I Know Your Intent: Graph-enhanced Intent-aware User Device Interaction Prediction via Contrastive Learning
With the booming of smart home market, intelligent Internet of Things (IoT) devices have
been increasingly involved in home life. To improve the user experience of smart homes …
been increasingly involved in home life. To improve the user experience of smart homes …
[PDF][PDF] User Device Interaction Prediction via Relational Gated Graph Attention Network and Intent-aware Encoder
With fast-evolving IoT solutions, the number of smart devices in homes have soared,
expected to reach 5 billion by 2025 [13]. The emergence of cloud platforms also allows IoT …
expected to reach 5 billion by 2025 [13]. The emergence of cloud platforms also allows IoT …
Beyond clicks: Modeling multi-relational item graph for session-based target behavior prediction
Session-based target behavior prediction aims to predict the next item to be interacted with
specific behavior types (eg, clicking). Although existing methods for session-based behavior …
specific behavior types (eg, clicking). Although existing methods for session-based behavior …
Dynamic embeddings for interaction prediction
In recommender systems (RSs), predicting the next item that a user interacts with is critical
for user retention. While the last decade has seen an explosion of RSs aimed at identifying …
for user retention. While the last decade has seen an explosion of RSs aimed at identifying …
Two-tier graph contextual embedding for cross-device user matching
The cross-device user matching task is to identify the behavior-logs (ie, behavior
sequences) on multiple devices that belong to one real person. Due to its anonymous and …
sequences) on multiple devices that belong to one real person. Due to its anonymous and …
Recursive RNN based shift representation learning for dynamic user-item interaction prediction
C Yin, S Wang, J Du, M Zhang - … 2020, Foshan, China, November 12–14 …, 2020 - Springer
Accurately predicting user-item interactions is critically important in many real applications
including recommender systems and user behavior analysis in social networks. One …
including recommender systems and user behavior analysis in social networks. One …
Predicting Dynamic User–Item Interaction with Meta-Path Guided Recursive RNN
Y Liu, C Yin, J Li, F Wang, S Wang - Algorithms, 2022 - mdpi.com
Accurately predicting user–item interactions is critically important in many real applications,
including recommender systems and user behavior analysis in social networks. One major …
including recommender systems and user behavior analysis in social networks. One major …
Facilitate interactions with devices in the internet of things (iot) with context-awareness
J Hua - 2022 - repositories.lib.utexas.edu
With the recent advances in the Internet of Things (IoT), more and more smart devices are
entering our everyday life. From light to door, these devices are usually capable of wireless …
entering our everyday life. From light to door, these devices are usually capable of wireless …
Towards automating smart homes: Contextual and temporal dynamics of activity prediction
The existing smart-home ecosystem has the capability to perceiving the ambient
environment by using cutting-edge sensing technologies but is limited to reacting …
environment by using cutting-edge sensing technologies but is limited to reacting …
TAP: A Transformer based Activity Prediction Exploiting Temporal Relations in Collaborative Tasks
H Kim, D Lee - … Workshops and other Affiliated Events (PerCom …, 2021 - ieeexplore.ieee.org
Activity prediction is an important challenge to provide cognitive supports in a smart space.
For user activity prediction without privacy and inconsistent data collection issues, recent …
For user activity prediction without privacy and inconsistent data collection issues, recent …