J. Inf. Data Manag.最新文献_第6页

MediBot: An Ontology-Based Chatbot to Retrieve Drug Information and Compare its Prices MediBot:一个基于本体的聊天机器人检索药品信息并比较其价格

J. Inf. Data Manag. Pub Date : 2021-09-10 DOI: 10.5753/jidm.2021.2148

Caio Viktor S. Avila, Wellington Franco, A. D. P. Venceslau, T. V. Rolim, V. Vidal, V. Pequeno

引用次数: 3

brModelo: An Initiative for Aiding Database Design brModelo:辅助数据库设计的倡议

J. Inf. Data Manag. Pub Date : 2021-09-10 DOI: 10.5753/jidm.2021.1983

R. Mello, Carlos Henrique Cândido, Milton Bittencourt S. Neto

引用次数: 1

The effect of political polarization on social distance stances in the Brazilian COVID-19 scenario 巴西 COVID-19 情景中政治两极化对社会距离立场的影响

J. Inf. Data Manag. Pub Date : 2021-08-05 DOI: 10.5753/jidm.2021.1889

Régis Ebeling, Carlos Abel Córdova Sáenz, J. Nobre, Karin Becker

{"title":"The effect of political polarization on social distance stances in the Brazilian COVID-19 scenario","authors":"Régis Ebeling, Carlos Abel Córdova Sáenz, J. Nobre, Karin Becker","doi":"10.5753/jidm.2021.1889","DOIUrl":"https://doi.org/10.5753/jidm.2021.1889","url":null,"abstract":"The COVID-19 pandemic changed the routine and concerns of people around the world since 2020. The alarming contagious rate and the lack of treatment or vaccine evoked different reactions to controlling and mitigating the virus's contagious. In this paper, we developed a case study on the Brazilian COVID scenario, investigating the influence of the political polarization in the pro/against stances of social isolation, represented in Twitter by two groups referred to as the Cloroquiners and Quarenteners. We analyzed these groups according to multiple dimensions: a) concerns expressed by each group and main arguments representing each stance; b) techniques to automatically infer from users political orientation, c) network analysis and community detection to characterize their behavior as a social network group and d) analysis of linguistic characteristics to identify psychological aspects. We propose combining two topic modeling techniques, LDA and BERTopics, to understand each stance's concerns in different granularity levels. Our main findings confirm that Cloroquiners are right-wing partisans, whereas Quarenteners are more related to the left-wing. Cloroquiners and Quarenteners' political polarization influences the arguments of economy and life and a stronger support/opposition to the president. As a group, the network of Cloroquiners is more closed and connected, and Quarenteners have a more diverse political engagement with a community of users polarized only with left-wing politicians and his supporters. In terms of psychological aspects, polarized groups come together on cognitive issues and negative emotions.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Analysis of Distinct Feature Groups in the Credit Scoring Problem 信用评分问题中的显著特征组分析

J. Inf. Data Manag. Pub Date : 2021-08-05 DOI: 10.5753/jidm.2021.1930

L. Verçosa, R. Lira, R. Monteiro, Kleber D. M. Silva, Jailson O. L. Magalhães, A. M. A. Maciel, B. Bezerra, C. B. Filho

{"title":"Analysis of Distinct Feature Groups in the Credit Scoring Problem","authors":"L. Verçosa, R. Lira, R. Monteiro, Kleber D. M. Silva, Jailson O. L. Magalhães, A. M. A. Maciel, B. Bezerra, C. B. Filho","doi":"10.5753/jidm.2021.1930","DOIUrl":"https://doi.org/10.5753/jidm.2021.1930","url":null,"abstract":"Registration and financial data have been traditionally used for the credit scoring problem. However,slight improvements in the reliability of the scores positively impacts financial companies. Therefore, exploring newfeatures is a strategic task. This work analyzes the importance of new feature groups not commonly employed forthe credit scoring task and others already used. We categorized features from open credit scoring datasets, suchas German and Australian and compared their groups with the ones of a company dataset used in this work. Ourdataset contains unusual feature groups, such as historical, geolocation, web behavior, and demographic data. In ouranalyzes, we first conducted bivariate tests with each feature-pair to assess their individual importance. Secondly, weran XGBoost machine learning model with each feature group to evaluate each group importance. We also appliedfeature selection with binary Particle Swarm Optimization to assess the groups importance when combined. Next, weemployed correlation tests to find inner and inter-correlation among the features groups. Finally, we used the companydataset and employed AdaBoost, Multilayer Perceptron, and XGBoost algorithms to find the best model for the task.Some of our main findings were that the unusual features added a slight improvement to registration features. We alsodetected reasonable inner correlation among some feature groups and found that all groups were relevant for the taskwith the Historical Group as the most promising. Lastly, XGBoost obtained the best performance over AdaBoost andMultilayer-perceptron for the task.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"15 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114861133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the combination of DistilBERT news representations and difusion topological features to classify fake news 评估蒸馏新闻表示和扩散拓扑特征相结合的假新闻分类

