J. Inf. Data Manag.最新文献_第7页

Polyflow: a Polystore-compliant Mechanism to Provide Interoperability to Heterogeneous Provenance Graphs Polyflow:一个兼容多存储的机制，为异构来源图提供互操作性

J. Inf. Data Manag. Pub Date : 2020-11-13 DOI: 10.5753/JIDM.2020.2017

Yan Mendes, Daniel de Oliveira, Victor Ströele

{"title":"Polyflow: a Polystore-compliant Mechanism to Provide Interoperability to Heterogeneous Provenance Graphs","authors":"Yan Mendes, Daniel de Oliveira, Victor Ströele","doi":"10.5753/JIDM.2020.2017","DOIUrl":"https://doi.org/10.5753/JIDM.2020.2017","url":null,"abstract":"Many scientific experiments are modeled as workflows. Workflows usually output massive amounts of data. To guarantee the reproducibility of workflows, they are usually orchestrated by Workflow Management Systems (WfMS), that capture provenance data. Provenance represents the lineage of a data fragment throughout its transformations by activities in a workflow. Provenance traces are usually represented as graphs. These graphs allows scientists to analyze and evaluate results produced by a workflow. However, each WfMS has a proprietary format for provenance and do it in different granularity levels. Therefore, in more complex scenarios in which the scientist needs to interpret provenance graphs generated by multiple WfMSs and workflows, a challenge arises. To first understand the research landscape, we conduct a Systematic Literature Mapping, assessing existing solutions under several different lenses. With a clearer understanding of the state of the art, we propose a tool called Polyflow, which is based on the concept of Polystore systems, integrating several databases of heterogeneous origin by adopting a global ProvONE schema. Polyflow allows scientists to query multiple provenance graphs in an integrated way. Polyflow was evaluated by experts using provenance data collected from real experiments that generate phylogenetic trees through workflows. The experiment results suggest that Polyflow is a viable solution for interoperating heterogeneous provenance data generated by different WfMSs, from both a usability and performance standpoint.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114905368","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

Automated classification of cardiology diagnoses based on textual medical reports 基于文本医学报告的心脏病诊断自动分类

J. Inf. Data Manag. Pub Date : 2020-10-20 DOI: 10.5753/kdmile.2020.11975

João A. O. Pedrosa, D. Oliveira, Wagner Meira, A. L. Ribeiro

引用次数: 3

Query co-planning for shared execution in Key-Value Stores 键值存储中共享执行的查询协同规划

J. Inf. Data Manag. Pub Date : 2020-09-28 DOI: 10.5753/sbbd.2020.13643

J. Ttito, Renato Marroquín, Sérgio Lifschitz

引用次数: 0

Weighted Linking Decomposition: Mining Denser and More Compact Hierarchies for Bipartite Graphs 加权链接分解:挖掘二部图的更密集和更紧凑的层次

J. Inf. Data Manag. Pub Date : 2020-06-30 DOI: 10.5753/JIDM.2020.2031

Edré Moreira, G. Campos, Wagner Meira Jr

引用次数: 0

World Cups Impact Analysis in the Soccer Players Transaction and Soccer Globalization using Complex Network Techniques 利用复杂网络技术分析足球运动员交易与足球全球化对世界杯的影响

J. Inf. Data Manag. Pub Date : 2019-12-30 DOI: 10.5753/jidm.2019.2035

A. P. S. Alves, Lucas G. S. Félix, C. M. Barbosa, Vitor Elisiário Carmo, V. D. F. Vieira, C. R. Xavier

引用次数: 0

Investigating the Relation Between Companies with Topological Analysis of a Network of Stock Exchange in Brazil 用巴西证券交易所网络的拓扑分析考察公司间的关系

J. Inf. Data Manag. Pub Date : 2019-12-30 DOI: 10.5753/jidm.2019.2033

V. D. F. Vieira, Lucas G. S. Félix, C. M. Barbosa, C. R. Xavier

{"title":"Investigating the Relation Between Companies with Topological Analysis of a Network of Stock Exchange in Brazil","authors":"V. D. F. Vieira, Lucas G. S. Félix, C. M. Barbosa, C. R. Xavier","doi":"10.5753/jidm.2019.2033","DOIUrl":"https://doi.org/10.5753/jidm.2019.2033","url":null,"abstract":"B3 (Brasil, Bolsa, Balcão) is the official stock exchange in Brazil and plays a key role in the world financial market. Stock exchange allows people and companies to relate through the shareholding and the purchase and sale of shares. The study of the relationship between people and companies can reveal valuable information about the operation of the stock exchange and, consequently, the financial market as a whole. In this work, the relations in B3 are modeled as a network, in which the vertices represent companies and people and the edges represent shareholdings. From the built network, several analyzes are performed with the objective of understanding and characterizing the patterns found in relationships. Investigation on the topology of the network is performed under different perspectives, such as the centrality of the vertices, organization of vertices in communities, the robustness and the diffusion of influence. The results show a strong community structure in the B3 network and, even though the network is fragile for the removal of vetices, the definition of the criterion of vertices to be chosen as a target can be determinant in the characterization of the robustness.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132286282","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

Generating Links for Patent Documents: an Automatic Approach using Computational Intelligence 专利文件的链接生成:一种使用计算智能的自动方法

