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A Multi-dimensional Survey on Learning from Imbalanced Data 14th

A Multi-dimensional Survey on Learning from Imbalanced Dat...

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14th international conference on Information, Intelligence, Systems, and Applications, IISA 2023

作者： Akritidis, Leonidas Bozanis, Panayiotis Department of Science and Technology International Hellenic University Thermi 14th km Thessaloniki - N. Moudania Thessaloniki57001 Greece

ISBN: (纸本)9783031674259

the problem of data imbalance in machine learning is related to the uneven distribution of the training examples to the involved classes. Nowadays, a large number of research fields and applications suffer from class imbalance, including Cybersecurity, bioinformatics, Natural Language Processing, management of multimedia content, and so on. Directly training machine/deep learning classifiers with such data has been proved quite problematic, because the generated models become strongly biased towards the majority class. Unable to learn the minority classes effectively, the accuracy of these "imbalanced" models degrades rapidly. Given the importance of the problem, numerous researchers have introduced innovative, state-of-the-art approaches with the aim of addressing it. In this chapter, we present a survey on the most significant advances in the area, by adopting a multi-dimensional categorization approach. Specifically, we classify the relevant works according to: i) the application field they focus on, ii) the methods they introduce to mitigate class imbalance, and iii) the classification models they utilize to evaluate the introduced algorithms. Additionally, we cover the state-of-the-art overviews in a systematic manner and we describe the proposed methods and their achieved results. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Contrastive Learning

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Intelligent Computing Technology 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： De-Shuang Huang Changjun Jiang Vitoantonio Bevilacqua Juan Carlos Figueroa

ISBN: (数字)9783642315886

ISBN: (纸本)9783642315879

this book constitutes the first of 3 volumes of refereed conference proceedings of the 8th international conference on Intelligent Computing, ICIC 2012, held in Huangshan, China, in July 2012. the 242 revised full papers presented were carefully reviewed and selected from 753 submissions. the 84 papers included in this volume are organized in topical sections on evolutionary learning and genetic algorithms, fuzzy theory and models, swarm intelligence and optimization, kernel methods and supporting vector machines, nature inspired computing and optimization, systems biology and computational biology, knowledge discovery and data mining, graph theory and algorithms, machine learning theory and methods, biomedical informatics theory and methods, complex systems theory and methods, pervasive/ubiquitous computing theory and methods, intelligent computing in bioinformatics, intelligent computing in pattern recognition, intelligent computing in image processing, intelligent computing in robotics, intelligent computing in computer vision, intelligent computing in Petri nets/transportation systems, intelligent data fusion and information security, intelligent sensor networks, knowledge representation/reasoning and expert systems, hybrid optimization, and bio-inspired computing and application.

关键词： Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computational Biology/bioinformatics Information Systems Applications (incl. Internet) Computation by Abstract Devices

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Alignment of multiple proteins with an ensemble of hidden Markov models

Alignment of multiple proteins with an ensemble of hidden Ma...

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6th international conference on Machine Learning and Applications, ICMLA 2007

作者： Jai, Song Chunmei, Liu Yinglei, Song Junfeng, Qu Hura, Gurdeep S. College of Electrical Engineering Zhejiang University China Department of Systems and Computer Science Howard University Washington DC 20059 United States Department of Mathematics and Computer Science Univ. of MD Eastern Shore Princess Anne MD United States Dept. of Information Technology Clayton State University Morrow GA United States Department of Mathematics and Computer Science University of Maryland Eastern Shore Princess Anne MD 21853 United States

ISBN: (纸本)0769530699

the alignment of multiple protein sequences is a problem of fundamental importance in bioinformatics. In general, the optimal alignment can be obtained through the optimization of an objective function. However, such an optimization task is often computationally intractible, most of the existing alignment tools thus use statistical or machine learning based methods to avoid direct optimizations. In this paper, we develop a new method that can progressively construct and update a set of alignments by adding sequences in certain order to each of the existing alignments. In particular, each of the existing alignments is modeled with a profile hidden markov model (HMM) and an added sequence is aligned to each of these profile HMMs. the profile HMMs in the set are then updated based on the alignments with leading alignment scores. We performed experiments on BaliBASE benchmarks to compare the performance of this new approach with that of other alignment tools. Our experiments showed that, by introducing an integer parameter that controls the number of profile HMMs in the set, we are able to efficiently explore the alignment space and significantly improve the alignment accuracy on sequences with low similarity. © 2007 IEEE.

