Zobrazeno 1 - 10
of 356
pro vyhledávání: '"Yuan, Xiaojie"'
Heterogeneous graphs have attracted a lot of research interests recently due to the success for representing complex real-world systems. However, existing methods have two pain points in embedding them into low-dimensional spaces: the mixing of struc
Externí odkaz:
http://arxiv.org/abs/2406.10367
Graph Transformers (GTs) have made remarkable achievements in graph-level tasks. However, most existing works regard graph structures as a form of guidance or bias for enhancing node representations, which focuses on node-central perspectives and lac
Externí odkaz:
http://arxiv.org/abs/2404.11869
Next Point-of-Interests (POIs) recommendation task aims to provide a dynamic ranking of POIs based on users' current check-in trajectories. The recommendation performance of this task is contingent upon a comprehensive understanding of users' persona
Externí odkaz:
http://arxiv.org/abs/2403.12100
Enterprises and organizations are faced with potential threats from insider employees that may lead to serious consequences. Previous studies on insider threat detection (ITD) mainly focus on detecting abnormal users or abnormal time periods (e.g., a
Externí odkaz:
http://arxiv.org/abs/2403.09209
Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments. Existing methods make great efforts to align the whole image to corresponding aspects. However, different regions of the
Externí odkaz:
http://arxiv.org/abs/2306.01004
ICD coding is designed to assign the disease codes to electronic health records (EHRs) upon discharge, which is crucial for billing and clinical statistics. In an attempt to improve the effectiveness and efficiency of manual coding, many methods have
Externí odkaz:
http://arxiv.org/abs/2305.18576
Entity Alignment (EA) aims to find the equivalent entities between two Knowledge Graphs (KGs). Existing methods usually encode the triples of entities as embeddings and learn to align the embeddings, which prevents the direct interaction between the
Externí odkaz:
http://arxiv.org/abs/2305.11501
Publikováno v:
WWW '23: Proceedings of the ACM Web Conference 2023 (523-532)
Temporal link prediction, aiming to predict future edges between paired nodes in a dynamic graph, is of vital importance in diverse applications. However, existing methods are mainly built upon uniform Euclidean space, which has been found to be conf
Externí odkaz:
http://arxiv.org/abs/2304.07302
Publikováno v:
The Semantic Web-ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings (pp. 179-195)
Temporal heterogeneous information network (temporal HIN) embedding, aiming to represent various types of nodes of different timestamps into low dimensional spaces while preserving structural and semantic information, is of vital importance in divers
Externí odkaz:
http://arxiv.org/abs/2304.06970
Open Information Extraction (OIE) methods extract a large number of OIE triples (noun phrase, relation phrase, noun phrase) from text, which compose large Open Knowledge Bases (OKBs). However, noun phrases (NPs) and relation phrases (RPs) in OKBs are
Externí odkaz:
http://arxiv.org/abs/2212.01207