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Published in 2019 at "Knowledge and Information Systems"
DOI: 10.1007/s10115-019-01401-x
Abstract: In order to facilitate the accesses of general users to knowledge graphs, an increasing effort is being exerted to construct graph-structured queries of given natural language questions. At the core of the construction is to…
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Keywords:
graph embedding;
knowledge;
query construction;
knowledge graph ... See more keywords
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Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.01.118
Abstract: Abstract Point-of-interest (POI) recommendation is an important technique widely used in self-driving services. While POI recommendation aims to recommend unvisited POIs to self-driving users, users always expect their intended items can be suggested together with…
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Keywords:
recommendation;
graph embedding;
poi recommendation;
fine grained ... See more keywords
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Published in 2022 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.12.079
Abstract: Capturing the composition patterns of relations is a vital task in knowledge graph completion. It also serves as a fundamental step towards multi-hop reasoning over learned knowledge. Previously, rotation-based translational methods, e.g., RotatE, have been…
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Keywords:
knowledge;
non commutative;
graph embedding;
knowledge graph ... See more keywords
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Published in 2023 at "Advances in Archaeological Practice"
DOI: 10.1017/aap.2023.1
Abstract: ABSTRACT The transnational networks of the illicit and illegal antiquities trade are hard to perceive. We suggest representing the trade as a knowledge graph with multiple kinds of relationships that can be transformed by a…
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Keywords:
knowledge graph;
knowledge;
graph;
model ... See more keywords
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Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa881
Abstract: Abstract Motivation The complete characterization of enzymatic activities between molecules remains incomplete, hindering biological engineering and limiting biological discovery. We develop in this work a technique, enzymatic link prediction (ELP), for predicting the likelihood of…
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Keywords:
graph embedding;
enzymatic link;
elp;
link prediction ... See more keywords
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Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac148
Abstract: MOTIVATION Identifying the target genes of transcription factors (TFs) is of great significance for biomedical researches. However, using biological experiments to identify TF-target gene interactions is still time consuming, expensive and limited to small scale.…
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Keywords:
heterogeneous graph;
target gene;
model;
graph embedding ... See more keywords
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Published in 2017 at "IEEE Access"
DOI: 10.1109/access.2017.2706525
Abstract: Solving problems with small sample sizes during training for feature extraction and the dimensionality reduction method will not produce high face recognition accuracy using the locality graph embedding (LGE) algorithm. Thus, we introduced a new…
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Keywords:
maximum margin;
graph embedding;
locality graph;
margin criterion ... See more keywords
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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2797876
Abstract: Knowledge graph embedding aims to construct a low-dimensional and continuous space, which is able to describe the semantics of high-dimensional and sparse knowledge graphs. Among existing solutions, translation models have drawn much attention lately, which…
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Keywords:
translation models;
graph embedding;
knowledge;
knowledge graph ... See more keywords
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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2022.3227714
Abstract: The knowledge graph embedding model aims to use low-dimensional real-valued vectors to represent the entities and relations in the triples, where operations such as link prediction and triple classification can be performed based on these…
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Keywords:
semantics;
knowledge graph;
framework;
embedding triples ... See more keywords
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Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.3036583
Abstract: Recently, the surge in popularity of the Internet of Things (IoT), mobile devices, social media, etc., has opened up a large source for graph data. Graph embedding has been proved extremely useful to learn low-dimensional…
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Keywords:
adversarial privacy;
inference;
privacy preserving;
graph ... See more keywords
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Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3099805
Abstract: Recent studies in cross-domain classification have shown that discriminant information of both source and target domains is very important. In this article, we propose a new domain adaptation (DA) method for hyperspectral image (HSI) classification,…
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Keywords:
alignment;
domain;
classification;
distribution alignment ... See more keywords