检索结果-内蒙古大学图书馆

rule-based algorithms for Automatic Pronunciation of Portuguese Verbal Inflections 11

11th International Conference on Computational Processing of Portuguese (PROPOR)

作者： Marquiafavel, Vanessa Shulby, Christopher Veiga, Arlindo Proenca, Jorge Candeias, Sara Perdigao, Fernando Univ Estadual Paulista IBILCE Sj Do Rio Preto Brazil Univ Sao Paulo ICMC Sao Carlos Brazil Inst Telecomunicacoes Pole Coimbra Coimbra Portugal Univ Coimbra DEEC Coimbra Portugal

ISBN: (纸本)9783319097619;9783319097602

The correct automatic pronunciation of words is a nontrivial problem, even for inflexions of Portuguese verbs, and has not been systematically solved yet, if verbal irregularity is taken into account. The purpose of this work is to enhance a grapheme-to-phoneme system with a verb pronunciation system for both varieties of Portuguese, Brazilian (BP) and European (EP), given only its infinitive form. The most common verbs for BP and EP (1000 and 2600 respectively) constituted our database to test the pronunciation system. A detailed and systematic analysis of regular and non-regular pronunciation forms of the inflected verbs was performed, and an index of irregularity for verb pronunciation is proposed. A rule-based algorithm to pronounce all inflexions according to verb paradigms is also described. The defined paradigms are, with a high level of certainty, representative of all the verbs for Portuguese.

关键词： Brazilian Portuguese European Portuguese Verbs Pronunciation rule-based algorithms

来源：评论

学校读者我要写书评

暂无评论

Methods for identifying health status from routinely collected health data: An overview

引用

INTEGRATIVE MEDICINE RESEARCH 2025年第1期14卷 101100页

作者： Liu, Mei Deng, Ke Wang, Mingqi He, Qiao Xu, Jiayue Li, Guowei Zou, Kang Sun, Xin Wang, Wen Sichuan Univ West China Hosp Inst Integrated Tradit Chinese & Western Med Chinese Evidence Based Med & Cochrane China Ctr Chengdu Peoples R China Hosp Chengdu Univ Tradit Chinese Med Chengdu Peoples R China NMPA Key Lab Real World Data Res & Evaluat Hainan Chengdu Peoples R China Sichuan Ctr Technol Innovat Real World Data Chengdu Peoples R China McMaster Univ Dept Hlth Res Methods Evidence & Impact Hamilton ON Canada Guangdong Second Prov Gen Hosp Ctr Clin Epidemiol & Methodol Guangzhou Guangdong Peoples R China St Josephs Healthcare Hamilton Res Inst Biostat Unit Hamilton ON Canada Sichuan Univ West China Sch Publ Hlth Chengdu Peoples R China Sichuan Univ West China Hosp 4 Chengdu Peoples R China

Routinely collected health data (RCD) are currently accelerating publications that evaluate the effectiveness and safety of medicines and medical devices. One of the fundamental steps in using these data is developing algorithms to identify health status that can be used for observational studies. However, the process and methodologies for identifying health status from RCD remain insufficiently understood. While most current methods rely on International Classification of Diseases (ICD) codes, they may not be universally applicable. Although machine learning methods hold promise for more accurately identifying the health status, they remain underutilized in RCD studies. To address these significant methodological gaps, we outline key steps and methodological considerations for identifying health statuses in observational studies using RCD. This review has the potential to boost the credibility of findings from observational studies that use RCD.

关键词： Routinely collected health data Health status Machine learning algorithms rule-based algorithms

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence-based System for Retinal Disease Diagnosis

引用

algorithms 2024年第7期17卷 315页

作者： Orlova, Ekaterina V. Ufa Univ Sci & Technol Dept Econ & Management Ufa 450076 Russia