关键词： Benchmarking

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Workshop on Conceptual Modeling, Ontologies and Metadata Management for FAIR Data, FAIR 2019, 6th Workshop on Conceptual Modeling in Requirements Engineering and Business Analysis, MREBA 2019, 2nd international Workshop on Empirical methods in Conceptual Modeling, EmpER 2019, 8th international Workshop on Modeling and Management of Big Data, MoBiD19 2019 and 7th international Workshop on Ontologies andConceptual Modelling, OntoCom 2019 held at the 38th international conference on Conceptual Modeling, ER 2019

Workshop on Conceptual Modeling, Ontologies and Metadata Man...

引用

Workshop on Conceptual Modeling, Ontologies and Metadata Management for FAIR Data, FAIR 2019, 6th Workshop on Conceptual Modeling in Requirements Engineering and Business Analysis, MREBA 2019, 2nd international Workshop on Empirical methods in Conceptual Modeling, EmpER 2019, 8th international Workshop on Modeling and Management of Big Data, MoBiD19 2019 and 7th international Workshop on Ontologies andConceptual Modelling, OntoCom 2019 held at the 38th international conference on Conceptual Modeling, ER 2019

ISBN: (纸本)9783030341459

the proceedings contain 24 papers. the special focus in this conference is on Conceptual Modeling, Ontologies and Metadata Management for FAIR Data. the topics include: Facilitating data exploration in industry 4.0;towards understanding aggressive behavior in residential care facilities using process mining;on complex value relations in hive;data capture and analyses from conversational devices in the homes of the elderly;GORO 2.0: Evolving an ontology for goal-oriented requirements engineering;using ontologies for comparing modeling techniques: Experience report;domain ontology for digital marketplaces;exploring semantics in clinical data interoperability;framework for construction and incremental maintenance of high-quality linked data mashup;Aligning DMBOK and open government with the FAIR data principles;a reference architecture for customizable marketplaces;Keyword search algorithm over large RDF datasets;representing the filter bubble: Towards a model to diversification in news;the ontoOO-method: An ontology-driven conceptual modeling approach for evolving the OO-method;stochastic models to improve E-news recommender systems;Exploring reproducibility and FAIR principles in data science using ecological niche modeling as a case study;realizing traceability from the business model to enterprise architecture;creation of multiple conceptual models from user stories – a natural language processing approach;towards a catalog of goals for strategic coopetition;early identification of potential distributed ledger technology business cases using e3value models;exploiting conceptual modeling for searching genomic metadata: a quantitative and qualitative empirical study;What are real JSON schemas like?: An empirical analysis of structural properties.

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Algebraic semantics of ER-models in the context of the calculus of relations. II: Dynamic view 6th

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6th international conference on Relational methods in Computer Science, RelMiCS 2001 and 1st Workshop of COST Action 274 theory and Application of Relational Structures as Knowledge Instruments, TARSKI 2001

作者： Doberkat, Ernst-Erich Omodeo, Eugenio G. Department of Computer Science Universität Dortmund Dortmund Germany Dipartimento di Informatica Università degli Studi di L’Aquila L’Aquila Italy

We provide a detailed analysis of the insertion operations for an ER-model represented in terms of the map calculus. this continues our previous study of compiling an ER model into the abstract setting of what might b... 详细信息

ISBN: (纸本)3540003150

关键词： Calculations

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8th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015

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8th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015

ISBN: (纸本)9783319277066

the proceedings contain 28 papers. the special focus in this conference is on Biomedical Electronics, Bioimaging, bioinformatics models, methods and algorithms. the topics include: Low power programmable gain analog to digital converter for integrated neural implant front end;integrated chip power receiver for wireless bio-implantable devices;research on a novel three-channel self-pressurized wrist pulse acquisition system;a wearable device for high-frequency EEG signal recording;indirect blood pressure evaluation by means of genetic programming;an iterative mesh optimization method for 3d meristem reconstruction at cell level;latent forests to model genetical data for the purpose of multilocus genome-wide association studies;crosstalk network biomarkers of a pathogen-host interaction difference network from innate to adaptive immunity;template scoring methods for protein torsion angle prediction;evaluating the robustness of correlation network analysis in the aging mouse hypothalamus;machine reading for extraction of bacteria and habitat taxonomies;validation study of a wave equation model of soft tissue for a new virtual reality laparoscopy training system;exploring the relationship between characteristics of ventilation performance and response of newborns during resuscitation;a novel application of universal background models for periocular recognition;fusion and comparison of IMU and EMG signals for wearable gesture recognition;integrating user-centred design in the development of a silent speech interface based on permanent magnetic articulography and a method and tool for strategic hospital planning.

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Statistical model based approach to spoken language acquisition

Statistical model based approach to spoken language acquisit...

