Temporal feature aggregation with attention for insider threat detection from activity logs

P Pal, P Chattopadhyay, M Swarnkar - Expert Systems with Applications, 2023 - Elsevier
Nowadays, insider attacks are emerging as one of the top cybersecurity threats. However,
the detection of insider threats is a more arduous task for many reasons. A significant cause …

GS-CBR-KBQA: Graph-structured case-based reasoning for knowledge base question answering

J Li, X Luo, G Lu - Expert Systems with Applications, 2024 - Elsevier
Abstract Knowledge Base Question Answering (KBQA) task is an important research
direction in natural language processing. Due to the flexibility and ambiguity of natural …

[HTML][HTML] Synset2Node: A new synset embedding based upon graph embeddings

F Jafarinejad - Intelligent Systems with Applications, 2023 - Elsevier
Due to the advances made in recent years, embedding methods caused a significant
increase in the accuracy of text or graph processing methods. Embedding methods exhibit a …

Hierarchical knowledge graph relationship prediction leverage of axiomatic fuzzy set graph structure

Y Fang, Q Lang, W Lu, X Liu, J Yang - Expert Systems with Applications, 2024 - Elsevier
Abstract Knowledge graph embedding has found widespread application across various
fields due to its inherent structured data. However, some non-graph-based models …

A Novel Joint Training Model for Knowledge Base Question Answering

S Wang, B Qin - IEEE/ACM Transactions on Audio, Speech …, 2023 - ieeexplore.ieee.org
In knowledge base question answering (KBQA) systems, relation detection and entity
recognition are two core components. However, since the relation detection in KBQA …

Knowledge Base Question Answering via Semantic Analysis

Y Liu, H Zhang, T Zong, J Wu, W Dai - Electronics, 2023 - mdpi.com
Knowledge Question Answering is one of the important research directions in the field of
robot intelligence. It is mainly based on background knowledge to analyze users' questions …

Question-Answering System Powered by Knowledge Graph and Generative Pretrained Transformer to Support Risk Identification in Tunnel Projects

MA Isah, BS Kim - Journal of Construction Engineering and …, 2025 - ascelibrary.org
Risk identification is fundamental to effective risk management in any construction project. It
is especially true for tunnel projects where technicality and complexity increase the risks …

A Decoupling and Aggregating Framework for Joint Extraction of Entities and Relations

Y Wang, X Liu, W Kong, HT Yu, T Racharak… - IEEE …, 2024 - ieeexplore.ieee.org
Named Entity Recognition and Relation Extraction are two crucial and challenging subtasks
in Information Extraction. Despite the successes achieved by the traditional approaches …

Benefiting from Structured Resources to Present a Computationally Efficient Word Embedding Method

F Jafarinejad - Journal of AI and Data Mining, 2022 - jad.shahroodut.ac.ir
In recent years, new word embedding methods have clearly improved the accuracy of NLP
tasks. A review of the progress of these methods shows that the complexity of these models …

[PDF][PDF] A Study on Joint Extraction of Entities and Relations based on Constructing Differentiated Subtask-Specific Features and Enabling Fine-Grained Information …

王堯 - 2024 - dspace02.jaist.ac.jp
Extracting entities and relations from raw texts is a crucial and challenging task in the field of
Information Extraction. Despite the successes achieved by the traditional approaches …