J. Inf. Data Manag. Pub Date : 2019-12-30 DOI: 10.5753/jidm.2019.2032

C. M. Souza, M. E. Santos, M. Meireles

{"title":"Generating Links for Patent Documents: an Automatic Approach using Computational Intelligence","authors":"C. M. Souza, M. E. Santos, M. Meireles","doi":"10.5753/jidm.2019.2032","DOIUrl":"https://doi.org/10.5753/jidm.2019.2032","url":null,"abstract":"Patents are organized into classification systems, which assist offices and users in the process of seeking and retrieving such documents. A wide variety of users use the patent systems and the information contained in these documents. However, patents are complex legal documents with a significant number of technical and descriptive details, which makes it difficult to identify and analyze the information contained in these documents. An automatic link system associated with some of the terms found in the patents would provide quick access to the concepts contained in specific knowledge bases. This work presents results of a project in which the objective is the automatic generation of links in patent documents. The experiments were conducted with four subgroups of the United States Patent and Trademark Office (USPTO), which uses the Cooperative Patent Classification (CPC) system. As the patent documents did not have keywords, the meaningful terms were selected using the algorithm χ2, for which the contents of the entire patent document were used. Some keywords with more than one meaning were disambiguated using a specific algorithm, generating a file with useful information used in the experiments. The links were generated based on Wikipedia articles and the USPTO patent database. The use of the patent database as a possible destination for the link is intended to cover cases in which Wikipedia has no articles on certain terms and also to provide an alternative source that may assist readers in understanding those documents. It is expected, with the creation of automated links, to make it easier to access concepts related to the terms presented by the documents and to understand the information disclosed by the inventors.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122539707","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

Exploring Deep Learning for the Analysis of Emotional Reactions to Terrorist Events on Twitter 探索深度学习分析Twitter上对恐怖事件的情绪反应

J. Inf. Data Manag. Pub Date : 2019-10-31 DOI: 10.5753/jidm.2019.2039

Karin Becker, Jonathas G. D. Harb, Régis Ebeling

{"title":"Exploring Deep Learning for the Analysis of Emotional Reactions to Terrorist Events on Twitter","authors":"Karin Becker, Jonathas G. D. Harb, Régis Ebeling","doi":"10.5753/jidm.2019.2039","DOIUrl":"https://doi.org/10.5753/jidm.2019.2039","url":null,"abstract":"Terrorist events have a substantial emotional impact on the population, and understanding these effects is very important to design effective assistance programs. However, investigating community-wide traumas is a complex and costly task, where most challenges are related to the data collection process. Social media has been used as a relevant source of data to investigate people’s sentiments and ideas. In this article, we study the emotional reactions of Twitter users regarding two terrorist events that occurred in the United Kingdom. The contributions are twofold: a) we experiment two deep learning architectures to develop an emotion classifier, and b) we develop an analysis on tweets related to terrorist events to underst and whether there is an emotional shift due to a terrorist attack andwhether the emotional reactions are dependent on the event, or on the demographics of the users. Both models, based on convolutional and recurrent neural architectures, presented very similar performances. The analyses revealed an emotion shift due to the events and a difference in the reactions to each specific event, where gender is the most significant factor.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117139866","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: 12

Time Series Forecasting to Support Irrigation Management 时间序列预测支持灌溉管理

J. Inf. Data Manag. Pub Date : 2019-10-31 DOI: 10.5753/jidm.2019.2037

D. Braga, T. C. D. Silva, A. D. Rocha, Gustavo Coutinho, R. P. Magalhães, Paulo T. Guerra, J. Macêdo, Simone D. J. Barbosa

{"title":"Time Series Forecasting to Support Irrigation Management","authors":"D. Braga, T. C. D. Silva, A. D. Rocha, Gustavo Coutinho, R. P. Magalhães, Paulo T. Guerra, J. Macêdo, Simone D. J. Barbosa","doi":"10.5753/jidm.2019.2037","DOIUrl":"https://doi.org/10.5753/jidm.2019.2037","url":null,"abstract":"Irrigated agriculture is the most water-consuming sector in Brazil, representing one of the main challenges for the sustainable use of water. This study has investigated and evaluated popular machine learning techniques like Gradient Boosting and Random Forest, deep learning models and univariate time series models to predict the value of reference evapotranspiration, a metric of water loss from the crop to the environment. The reference evapotranspiration ET0, plays an essential role in irrigation management since it can be used to reduce the amount of water that will not be absorbed by the crop. We performed the experiments with two real datasets generated by weather stations. The results show that the deep learning models are data-hungry, even when we increased the training set it was not enough to outperform multivariate models like Random Forest, Gradient Boosting and M5’ which indeed execute faster than the deep learning models during the training phase. However, the univariate time series model as the evaluated deep learning models (stacked LSTM and BLSTM) is a viable and lower-cost solution for predicting ET0, since we need to monitor only one variable.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131756337","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: 6

Interactive Visualization of Trivariate Georeferenced Data 三变量地理参考数据的交互式可视化

J. Inf. Data Manag. Pub Date : 2018-12-30 DOI: 10.5753/jidm.2018.2043

Tarsus Magnus Pinheiro, Claudio Esperança

引用次数: 0