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Hierarchical comments-based clustering
2011
Proceedings of the 2011 ACM Symposium on Applied Computing - SAC '11
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In this paper, we explore a comments-driven clustering framework for organizing Web resources according to this user-based perspective. ...
Concretely, we propose a hierarchical comment clustering approach that relies on two key features: (i) comment term normalization and key term extraction for distilling noisy comments for effective clustering ...
. • We introduce a comments distillation framework for extracting core comment features via comment term normalization and KL-divergence-based key term extraction for enabling effective clustering. • We ...
doi:10.1145/1982185.1982434
dblp:conf/sac/HsuCK11
fatcat:ux7bu4zbxja3pcyvtuw73hu44u
Eco-innovation in process engineering: Contradictions, inventive principles and methods
2019
Thermal Science and Engineering Progress
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However, environmental impact, followed by energy and material consumption still remain the main negative implications of the technological progress in process engineering. ...
The study conceptualizes a correlation matrix between the eco-requirements for prediction of typical eco-contradictions on example of processes involving solids handling. ...
The authors thank the European Commission for supporting their ...
doi:10.1016/j.tsep.2018.10.012
fatcat:px63nj2fqbhofdqqgshbcaw3eu
Rapid Realist Review of School-Based Physical Activity Interventions in 7- to 11-Year-Old Children
2021
Children
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The school level led to most context-mechanism-outcome configurations related to school leadership and policy, workforce structure, program characteristics, and school environment. ...
The aim of this rapid realist review was to determine, what physical activity interventions in school settings for children aged 7- to 11-years-old works, for whom, and in what circumstances. ...
Further, the conceptual framework could be applied within the active school framework, especially in relation to policy and vision, social and physical environment, and seven opportunities for physical ...
doi:10.3390/children8010052
pmid:33467132
pmcid:PMC7830730
fatcat:iepqrpzcf5e5ndu6dk5uht4aoa
A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods
[article]
2023
arXiv
pre-print
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Multi-task learning (MTL) has become increasingly popular in natural language processing (NLP) because it improves the performance of related tasks by exploiting their commonalities and differences. ...
In this survey, we review recent advances of multi-task learning methods in NLP, with the aim of summarizing them into two general multi-task training methods based on their task relatedness: (i) joint ...
Wenhao Yu is also supported in part by Bloomberg Data Science Ph.D Fellowship. We would also like to thank Libo Qin from Harbin Institute of Technology for his valuable suggestions to this paper. ...
arXiv:2204.03508v2
fatcat:ymavui5wf5aqld4ijnfmoksuoq
Semi-supervised News Discourse Profiling with Contrastive Learning
[article]
2023
arXiv
pre-print
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In this paper, we present a novel approach, denoted as Intra-document Contrastive Learning with Distillation (ICLD), for addressing the news discourse profiling task, capitalizing on its unique structural ...
News Discourse Profiling seeks to scrutinize the event-related role of each sentence in a news article and has been proven useful across various downstream applications. ...
Acknowledgements We thank the anonymous reviewers for their valuable feedback and input. ...
arXiv:2309.11692v1
fatcat:7sbfconkifa55kvnlvf72e2ohq
A Comprehensive Survey on Automatic Knowledge Graph Construction
[article]
2023
arXiv
pre-print
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Thus, there is a demand for a systematic review of paradigms to organize knowledge structures beyond data-level mentions. ...
The processes of knowledge acquisition are reviewed in detail, including obtaining entities with fine-grained types and their conceptual linkages to knowledge graphs; resolving coreferences; and extracting ...
in HACE big data environments, including noisy, document-level data and low-resource data. ...
arXiv:2302.05019v1
fatcat:7in54wjwyzhfnkx755izrkzr3y
Services, Frameworks, and Paradigms for Distributed Multimedia Applications
1996
IEEE Multimedia
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Known development environments for distributed applications are obvious candidates for such encompassing frameworks. ...
As a way to alleviate this problem, we make the case for an encompassing framework in which all services would be offered under a unifying paradigm. ...
Such microworlds (sometimes called environments or toolkits by the vendors) are rather self-contained and platform-dependent. ...
doi:10.1109/mmul.1996.556539
fatcat:rprbbw4rbrdnhpo35llmur2swy
A conceptual framework for teaching computational thinking in personalized OERs
2020
Smart Learning Environments
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This study hence proposes a conceptual framework that seeks to consider how to promotelearners' personalized learning experiences and enhance their CT skills in OERs. ...
