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Meta-level Information Extraction [chapter]

Peter Kluegl, Martin Atzmueller, Frank Puppe
2009 Lecture Notes in Computer Science  
This paper presents a novel approach for meta-level information extraction (IE).  ...  The common IE process model is extended by utilizing transfer knowledge and meta-features that are created according to already extracted information.  ...  for the meta-level information extraction.  ... 
doi:10.1007/978-3-642-04617-9_30 fatcat:4jwg3biz4nfmdasx7u4otatr5i

A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning [article]

Huimin Peng
2021 arXiv   pre-print
Self-supervised learning utilizes self-supervision from original data and extracts higher-level generalizable features through unsupervised pre-training or optimization of contrastive loss objectives.  ...  Self-supervised learning guided by meta-learner and general meta-learning algorithms under self-supervision are both examples of possible combinations.  ...  Meta-learner in meta-learning performs higher-level optimization to learn how to generalize base learner, and pre-training in self-supervised learning extracts high-level generalizable features that can  ... 
arXiv:2103.00845v2 fatcat:soq6tfl56vgshebtnot57e4qwe

MetaPAD: Meta Pattern Discovery from Massive Text Corpora [article]

Meng Jiang, Jingbo Shang, Taylor Cassidy, Xiang Ren, Lance M. Kaplan, Timothy P. Hanratty, Jiawei Han
2017 arXiv   pre-print
from multiple facets---their types, contexts, and extractions; and (3) it examines type distributions of entities in the instances extracted by each group of patterns, and looks for appropriate type levels  ...  In this study, we propose a novel typed textual pattern structure, called meta pattern, which is extended to a frequent, informative, and precise subsequence pattern in certain context.  ...  , and extracted instances (see Sec. 4.2). ird, MetaPAD examines the type distributions of entities in the extractions from every meta pa ern group, and looks for the most appropriate type level that the  ... 
arXiv:1703.04213v2 fatcat:tr3lxohrz5fc3nw6vi326kor4i

Disagreements in meta-analyses using outcomes measured on continuous or rating scales: observer agreement study

B. Tendal, J. P T Higgins, P. Juni, A. Hrobjartsson, S. Trelle, E. Nuesch, S. Wandel, A. W Jorgensen, K. Gesser, S. Ilsoe-Kristensen, P. C Gotzsche
2009 BMJ (Clinical Research Edition)  
The experts agreed somewhat more than the PhD students at trial level (61% v 46%), but not at meta-analysis level.  ...  Results The agreement was 53% at trial level and 31% at meta-analysis level. Including all pairs, the median disagreement was SMD=0.22 (interquartile range 0.07-0.61).  ...  The level of information in the review protocols is given in table 1. None of the review protocols contained information on which scales should be preferred.  ... 
doi:10.1136/bmj.b3128 pmid:19679616 pmcid:PMC2726927 fatcat:p3brjdsmyjgsxje3gqt5b2ub5y

Meta-association rules for mining interesting associations in multiple datasets

M.D. Ruiz, J. Gómez-Romero, M. Molina-Solana, J.R. Campaña, M.J. Martin-Bautista
2016 Applied Soft Computing  
Meta-association rules are a new tool that convey new information from the patterns extracted from multiple datasets and give a "summarized" representation about most frequent patterns.  ...  Association rules have been widely used in many application areas to extract new and useful information expressed in a comprehensive way for decision makers from raw data.  ...  The objective of meta-association rules is then to extract globally-valid additional knowledge based on previously extracted information, in the form of association rules, that have similar structure and  ... 
doi:10.1016/j.asoc.2016.08.014 fatcat:qqyu352ztnhw3h5jii5wgs44na

Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks [article]

Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu
2019 arXiv   pre-print
Through modelling the rich object properties and relations in recommender system as a heterogeneous information network, NeuACF first extracts different aspect-level similarity matrices of users and items  ...  respectively through different meta-paths, and then feeds an elaborately designed deep neural network with these matrices to learn aspect-level latent factors.  ...  Meta-paths [9] , relation sequences connecting objects, are then employed to extract aspect-level features of users and items.  ... 
arXiv:1909.06627v1 fatcat:wqzcifktbfaqdg3cy7dwfnzxy4

Extracting Pathway-Level Signatures from Proteogenomic data in Breast Cancer Using Independent Component Analysis

Wenke Liu, Samuel H Payne, Sisi Ma, David Fenyö
2019 Molecular & Cellular Proteomics  
We show that as an unsupervised feature extraction method, ICA was able to construct signatures with known biological relevance on both transcriptome and proteome levels.  ...  Our results demonstrate that the application of ICA to proteogenomics data could lead to pathway-level knowledge discovery.  ...  Our analysis has demonstrated that ICA was able to blindly extract information in the form of weighted gene combinations, which may be biologically meaningful at pathway level.  ... 
doi:10.1074/mcp.tir119.001442 pmid:31213479 pmcid:PMC6692784 fatcat:hwj32glyinekrdcql4bswbgju4