J. Inf. Data Manag. Pub Date : 2021-08-05 DOI: 10.5753/jidm.2021.1895

Carlos Abel Córdova Sáenz, Marcelo Dias, Karin Becker

{"title":"Assessing the combination of DistilBERT news representations and difusion topological features to classify fake news","authors":"Carlos Abel Córdova Sáenz, Marcelo Dias, Karin Becker","doi":"10.5753/jidm.2021.1895","DOIUrl":"https://doi.org/10.5753/jidm.2021.1895","url":null,"abstract":"Fake news (FN) have affected people’s lives in unimaginable ways. The automatic classification of FN is a vital tool to prevent their dissemination and support fact-checking. Related work has shown that FN spread faster, deeper, and more broadly than truthful news on social media. Deep learning has produced state-of-the-art solutions in this field, mainly based on textual attributes. In this paper, we propose to combine compact representations of the textual news properties generated using DistilBERT, with topological metrics extracted from their propagation network in social media. Using a dataset related to politics and distinct learning algorithms, we extensively assessed the components of the proposed solution. Regarding the textual attributes, we reached results comparable to stateof-the-art solutions using only the news title and contents, which is useful for FN early detection. We assessed the influential topological metrics, and the effect of their combination with the news textual features. We also explored the use of ensembles. Our results were very promising, revealing the potential of the features proposed and the adoption of ensembles.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116725123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Exploratory Analysis of Electronic Health Records using Topic Modeling 利用主题建模对电子健康记录进行探索性分析

J. Inf. Data Manag. Pub Date : 2021-02-14 DOI: 10.5753/jidm.2020.2024

Denio Duarte, I. Puerari, Guilherme Dal Bianco, Julyane Felipette Lima

{"title":"Exploratory Analysis of Electronic Health Records using Topic Modeling","authors":"Denio Duarte, I. Puerari, Guilherme Dal Bianco, Julyane Felipette Lima","doi":"10.5753/jidm.2020.2024","DOIUrl":"https://doi.org/10.5753/jidm.2020.2024","url":null,"abstract":"The rapid growth of electronic health record (EHR) systems brings an increase in available information about patients in hospitals. This massive amount of text information presents an opportunity to extract unknown information about medical history, medication, diseases, allergies, among others. Extracting the main topics that represent the subjects covered by a text collection can give valuable insights. To this end, approaches for topic modeling have been used to tackle such problems as information discovery and topic extraction with thematic information. In this context, this work presents an exploratory analysis of a collection of electronic health records from an intensive care unit (ICU). The collection is split into two sub-collections: discharged patients and patients who progressed to death. We apply an LDA-based approach to discover the latent topics from the collections. The analyses show that some topics are more recurrent in the deceased patients (the death collection), like renal diseases, and others are more recurrent in the discharge collection, for example, diabetes. The results of the analyses can be useful for improving intensive care services since the topics can be a guide to understanding the patterns in discharge and death situations.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128352560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Frontmatter

J. Inf. Data Manag. Pub Date : 2021-01-13 DOI: 10.1515/ijb-2021-frontmatter2

Angelo Brayner, M. Holanda

引用次数: 0

SAVIME: An Array DBMS for Simulation Analysis and ML Models Prediction savme:用于模拟分析和ML模型预测的数组DBMS

J. Inf. Data Manag. Pub Date : 2020-12-30 DOI: 10.5753/JIDM.2020.2021

A. Silva, Hermano Lustosa, Daniel Nascimento Ramos da Silva, F. Porto, P. Valduriez

引用次数: 7

Mining Temporal Exception Rules from Multivariate Time Series Using a new Support Measure 基于新支持测度的多元时间序列时间异常挖掘

J. Inf. Data Manag. Pub Date : 2020-12-30 DOI: 10.5753/jidm.2020.2020

Thábata Amaral, Elaine P. M. de Sousa

{"title":"Mining Temporal Exception Rules from Multivariate Time Series Using a new Support Measure","authors":"Thábata Amaral, Elaine P. M. de Sousa","doi":"10.5753/jidm.2020.2020","DOIUrl":"https://doi.org/10.5753/jidm.2020.2020","url":null,"abstract":"Association rules are a common task to discover useful and comprehensive relationships among frequent and infrequent data. Frequent patterns describe a usual behavior, while infrequent ones represent uncommon knowledge. Our interest lies in finding exception rules, a class of infrequent patterns that may have critical effects as a consequence. Existing approaches for exception rules mining usually handle “itemsets databases”, where transactions are organized with no temporal information. However, temporality may be inherent to some real contexts and should be considered to improve the semantic quality of results. Moreover, these approaches implement a non-discriminatory support measure to estimate the relevance of an item, thus interpreting a large volume of data that may be merely occasional as patterns. Aiming to overcome these drawbacks, we propose TRiER (TempoRal Exception Ruler), an efficient method for mining temporal exception rules that not only discover exceptional behaviors and their causative agents, but also identifies how long consequences take to appear. We also present a new support measure to manipulate time series. This measure considers the context in which a pattern occurs, thus incorporating more semantics to the results obtained. We performed an extensive experimental analysis in real multivariate time series to verify the practical applicability of TRiER. Our results show TRiER has lower computational cost and is more scalable than existing approaches while finding a succinct and relevant set of patterns.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129522827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Experimental Analysis of the Use of Different Storage Technologies on a Relational DBMS 关系型数据库管理系统中不同存储技术应用的实验分析

J. Inf. Data Manag. Pub Date : 2020-12-30 DOI: 10.5753/JIDM.2020.1868

Francisco D. B. S. Praciano, Italo C. Abreu, Javam C. Machado

引用次数: 0