Through extensive reviewing of literature, this study provides several implications for further research. ...
This framework envisions the low-level data fusion that combines all raw data, which has similar epistemological features. ...
doi:10.1186/s40561-019-0108-z
fatcat:dykgmidohzfifnkcvmpypzxjyy
ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
[article]
2021
arXiv
pre-print
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To reduce the computation overhead and carbon emission, we propose an online distillation framework for ERNIE 3.0 Titan, where the teacher model will teach students and train itself simultaneously. ...
A unified framework named ERNIE 3.0 was recently proposed for pre-training large-scale knowledge enhanced models and trained a model with 10 billion parameters. ...
Relation Extraction. The relation extraction task is to identify the relationship between different entities like persons and organizations. ...
arXiv:2112.12731v1
fatcat:hact2hlojrdydhxcnzozmb7kee
Pre-training Methods in Information Retrieval
[article]
2022
arXiv
pre-print
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In addition, we also introduce PTMs specifically designed for IR, and summarize available datasets as well as benchmark leaderboards. ...
The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to the user's information need. ...
Acknowledgements
References
Pre-training Methods in Information Retrieval Acknowledgements ...
arXiv:2111.13853v3
fatcat:pilemnpphrgv5ksaktvctqdi4y
D2.1 – Distillation of existing resources for exposure assessment of NFs/NEPs
2021
Zenodo
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This document describes the resources selected based on the criteria presented in Milestone 1 and the results of the assessment process for the distillation process. ...
to parameterise and run the model for a custom scenario, unless use of the tool is self-explanatory enough to not need specific documentation. ...
Suggestions will be provided in the Task 2.2 for the implementation and use of quality criteria for the newly generated and existing datasets. ...
doi:10.5281/zenodo.10822413
fatcat:hwozwc3ywjegfinejn5ia3ejee
A Survey of Information Extraction Based on Deep Learning
2022
Applied Sciences
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Deep learning-based entity relation extraction techniques have gradually surpassed traditional feature- and kernel-function-based methods in terms of the depth of feature extraction and model accuracy. ...
At the level of IE tasks, it is expounded from entity relationship extraction, event extraction, and multi-modal information extraction three aspects, and creates a comparative analysis of various extraction ...
The experimental results show that UIE has achieved very competitive performance in both supervised and low-resource environments, which verifies its versatility, effectiveness, and portability [80] . ...
doi:10.3390/app12199691
fatcat:jmoum63qhvfstcsufkyf3hqpe4
Findings of Case-Study Analysis: System-Level Biomimicry in Built-Environment Design
2019
Biomimetics
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in the built environment. ...
This paper explores insights from a selection of system-level case studies in the built environment, using meta-analysis to investigate common challenges and priorities from these projects to support knowledge-sharing ...
The first author gratefully acknowledges the Australia Awards-Endeavour Scholarships and the Australian Government Research Training Program for supporting the broader research project. ...
doi:10.3390/biomimetics4040073
pmid:31683928
pmcid:PMC6963226
fatcat:2rrambovjjf3jhthm2e4qmupqi
Bridging National Policies with Practical Rural Construction and Development: Research on a Decision Support System Based on Multi-Source Big Data and Integrated Algorithms
2023
Sustainability
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and the environment. ...
with less distinct characteristics—through an analysis of the Chinese government's policy framework for rural construction. ...
This confirms the general consensus that many townships still heavily rely on their own resources for development and lack effective systems for managing external resources and enhancing self-service capabilities ...
doi:10.3390/su152316152
fatcat:d5gt2gkzy5fohpaxr5xdbbojde
A Survey of Multi-Task Deep Reinforcement Learning
2020
Electronics
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This is primarily due to the limited applicability of deep reinforcement learning algorithms to many scenarios across related tasks from the same environment. ...
Undoubtedly, the inception of deep reinforcement learning has played a vital role in optimizing the performance of reinforcement learning-based intelligent agents with model-free based approaches. ...
for the limited resources of a single learning system (environment). ...
doi:10.3390/electronics9091363
fatcat:cohk2pukzbgbfizarqweuw45oe
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