The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological methods can significantly improve and speed up the analysis of results and diagnostics. We propose an approach to designing an artificial intelligent diagnosis system (AI diagnosis system) which includes an electrophysiological complex to collect objective information and an intelligent decision support system to justify the diagnosis. The task of diagnosing retinal diseases based on a set of heterogeneous data is considered as a multi-class classification on unbalanced data. The decision support system includes two classifiers-one classifier is based on a fuzzy model and a fuzzy rule base (RB-classifier) and one uses the stochastic gradient boosting algorithm (SGB-classifier). The efficiency of algorithms in a multi-class classification on unbalanced data is assessed based on two indicators-MAUC (multi-class area under curve) and MMCC (multi-class Matthews correlation coefficient). Combining two algorithms in a decision support system provides more accurate and reliable pathology identification. The accuracy of diagnostics using the proposed AI diagnosis system is 5-8% higher than the accuracy of a system using only diagnostics based on electrophysical indicators. The AI diagnosis system differs from other systems of this class in that it is based on the processing of objective electrophysiological data and socio-demographic data about patients, as well as subjective information from the anamnesis, which ensures increased efficiency of medical decision-making. The system is tested using actual data about retinal diseases from the Russian Institute of Eye Diseases and its high efficiency is proven. Simulation experiments conducted in various scenario conditions with different combinations of factors ensured the identific

关键词： artificial intelligence decision support system fuzzy model rule-based algorithms stochastic gradient boosting algorithm retinal disease diagnosis healthcare

来源：评论

学校读者我要写书评

暂无评论

Multiscale fully convolutional network-based approach for multilingual character segmentation

引用

IET COMPUTER VISION 2021年第6期15卷 449-461页

作者： Yu, Chao Liu, Jin Li, Yunhui Shanghai Maritime Univ Shanghai Peoples R China

Character segmentation is a challenging task for optical character recognition systems. Traditional methods usually utilize rule-based algorithms but most of them are not applicable in modern intelligent recognition applications that require high accuracy. It is especially the case for text containing Eastern Asian language characters with complex pictograph structures, such as Chinese. To alleviate this problem, this study proposes an encoder-decoder structure-based multiscale fully convolutional network (MSFCN) model for optical character segmentation. Comparing with other methods, MSFCN can not only effectively extract semantic details from images but also exploit boundary information of intervals between characters, thereby distinguishing characters from a background in pixel level. Extensive experiments have been conducted on two benchmark data sets of ICDAR2013 and MLCS. Obtained results prove that MSFCN achieves state-of-the-art segmentation performance and indicated its practical application value.

关键词： MSFCN image segmentation Eastern Asian language characters optical character segmentation convolutional network model image classification optical character recognition systems complex pictograph structures practical application value state-of-the-art segmentation performance multilingual character segmentation optical character recognition rule-based algorithms modern intelligent recognition applications encoder-decoder structure-based fully convolutional network-based approach

来源：评论

学校读者我要写书评

暂无评论

ACRIPPER: A New Associative Classification based on RIPPER Algorithm

引用

JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT 2021年第1期20卷

作者： Abu-Arqoub, Mohammed Hadi, Wael Ishtaiwi, Abdelraouf Univ Petra Dept Comp Sci Amman Jordan Univ Petra Dept Informat Secur Amman Jordan

Associative Classification (AC) classifiers are of substantial interest due to their ability to be utilised for mining vast sets of rules. However, researchers over the decades have shown that a large number of these mined rules are trivial, irrelevant, redundant, and sometimes harmful, as they can cause decision-making bias. Accordingly, in our paper, we address these challenges and propose a new novel AC approach based on the RIPPER algorithm, which we refer to as ACRIPPER. Our new approach combines the strength of the RIPPER algorithm with the classical AC method, in order to achieve: (1) a reduction in the number of rules being mined, especially those rules that are largely insignificant;(2) a high level of integration among the confidence and support of the rules on one hand and the class imbalance level in the prediction phase on the other hand. Our experimental results, using 20 different well-known datasets, reveal that the proposed ACRIPPER significantly outperforms the well-known rule-based algorithms RIPPER and J48. Moreover, ACRIPPER significantly outperforms the current AC-based algorithms CBA, CMAR, ECBA, FACA, and ACPRISM. Finally, ACRIPPER is found to achieve the best average and ranking on the accuracy measure.

