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In exploratory search tasks, alongside information retrieval, information representation is an important factor in sensemaking. In this paper, we explore a multi-layer extension to knowledge graphs, hierarchical knowledge graphs (HKGs),…

Information Retrieval · Computer Science 2020-05-06 Bahareh Sarrafzadeh , Adam Roegiest , Edward Lank

In this paper, we explore different approaches to anomaly detection on dynamic knowledge graphs, specifically in a Micro-services environment for Kubernetes applications. Our approach explores three dynamic knowledge graph representations:…

Machine Learning · Computer Science 2024-11-12 Xiaohua Lu , Leshanshui Yang

Graph Transformers (GTs) have recently achieved significant success in the graph domain by effectively capturing both long-range dependencies and graph inductive biases. However, these methods face two primary challenges: (1) multi-view…

Machine Learning · Computer Science 2025-01-03 Xiaotang Wang , Yun Zhu , Haizhou Shi , Yongchao Liu , Chuntao Hong

This paper proposes a discrete knowledge graph (KG) embedding (DKGE) method, which projects KG entities and relations into the Hamming space based on a computationally tractable discrete optimization algorithm, to solve the formidable…

Information Retrieval · Computer Science 2021-01-14 Yunqi Li , Shuyuan Xu , Bo Liu , Zuohui Fu , Shuchang Liu , Xu Chen , Yongfeng Zhang

Decentralized collaborative learning for Point-of-Interest (POI) recommendation has gained research interest due to its advantages in privacy preservation and efficiency, as it keeps data locally and leverages collaborative learning among…

Information Retrieval · Computer Science 2024-10-15 Ruiqi Zheng , Liang Qu , Guanhua Ye , Tong Chen , Yuhui Shi , Hongzhi Yin

Knowledge graphs (KGs) are the cornerstone of the semantic web, offering up-to-date representations of real-world entities and relations. Yet large language models (LLMs) remain largely static after pre-training, causing their internal…

Computation and Language · Computer Science 2026-03-24 Songlin Zhai , Guilin Qi , Yue Wang , Yuan Meng

Probabilistic dependency graphs (PDGs) are a flexible class of probabilistic graphical models, subsuming Bayesian Networks and Factor Graphs. They can also capture inconsistent beliefs, and provide a way of measuring the degree of this…

Data Structures and Algorithms · Computer Science 2023-11-10 Oliver E. Richardson , Joseph Y. Halpern , Christopher De Sa

Recently, Knowledge Graphs (KGs) have been successfully coupled with Large Language Models (LLMs) to mitigate their hallucinations and enhance their reasoning capability, such as in KG-based retrieval-augmented frameworks. However, current…

Artificial Intelligence · Computer Science 2024-10-22 Bo Ni , Yu Wang , Lu Cheng , Erik Blasch , Tyler Derr

In Knowledge Graphs (KGs), where the schema of the data is usually defined by particular ontologies, reasoning is a necessity to perform a range of tasks, such as retrieval of information, question answering, and the derivation of new…

Artificial Intelligence · Computer Science 2025-02-27 Anastasios Nentidis , Charilaos Akasiadis , Angelos Charalambidis , Alexander Artikis

(Dis)agreement detection aims to identify the authors' attitudes or positions (\textit{{agree, disagree, neutral}}) towards a specific text. It is limited for existing methods merely using textual information for identifying…

Computation and Language · Computer Science 2023-02-09 Yun Luo , Zihan Liu , Stan Z. Li , Yue Zhang

The quality of a knowledge graph directly impacts the quality of downstream applications (e.g. the number of answerable questions using the graph). One ongoing challenge when building a knowledge graph is to ensure completeness and…

Large-scale graph-structured data arising from social networks, databases, knowledge bases, web graphs, etc. is now available for analysis and mining. Graph-mining often involves 'relationship queries', which seek a ranked list of…

Databases · Computer Science 2016-05-03 Puneet Agarwal , Maya Ramanath , Gautam Shroff

Dynamic Text-Attributed Graphs (DyTAGs) have numerous real-world applications, e.g. social, collaboration, citation, communication, and review networks. In these networks, nodes and edges often contain text descriptions, and the graph…

Machine Learning · Computer Science 2025-02-18 Amit Roy , Ning Yan , Masood Mortazavi

RDF knowledge graphs (KG) are powerful data structures to represent factual statements created from heterogeneous data sources. KG creation is laborious and demands data management techniques to be executed efficiently. This paper tackles…

Artificial Intelligence · Computer Science 2022-10-27 Enrique Iglesias , Samaneh Jozashoori , Maria-Esther Vidal

Knowledge Graph Completion (KGC) has been recently extended to multiple knowledge graph (KG) structures, initiating new research directions, e.g. static KGC, temporal KGC and few-shot KGC. Previous works often design KGC models closely…

Computation and Language · Computer Science 2022-09-19 Chen Chen , Yufei Wang , Bing Li , Kwok-Yan Lam

In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of existing algorithms) in both the interactive and non-interactive…

Data Structures and Algorithms · Computer Science 2011-07-26 Anupam Gupta , Aaron Roth , Jonathan Ullman

Constructing domain-specific knowledge graphs from unstructured text remains challenging due to heterogeneous entity mentions, long-tail relation distributions, and the absence of standardized schemas. We present LEC-KG, a bidirectional…

Computation and Language · Computer Science 2026-03-02 Yikai Zeng , Yingchao Piao , Changhua Pei , Jianhui Li

Knowledge graphs (KGs) have emerged as a powerful paradigm for structuring and leveraging diverse real-world knowledge, which serve as a fundamental technology for enabling cognitive intelligence systems with advanced understanding and…

Artificial Intelligence · Computer Science 2025-06-16 Guanglin Niu , Bo Li , Yangguang Lin

Personal service robots are deployed to support daily living in domestic environments, particularly for elderly and individuals requiring assistance. These robots must perceive complex and dynamic surroundings, understand tasks, and execute…

Artificial Intelligence · Computer Science 2025-07-15 Margherita Martorana , Francesca Urgese , Mark Adamik , Ilaria Tiddi

Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among…

Computer Vision and Pattern Recognition · Computer Science 2020-04-27 Ferda Ofli , Firoj Alam , Muhammad Imran
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