Pathway-Level Integration of Proteogenomic data in Breast Cancer Using Independent Component Analysis [article]

Wenke Liu, Sisi Ma, David Fenyo
2017 bioRxiv   pre-print
We show that as an unsupervised feature extraction method, ICA was able to construct signatures with known biological relevance on both transcriptome and proteome levels.  ...  In this study, we apply independent component analysis (ICA) to human breast cancer proteogenomics data to retrieve mechanistic information.  ...  Our analysis has demonstrated that ICA was able to blindly extract biologically meaningful information at pathway level.  ... 
doi:10.1101/175687 fatcat:vd4i24d52jh4djibfnjxzs7q2a

Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

Elizabeth Korevaar, Amalia Karahalios, Andrew B. Forbes, Simon L. Turner, Steve McDonald, Monica Taljaard, Jeremy M. Grimshaw, Allen C. Cheng, Lisa Bero, Joanne E. McKenzie
2020 F1000Research  
; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies.  ...  From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies  ...  level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome  ... 
doi:10.12688/f1000research.22226.3 fatcat:m3v5j5iwlbdwpctoxl3jfbybde

Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

Elizabeth Korevaar, Amalia Karahalios, Andrew B. Forbes, Simon L. Turner, Steve McDonald, Monica Taljaard, Jeremy M. Grimshaw, Allen C. Cheng, Lisa Bero, Joanne E. McKenzie
2020 F1000Research  
; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies.  ...  From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies  ...  level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome  ... 
doi:10.12688/f1000research.22226.2 fatcat:ob3juotombbgtgnioumd3qxiri

Enhancing Search: Events and Their Discourse Context [chapter]

Sophia Ananiadou, Paul Thompson, Raheel Nawaz
2013 Lecture Notes in Computer Science  
We describe our annotation scheme used to capture this information at the event level, report on the corpora that have so far been enriched according to this scheme and provide details of our experiments  ...  to recognise this information automatically.  ...  The work described in this paper has been funded by the Meta-Net4U project (ICT PSP Programme, Grant Agreement: No 270893) and the JISCfunded Integrated Social History Environment for Research (ISHER)-  ... 
doi:10.1007/978-3-642-37256-8_27 fatcat:pf7kv5jmsjfrtgaqlt3wymxdgu

Attention-aware heterogeneous graph neural network

Jintao Zhang, Quan Xu
2021 Big Data Mining and Analytics  
Finally, the semantic-level neural network is proposed to extract the feature interaction relationships on different meta-paths and learn the final embedding of nodes.  ...  Specifically, we first use node-level attention to aggregate and update the embedding representation of nodes, and then concatenate the embedding representation of the nodes on different meta-paths.  ...  The main contributions of this paper are summarized as follows. • We propose a semantic-level neural network to extract feature interaction information hidden between node embeddings on different meta-paths  ... 
doi:10.26599/bdma.2021.9020008 fatcat:ceew7ktk7vhy7gxiesgouomiaq

Comparison of methods of extracting information for meta-analysis of observational studies in nutritional epidemiology

Jong-Myon Bae
2016 Epidemiology and Health  
CONCLUSIONS: The ICM is advantageous over the HLM owing to its higher statistical accuracy in extracting information for QSR on nutritional epidemiology.  ...  The ES and SES were estimated by performing a meta-analysis using the fixedeffect model.  ...  levels, and the meta-analysis was performed by extracting the ES of the highest intake group and 95% confidence interval (CI) with respect to the lowest intake group.  ... 
doi:10.4178/epih.e2016003 fatcat:xrlvl5dplfczlnaidr6fqd35d4

Comparison of methods of extracting information for meta-analysis of observational studies in nutritional epidemiology

Jong-Myon Bae
2016 Epidemiology and Health  
CONCLUSIONS: The ICM is advantageous over the HLM owing to its higher statistical accuracy in extracting information for QSR on nutritional epidemiology.  ...  The ES and SES were estimated by performing a meta-analysis using the fixedeffect model.  ...  levels, and the meta-analysis was performed by extracting the ES of the highest intake group and 95% confidence interval (CI) with respect to the lowest intake group.  ... 
doi:10.4178/epih/e2016003 pmid:26797219 pmcid:PMC4751349 fatcat:tdb73lkufjhdlkq2lb5wa4mnxu

Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks

Xiaotian Han, Chuan Shi, Senzhang Wang, Philip S. Yu, Li Song
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
Through modelling rich objects and relations in recommender system as a heterogeneous information network, NeuACF first extracts different aspect-level similarity matrices of users and items through different  ...  meta-paths and then feeds an elaborately designed deep neural network with these matrices to learn aspect-level latent factors.  ...  Given a specific meta-path, there are several alternatives to extract the aspect-level features: commuting matrix or similarity matrix.  ... 
doi:10.24963/ijcai.2018/471 dblp:conf/ijcai/HanSWYS18 fatcat:3y5bgcnbcbh25jk75v6vd2kkaq
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