关键词： Associative classification classification rule-based algorithms data mining

来源：评论

学校读者我要写书评

暂无评论

SOAR: Simultaneous Or-of-And rules for classification of positive and negative classes

引用

STAT 2023年第1期12卷

作者： Khusainova, Elena Dodwell, Emily Mitra, Ritwik AT&T Data Sci & Res CDO New York NY 10007 USA AT&T 33 Thomas St New York NY 10007 USA

Algorithmic decision making has proliferated and now impacts our daily lives in both mundane and consequential ways. Machine learning practitioners use a myriad of algorithms for predictive models in applications as diverse as movie recommendations, medical diagnoses, and parole recommendations without delving into the reasons driving specific predictive decisions. The algorithms in such applications are often chosen for their superior performance among a pool of competing algorithms;however, popular choices such as random forest and deep neural networks fail to provide an interpretable understanding of the model's predictions. In recent years, rule-based algorithms have provided a valuable alternative to address this issue. Previous work established an or-of-and (disjunctive normal form) based classification technique that allows for classification rule mining of a single class in a binary classification. In this work, we extend this idea to provide classification rules for both classes simultaneously. That is, we provide a distinct set of rules for each of the positive and negative classes. We also present a novel and complete taxonomy of classifications that clearly capture and quantify the inherent ambiguity of noisy binary classifications in the real world. We show that this approach leads to a more granular formulation of the likelihood model and a simulated annealing-based optimization achieves classification performance competitive with comparable techniques. We apply our method to synthetic and real-world data sets for comparison with other related methods to demonstrate the utility of our contribution.

关键词： interpretable machine learning rule-based algorithms

来源：评论

学校读者我要写书评

暂无评论

An Evidence-based Framework for Creating Inclusive and Personalized mHealth Solutions-Designing a Solution for Medicaid-Eligible Pregnant Individuals With Uncontrolled Type 2 Diabetes

引用

JMIR DIABETES 2023年第1期8卷 e46654页

作者： Fareed, Naleef Swoboda, Christine Wang, Yiting Strouse, Robert Hoseus, Jenelle Baker, Carrie Joseph, Joshua J. Venkatesh, Kartik Ohio State Univ Coll Med Dept Biomed Informat 370 W 9th Ave Columbus OH 43210 USA Ohio State Univ Coll Med Ctr Advancement Team Sci Analyt & Syst Thinking Columbus OH USA Ohio State Univ Coll Med Dept Res Informat Technol Columbus OH USA Hlth Impact Ohio Columbus OH USA Ohio State Univ Coll Med Div Endocrinol Diabet & Metab Columbus OH USA Ohio State Univ Dept Obstet & Gynecol Div Maternal Fetal Med Columbus OH USA

Mobile health (mHealth) apps can be an evidence-based approach to improve health behavior and outcomes. Prior literature has highlighted the need for more research on mHealth personalization, including in diabetes and pregnancy. Critical gaps exist on the impact of personalization of mHealth apps on patient engagement, and in turn, health behaviors and outcomes. Evidence regarding how personalization, engagement, and health outcomescould be aligned when designing mHealth for underserved populations is much needed, given the historical oversights with mHealth design in these populations. This viewpoint is motivated by our experience from designing a personalized mHealth solution focused on Medicaid-enrolled pregnant individuals with uncontrolled type 2 diabetes, many of whom also experience a high burden of social needs. We describefundamental components of designing mHealth solutions that are both inclusive and personalized, forming the basis of an evidence-based framework for future mHealth design in other disease states with similar contexts.

关键词： personalization mobile health mHealth pregnancy pregnant maternal personalized diabetic algorithm diabetes rule-based algorithms social determinants of health inclusive inclusivity design

来源：评论

学校读者我要写书评

暂无评论

NooJ Grammars and Ethical algorithms: Tackling On-Line Hate Speech 12th

NooJ Grammars and Ethical Algorithms: Tackling On-Line Hate ...

