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Found 12 papers, 6 papers with code
Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data
This integration provides rich indicators of pandemic dynamics through learning with temporal graph neural networks.
Few-Shot Nested Named Entity Recognition
Leveraging contextual dependency to distinguish nested entities, we propose a Biaffine-based Contrastive Learning (BCL) framework.
Multimodal Review Generation with Privacy and Fairness Awareness
Users express their opinions towards entities (e. g., restaurants) via online reviews which can be in diverse forms such as text, ratings, and images.
Privacy-Preserving Visual Content Tagging using Graph Transformer Networks
With the rapid growth of Internet media, content tagging has become an important topic with many multimedia understanding applications, including efficient organisation and search.
Privacy-Preserving Visual Content Tagging using Graph Transformer Networks
With the rapid growth of Internet media, content tagging has become an important topic with many multimedia understanding applications, including efficient organisation and search.
KBot: a Knowledge graph based chatBot for natural language understanding over linked data
With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs).
Generic Multilayer Network Data Analysis with the Fusion of Content and Structure
Multi-feature data analysis (e. g., on Facebook, LinkedIn) is challenging especially if one wants to do it efficiently and retain the flexibility by choosing features of interest for analysis.
dpUGC: Learn Differentially Private Representation for User Generated Contents
To our best knowledge, this is the first work of learning user-level differentially private word embedding model from text for sharing.
ETNLP: a visual-aided systematic approach to select pre-trained embeddings for a downstream task
We demonstrate the effectiveness of the proposed approach on our pre-trained word embedding models in Vietnamese to select which models are suitable for a named entity recognition (NER) task.
Self-adaptive Privacy Concern Detection for User-generated Content
To protect user privacy in data analysis, a state-of-the-art strategy is differential privacy in which scientific noise is injected into the real analysis output.
Lexical-semantic resources: yet powerful resources for automatic personality classification
In this paper, we aim to reveal the impact of lexical-semantic resources, used in particular for word sense disambiguation and sense-level semantic categorization, on automatic personality classification task.
