Graph neural networks for link prediction with subgraph sketching
Many Graph Neural Networks (GNNs) perform poorly compared to simple heuristics on Link
Prediction (LP) tasks. This is due to limitations in expressive power such as the inability to …
Prediction (LP) tasks. This is due to limitations in expressive power such as the inability to …
Twhin: Embedding the twitter heterogeneous information network for personalized recommendation
Social networks, such as Twitter, form a heterogeneous information network (HIN) where
nodes represent domain entities (eg, user, content, advertiser, etc.) and edges represent …
nodes represent domain entities (eg, user, content, advertiser, etc.) and edges represent …
Detecting abusive Instagram comments in Turkish using convolutional Neural network and machine learning methods
Instagram is a free photo-sharing platform where each user has a profile and can upload
photos for followers to view, like, and comment. Abusive comments on images can be …
photos for followers to view, like, and comment. Abusive comments on images can be …
Efficient link prediction via gnn layers induced by negative sampling
Graph neural networks (GNNs) for link prediction can loosely be divided into two broad
categories. First, node-wise architectures pre-compute individual embeddings for each node …
categories. First, node-wise architectures pre-compute individual embeddings for each node …
Semantics and content-based recommendations
Content-based recommendations suggest items similar to those the user already liked in the
past by building a representation of users and items based on descriptive features, which …
past by building a representation of users and items based on descriptive features, which …
[HTML][HTML] Word2Vec-based efficient privacy-preserving shared representation learning for federated recommendation system in a cross-device setting
Recommendation systems have required centralized storage of user data, but due to privacy
concerns, recent studies adopted federated learning (FL) that discloses intermediate …
concerns, recent studies adopted federated learning (FL) that discloses intermediate …
[PDF][PDF] Predicting Feature-based Similarity in the News Domain Using Human Judgments.
When reading an online news article, users are typically presented 'more like this'
recommendations by news websites. In this study, we assessed different similarity functions …
recommendations by news websites. In this study, we assessed different similarity functions …
[HTML][HTML] Patient embeddings from diagnosis codes for health care prediction tasks: Pat2Vec machine learning framework
Background In health care, diagnosis codes in claims data and electronic health records
(EHRs) play an important role in data-driven decision making. Any analysis that uses a …
(EHRs) play an important role in data-driven decision making. Any analysis that uses a …
DSER: Deep-sequential embedding for single domain recommendation
Abstract Recently, Deep Neural Networks (DNNs) have proved their capability to model
nonlinear relationships between users and items in recommender systems. Therefore, many …
nonlinear relationships between users and items in recommender systems. Therefore, many …
A hybrid Hadoop-based sentiment analysis classifier for tweets associated with COVID-19 utilizing two machine learning algorithms: CNN, and fuzzy C4. 5
In recent years, research on opinion mining from X (formerly Twitter) has rapidly advanced,
focusing on processing tweets to determine user sentiments about events. Many …
focusing on processing tweets to determine user sentiments about events. Many …