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6th Pacific Rim international conference on Artificial Intelligence, PRICAI 2000

作者： Iwahashi, Naoto Sony Computer Science Labs Inc. Takanawa Muse Bldg. 3-14-13 Higashi-Gotanda Shinagawa-ku Tokyo 141-0022 Japan

ISBN: (纸本)3540679251

this paper describes an algorithm for spoken language acquisition through natural interface based on the perception of speech and other information conveyed in continuous signal spaces. In this algorithm the grounded language knowledge is represented by statistical model consisting of hidden Markov models and stochastic context-free grammar. the syntactic structure in each spoken utterance is inferred from the conceptual structure extracted from the perceptual information in the learning process. the algorithm is robust against ambiguity and sparseness of learning data because it uses statistical learning methods, such as Bayesian learning. Experimental results show that spoken language is learned robustly from a small amount of learning data. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Hidden Markov models

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6th international conference on Flexible Query Answering Systems, FQAS 2004

6th International Conference on Flexible Query Answering Sys...

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6th international conference on Flexible Query Answering Systems, FQAS 2004

ISBN: (纸本)3540221603

the proceedings contain 38 papers. the special focus in this conference is on Development of Query Systems that are more Expressive, Informative, Cooperative, Productive, and Intuitive to Use. the topics include: Meme media architecture for the reediting and redistribution of web resources;a flexible access control model for web services;active xml and active query answers;towards flexible querying of xml imprecise data in a dataware house opened on the web;fuzzy closeness relation as a basis for weakening fuzzy relational queries;querying data sources in a superpeer data management system;logic-based integration of query answering and knowledge discovery;discovering representative models in large time series databases;a new approach for mining association rules in data warehouses;query rewriting in itemset mining;query answering based on collaboration and chase;construction of query concepts in a document space based on data mining techniques;towards formal ontologies requirements with multiple perspectives;a unifying framework for flexible information access in taxonomy-based sources;interactive schema integration with sphinx;on querying ontologies and databases;on the discovery of the semantic context of queries by game-playing;information retrieval system for medical narrative reports;combining knowledge-based methods to refine and expand queries in medicine;a flexible data processing technique for a tele-assistance system of elderly people;semantic web services discovery regarded as a constraint satisfaction problem;similarity-based query caching and access to multigranular temporal objects.

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Multimodal Corpora - From models of Natural Interaction to Systems and Applications

Multimodal Corpora - From Models of Natural Interaction to S...

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international Workshop on Multimodal Corpora: From models of Natural Interaction to Systems and Applications, Held in Conjunction with the 6th international conference for Language Resources and Evaluation, LREC 2008

ISBN: (纸本)3642047920

the proceedings contain 13 papers. the topics discussed include: the SmartWeb corpora: multimodal access to the web in natural environments;promoting free dialog video corpora: the IFADV corpus example;creating and exploiting multimodal annotated corpora: the ToMA project;multi-track annotation of child language and gestures;gesture, gaze and persuasive strategies in political discourse;unsupervised clustering in multimodal multiparty meeting analysis;multimodal corpora annotation: validation methods to assess coding scheme reliability;on the contextual analysis of agreement scores;creating standardized video recordings of multimodal interactions across cultures;multimodal intercultural information and communication technology - a framework for designing and evaluating multimodal intercultural communicators;accessing a large multimodal corpus using an automatic content linking device;and an exchange format for multimodal annotations.

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Trigger words detection by integrating attention mechanism into Bi-LSTM neural network—A case study in PubMED-wide trigger words detection for pancreatic cancer 17th

Trigger words detection by integrating attention mechanism i...

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17th China National conference on Computational Linguistics, CCL 2018 and 6th international Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018

作者： Zhou, Kaiyin Yao, Xinzhi Wang, Shuguang Kim, Jin-Dong Cohen, Kevin Bretonnel Chen, Ruiying Wang, Yuxing Xia, Jingbo College of Informatics Huazhong Agricultural University Wuhan China Hubei Key Laboratory of Agricultural Bioinformatics Wuhan China Tokyo Japan School of Medicine University of Colorado Denver Anschutz Medical Campus Aurora United States

ISBN: (纸本)9783030017156

A Bi-LSTM based encode/decode mechanism for named entity recognition was studied in this research. In the proposed mechanism, Bi-LSTM was used for encoding, an Attention method was used in the intermediate layers, and an unidirectional LSTM was used as decoder layer. By using element wise product to modify the conventional decoder layers, the proposed model achieved better F-score, compared with other three baseline LSTM-based models. For the purpose of algorithm application, a case study of causal gene discovery in terms of disease pathway enrichment was designed. In addition, the causal gene discovery rate of our proposed method was compared with another baseline methods. the result showed that trigger genes detection effectively increase the performance of a text mining system for causal gene discovery. © Springer Nature Switzerland AG 2018.

关键词： Decoding

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