引用

12th International Conference on Automatic Processing of Natural-Language Electronic Texts with NooJ (NooJ)

作者： Monteleone, Mario Univ Salerno Dipartimento Sci Polit Sociali & Comunicaz Fisciano Italy

ISBN: (纸本)9783030108670;9783030108687

The definition of "on-line hate speech" covers all forms of expression that propagate, incite, promote or justify hatred based on intolerance, including that expressed in the form of discrimination and hostility against minorities. Moreover, the concept of hatred includes other sub-concepts such as Homophobia, Racism, Chauvinism, Terrorism, Nationalism, Tolerance/Intolerance, and so on. Specifically, on-line hate speech is used in cases of cyber-harassment, to harm others deliberately, repeatedly and aggressively, in a way so to weaken victims psychologically. To contrast this phenomenon, EC has allocated a relevant amount of H2020 funds for the completion of specific research projects, the goal of which is the construction of computer tools to locate, evaluate and eventually block on-line hate speech. Today, the automatic tackling of online hatred is a daily-performed operation on Social Forums like Facebook, Twitter and Instagram. However, the algorithms these Social Forums use are stochastic/statistical, therefore not suitable to contextualize syntactically and semantically the words used inside posts. Therefore, with on-line hate speech tackling, statistical algorithms may produce inaccurate or even false results, with rather serious consequences.

关键词： NooJ NooJ finite-state automata/transducers On-line hate speech Ethical algorithms rule-based algorithms Statistical algorithms

来源：评论

学校读者我要写书评

暂无评论

SM-ruleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification

引用

COMPUTERS IN BIOLOGY AND MEDICINE 2017年 81卷 79-92页

作者： Cheruku, Ramalingaswamy Edla, Damodar Reddy Kuppili, Venkatanareshbabu Natl Inst Technol Goa Dept Comp Sci & Engn Ponda 403401 Goa India

Diabetes is a major health challenge around the world. Existing rule-based classification systems have been widely used for diabetes diagnosis, even though they must overcome the challenge of producing a comprehensive optimal ruleset while balancing accuracy, sensitivity and specificity values. To resolve this drawback, in this paper, a Spider Monkey Optimization-based rule miner (SM-ruleMiner) has been proposed for diabetes classification. A novel fitness function has also been incorporated into SM-ruleMiner to generate a comprehensive optimal ruleset while balancing accuracy, sensitivity and specificity. The proposed rule-miner is compared against three rule-based algorithms, namely ID3, C4.5 and CART, along with several meta-heuristic based rule mining algorithms, on the Pima Indians Diabetes dataset using 10-fold cross validation. It has been observed that the proposed rule miner outperforms several well-known algorithms in terms of average classification accuracy and average sensitivity. Moreover, the proposed rule miner outperformed the other algorithms in terms of mean rule length and mean ruleset size.

关键词： Spider monkey optimization Classification rules rule-based algorithms Diabetes diagnosis Optimal ruleset

来源：评论

学校读者我要写书评

暂无评论

Applying Classification Techniques To Predict Students' Academic Results

Applying Classification Techniques To Predict Students' Acad...

引用

IEEE International Conference on Current Trends in Advanced Computing (ICCTAC)

作者： Senthil, S. Lin, Wong Mu Reva Univ Sch Comp Sci & Applicat Bengaluru India

ISBN: (纸本)9781509049974

The ability to predict students' academic results is due to the application of various models developed using Data Mining techniques. It is one of the many applications available in Educational Data Mining (EDM). Although there are many classification algorithms available and there have been many researches done to compare certain algorithms, this study aims to compare Bayes-based, ANN-based, Regression-based, SVM-based, Instance-based, Tree-based and rule-based classification algorithms using a dataset downloaded online from UCI Machine Learning Repository. The data were preprocessed and categorized to different datasets before applying Data Mining techniques. Dimension reduction and data re-balancing were applied and proved to increase prediction accuracy. The algorithms were compared in terms of accuracy rate, precision rate, AUC and model building time. Tree-based algorithms performed better than other categories of algorithms. Within Tree-based algorithms, RandomForest algorithm proved to be the best classification algorithm. Tree-based and rule-based algorithms reveal the key attributes contributing to accurate prediction of students' results.

关键词： Educational Data Mining (EDM) Classification Knowledge Discovery in Databases (KDD) Tree-based algorithms rule-based algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：