f-e053-3705fe0a095a
|
284
|
|
Natural Language Statistical Features of LSTM-Generated Texts, file e31e124d-a24c-987f-e053-3705fe0a095a
|
268
|
|
Texture analysis and multiple-instance learning for the classification of malignant lymphomas, file e31e124e-7790-987f-e053-3705fe0a095a
|
240
|
|
Explaining potentially unfair clauses to the consumer with the claudette tool, file e31e124e-c746-987f-e053-3705fe0a095a
|
214
|
|
Argumentation mining: State of the art and emerging trends, file e31e1250-4e81-987f-e053-3705fe0a095a
|
211
|
|
MetalDetector: A web server for predicting metal-binding sites and disulfide bridges in proteins from sequence, file e31e124c-cc06-987f-e053-3705fe0a095a
|
170
|
|
Attention in Natural Language Processing, file e31e124e-afed-987f-e053-3705fe0a095a
|
156
|
|
Evaluating origin–destination matrices obtained from CDR data, file e31e124e-0490-987f-e053-3705fe0a095a
|
148
|
|
GDPR privacy policies in CLAUDETTE: Challenges of omission, context and multilingualism, file e31e124e-cc6d-987f-e053-3705fe0a095a
|
147
|
|
The Force Awakens: Artificial intelligence for consumer law, file e31e124e-c748-987f-e053-3705fe0a095a
|
142
|
|
Automated detection of unfair clauses in online consumer contracts, file e31e124e-cc68-987f-e053-3705fe0a095a
|
132
|
|
Automated processing of privacy policies under the EU general data protection regulation, file e31e124e-a974-987f-e053-3705fe0a095a
|
129
|
|
MetalDetector v2.0: Predicting the geometry of metal binding sites from protein sequence, file e31e124c-837e-987f-e053-3705fe0a095a
|
114
|
|
Detecting and explaining unfairness in consumer contracts through memory networks, file e31e1250-727d-987f-e053-3705fe0a095a
|
110
|
|
Editorial: Statistical relational artificial intelligence, file e31e124e-c74f-987f-e053-3705fe0a095a
|
95
|
|
Predicting the usefulness of amazon reviews using off-the-shelf argumentation mining, file e31e124e-cc64-987f-e053-3705fe0a095a
|
90
|
|
Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches, file e31e124f-1b4d-987f-e053-3705fe0a095a
|
90
|
|
Argument mining on clinical trials, file e31e124e-cc66-987f-e053-3705fe0a095a
|
85
|
|
Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?, file e31e124f-d866-987f-e053-3705fe0a095a
|
78
|
|
A General Pipeline for Online Gesture Recognition in Human–Robot Interaction, file 10ca4e74-c92a-4584-8b22-1f26dc213aa3
|
69
|
|
Constraint detection in natural language problem descriptions, file e31e124e-cc6f-987f-e053-3705fe0a095a
|
68
|
|
Predict Cellular network traffic with markov logic, file e31e124e-a976-987f-e053-3705fe0a095a
|
43
|
|
An Argumentation-based Perspective over the Social IoT, file e31e124f-c2a2-987f-e053-3705fe0a095a
|
37
|
|
MARGOT: A web server for argumentation mining, file e31e1250-09ae-987f-e053-3705fe0a095a
|
35
|
|
Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning, file ec39e44f-d495-4736-be01-782a694083dc
|
35
|
|
Individual and Collective Self-Development: Concepts and Challenges, file e5dd5890-be7d-4cb2-8a88-02db69aef1bd
|
27
|
|
Assessing the Cross-Market Generalization Capability of the CLAUDETTE System, file e243c5a7-1238-48ba-a892-a97d3b4d2186
|
23
|
|
Demand Forecasting Methods: A Case Study in the Italian Processed Meat Industry, file e05d4979-10f9-47d6-851f-9db6c44b03d7
|
22
|
|
Argument mining as rapid screening tool of COVID-19 literature quality: Preliminary evidence, file 877df2c5-1530-4844-aee5-cf5d94c787a7
|
18
|
|
Poka Yoke Meets Deep Learning: A Proof of Concept for an Assembly Line Application, file ad2d5cd6-8a64-4015-bca8-9a4a2bd4cf24
|
16
|
|
A General Pipeline for Online Gesture Recognition in Human–Robot Interaction, file 69c9a212-abc6-4570-9092-80f9070f7f21
|
14
|
|
Application of Machine Learning Demand Forecasting Techniques in the Italian Processed Meat Industry, file 6e788a8f-0adf-4111-8bf4-fe9b0517b1f0
|
14
|
|
Natural Language Statistical Features of LSTM-Generated Texts, file e31e1250-20b8-987f-e053-3705fe0a095a
|
10
|
|
Multi-Task Attentive Residual Networks for Argument Mining, file 0aa486ff-0e15-4375-97ec-815b84cf7a59
|
9
|
|
Characterization of metalloproteins by high-throughput X-ray absorption spectroscopy, file e31e124c-8d7b-987f-e053-3705fe0a095a
|
6
|
|
Type Extension Trees for feature construction and learning in relational domains, file e31e124c-cce5-987f-e053-3705fe0a095a
|
6
|
|
CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service, file e31e124d-a96b-987f-e053-3705fe0a095a
|
6
|
|
Markov logic networks for optical chemical structure recognition, file e31e124c-d7ae-987f-e053-3705fe0a095a
|
5
|
|
CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service, file e31e124f-fc4a-987f-e053-3705fe0a095a
|
5
|
|
Relational information gain, file e31e124c-caf3-987f-e053-3705fe0a095a
|
3
|
|
En plein air visual agents, file e31e124c-d5a2-987f-e053-3705fe0a095a
|
3
|
|
Argument mining: A machine learning perspective, file e31e124c-d066-987f-e053-3705fe0a095a
|
2
|
|
Context-independent claim detection for argument mining, file e31e124c-d08d-987f-e053-3705fe0a095a
|
2
|
|
Lead time forecasting with machine learning techniques for a pharmaceutical supply chain, file e31e124f-d88c-987f-e053-3705fe0a095a
|
2
|
|
Semantic video labeling by developmental visual agents, file e31e124c-87ef-987f-e053-3705fe0a095a
|
1
|
|
Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning, file e31e124c-87f2-987f-e053-3705fe0a095a
|
1
|
|
MARGOT: A web server for argumentation mining, file e31e124c-cb5f-987f-e053-3705fe0a095a
|
1
|
|
Collective traffic forecasting, file e31e124c-cff4-987f-e053-3705fe0a095a
|
1
|
|
Metal binding in proteins: Machine learning complements X-ray absorption spectroscopy, file e31e124c-d31d-987f-e053-3705fe0a095a
|
1
|
|
Argumentation in social media, file e31e124d-0e3e-987f-e053-3705fe0a095a
|
1
|
| Totale |
5.244 |
