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- research-articleApril 2024
Intelligent reflecting surface-aided computation offloading in UAV-enabled edge networks
Wireless Networks (WIRE), Volume 30, Issue 5Jul 2024, Pages 3199–3210https://doi.org/10.1007/s11276-024-03731-3AbstractThe popularity of wireless communication technology and smart devices make emerging tasks tend to be computationally intensive. Unfortunately, mobile devices are often computationally resource-constrained. Mobile edge computing is proposed to ...
- research-articleFebruary 2024
- research-articleDecember 2023
Click is not equal to purchase: multi-task reinforcement learning for multi-behavior recommendation
World Wide Web (WWWJ), Volume 26, Issue 6Nov 2023, Pages 4153–4172https://doi.org/10.1007/s11280-023-01215-6AbstractReinforcement learning (RL) has achieved ideal performance in recommendation systems (RSs) by taking care of both immediate and future rewards from users. However, the existing RL-based recommendation methods assume that only a single type of ...
- research-articleAugust 2023
Sequential recommendation with probabilistic logical reasoning
IJCAI '23: Proceedings of the Thirty-Second International Joint Conference on Artificial IntelligenceAugust 2023, Article No.: 270, Pages 2432–2440https://doi.org/10.24963/ijcai.2023/270Deep learning and symbolic learning are two frequently employed methods in Sequential Recommendation (SR). Recent neural-symbolic SR models demonstrate their potential to enable SR to be equipped with concurrent perception and cognition capacities. ...
- research-articleJuly 2023
Multi-dimensional Graph Neural Network for Sequential Recommendation
Highlights- We design a multi-dimensional information integrated graph neural network, which integrates the category and time information into the graph embedding ...
Graph neural networks (GNNs) technology has been widely used in recommendation systems because most information in recommendation systems has a graph structure in nature, and GNNs have advantages in graph representation learning. In ...
- ArticleOctober 2022
Click is Not Equal to Purchase: Multi-task Reinforcement Learning for Multi-behavior Recommendation
Web Information Systems Engineering – WISE 2022Oct 2022, Pages 443–459https://doi.org/10.1007/978-3-031-20891-1_32AbstractReinforcement learning (RL) has achieved ideal performance in recommendation systems (RS) by taking care of both immediate and future rewards from users. However, the existing RL-based recommendation methods assume that only a single type of ...
- ArticleOctober 2021
Exploiting Intra and Inter-field Feature Interaction with Self-Attentive Network for CTR Prediction
Web Information Systems Engineering – WISE 2021Oct 2021, Pages 34–49https://doi.org/10.1007/978-3-030-91560-5_3AbstractClick-Through Rate (CTR) prediction models have achieved huge success mainly due to the ability to model arbitrary-order feature interactions. Recently, Self-Attention Network (SAN) has achieved significant success in CTR prediction. However, most ...
- ArticleOctober 2021
MGSAN: A Multi-granularity Self-attention Network for Next POI Recommendation
Web Information Systems Engineering – WISE 2021Oct 2021, Pages 193–208https://doi.org/10.1007/978-3-030-91560-5_14AbstractNext Point-of-Interest (POI) recommendation has become a vital research trend, helping people find interesting and attractive locations. Existing methods usually exploit the individual-level POI sequences but failed to utilize the information of ...
- ArticleApril 2021
Knowledge-Aware Hypergraph Neural Network for Recommender Systems
Database Systems for Advanced ApplicationsApr 2021, Pages 132–147https://doi.org/10.1007/978-3-030-73200-4_9AbstractKnowledge graph (KG) has been widely studied and employed as auxiliary information to alleviate the cold start and sparsity problems of collaborative filtering in recommender systems. However, most of the existing KG-based recommendation models ...
- ArticleAugust 2020
Spatio-Temporal Self-Attention Network for Next POI Recommendation
AbstractNext Point-of-Interest (POI) recommendation, which aims to recommend next POIs that the user will likely visit in the near future, has become essential in Location-based Social Networks (LBSNs). Various Recurrent Neural Network (RNN) based ...
- ArticleAugust 2020
Knowledge Graph Attention Network Enhanced Sequential Recommendation
AbstractKnowledge graph (KG) has recently been proved effective and attracted a lot of attentions in sequential recommender systems. However, the relations between the attributes of different entities in KG, which could be utilized to improve the ...
- research-articleJanuary 2020
Representation Learning of Knowledge Graphs with Embedding Subspaces
Most of the existing knowledge graph embedding models are supervised methods and largely relying on the quality and quantity of obtainable labelled training data. The cost of obtaining high quality triples is high and the data sources are facing a serious ...
- research-articleJanuary 2017
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing
- J. Alfredo Hernández-Pérez,
- Jian Wu,
- Chunhua Li,
- Xuefeng Xian,
- Zhiming Cui,
- Victor S. Sheng,
- Pengpeng Zhao
Computational Intelligence and Neuroscience (CIAN), Volume 20172017https://doi.org/10.1155/2017/4092135Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far ...
- ArticleDecember 2010
Traffic Video Segmentation and Key Frame Extraction Using Improved Global K-Means Clustering
ISISE '10: Proceedings of the 2010 Third International Symposium on Information Science and EngineeringDecember 2010, Pages 521–525https://doi.org/10.1109/ISISE.2010.133Huge amount of Traffic video segmented into manageable shots is the key step of database storage and video analysis in Intelligent Transportation Systems (ITS). Then key frames are extracted for representing main visual content of each shot. This paper ...
- chapterAugust 2009
Extension of OWL with Dynamic Fuzzy Logic
Advances in Web and Network Technologies, and Information ManagementAugust 2009, Pages 67–76https://doi.org/10.1007/978-3-642-03996-6_7In recent years, ontology has played a major role in knowledge representation. Ontology languages are based on description logics. Though they are expressive enough, they cannot express and reason with fuzzy and dynamic knowledge on the Semantic Web. To ...
- ArticleJuly 2009
Medical Image De-noising Extended Model Based on Independent Component Analysis and Dynamic Fuzzy Function
ICIE '09: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01July 2009, Pages 209–212https://doi.org/10.1109/ICIE.2009.196Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. This paper proposes a new extended model for CT medical ...
- ArticleJune 2009
Data Source Selection for Large-Scale Deep Web Data Integration
WMWA '09: Proceedings of the 2009 Second Pacific-Asia Conference on Web Mining and Web-based ApplicationJune 2009, Pages 178–182https://doi.org/10.1109/WMWA.2009.25Deep web has been an important resource on the web due to its rich and high quality information, leading to emerging a new application area in data mining and integrates. There may be hundreds or thousands of data sources providing data of relevance to ...