Microblog posts (e.g. tweets) often contain users opinions and thoughts about events, products, people, organizations, among other possibilities. However, the usage of social media to promote online disinformation and manipulation is not an uncommon occurrence. Analyzing the characteristics of such discourses in social media is essential for understanding and fighting such actions. Extracting recurrent fragments of text, i.e. word sequences, which are semantically similar can lead to the discovery of linguistic patterns used in certain kinds of discourse. Therefore, we aim to use such patterns to encapsulate frequent discourses textually expressed in microblog posts. In this paper, we propose to exploit linguistic patterns in the context of the 2016 United Estates presidential election. Through a technique that we call Short Semantic Pattern (SSP) mining, we were able to extract sequences of words that share a similar meaning in their word embedding representation. In the experiments we investigate the incidence of SSP instances regarding political adversaries and media in tweets posted by Donald Trump, during the presidential election campaign. Experimental results show a high preponderance of some statements of Donald Trump towards their adversaries and expressions that often appeared in such tweets.
{"title":"Linguistic Pattern Mining for Data Analysis in Microblog Texts using Word Embeddings","authors":"Danielly Sorato, Renato Fileto","doi":"10.1145/3330204.3330228","DOIUrl":"https://doi.org/10.1145/3330204.3330228","url":null,"abstract":"Microblog posts (e.g. tweets) often contain users opinions and thoughts about events, products, people, organizations, among other possibilities. However, the usage of social media to promote online disinformation and manipulation is not an uncommon occurrence. Analyzing the characteristics of such discourses in social media is essential for understanding and fighting such actions. Extracting recurrent fragments of text, i.e. word sequences, which are semantically similar can lead to the discovery of linguistic patterns used in certain kinds of discourse. Therefore, we aim to use such patterns to encapsulate frequent discourses textually expressed in microblog posts. In this paper, we propose to exploit linguistic patterns in the context of the 2016 United Estates presidential election. Through a technique that we call Short Semantic Pattern (SSP) mining, we were able to extract sequences of words that share a similar meaning in their word embedding representation. In the experiments we investigate the incidence of SSP instances regarding political adversaries and media in tweets posted by Donald Trump, during the presidential election campaign. Experimental results show a high preponderance of some statements of Donald Trump towards their adversaries and expressions that often appeared in such tweets.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116808321","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}
Thais Mester Barboza, F. Santoro, K. Revoredo, Rosa Costa
A business process is a sequence of activities logically organized with the goal to produce a service or product which add value for a customer. Process auditing in corporate environment aims to assess the degree of compliance of processes and their controls. Due to the volume of information that needs to be analyzed in an audit job, its cost can be very high. We argue that process mining has the potential to improve this activity, allowing the auditor to meet the short deadlines, as well as bringing greater value to the senior management and reliability in the service provided by the audit. Our goal is to discuss how process mining can improve and bring agility to the verification of conformity of the process model against the process actually carried out in an organization.
{"title":"A Case Study of Process Mining in Auditing","authors":"Thais Mester Barboza, F. Santoro, K. Revoredo, Rosa Costa","doi":"10.1145/3330204.3330241","DOIUrl":"https://doi.org/10.1145/3330204.3330241","url":null,"abstract":"A business process is a sequence of activities logically organized with the goal to produce a service or product which add value for a customer. Process auditing in corporate environment aims to assess the degree of compliance of processes and their controls. Due to the volume of information that needs to be analyzed in an audit job, its cost can be very high. We argue that process mining has the potential to improve this activity, allowing the auditor to meet the short deadlines, as well as bringing greater value to the senior management and reliability in the service provided by the audit. Our goal is to discuss how process mining can improve and bring agility to the verification of conformity of the process model against the process actually carried out in an organization.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"3 22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128030041","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}
McLyndon S. de L. Xavier, Kleinner Farias, Jorge Barbosa, L. Gonçales, Vinicius Bishoff
In collaborative software modeling the two main types of collaboration still present problems, such as the constant interruptions that hinder the cognitive process in synchronous collaboration, and the complicated and costly stages of conflict resolution in asynchronous collaboration. For this, this paper proposes a technique called "UMLCollab". This technique combines aspects from synchronous and asynchronous collaboration. Through experiments, developers applied the proposed solution and they achieved to an intermediate productivity in relation to traditional collaboration methods. The results showed that the "UMLCollab" improved the correctness of the changed models, the notion of developer regarding to the resolution of conflicts, and enabled the parallel changes occurring while other collaborators are working on without degrade the software diagrams being modelled locally.
{"title":"UMLCollab","authors":"McLyndon S. de L. Xavier, Kleinner Farias, Jorge Barbosa, L. Gonçales, Vinicius Bishoff","doi":"10.1145/3330204.3330239","DOIUrl":"https://doi.org/10.1145/3330204.3330239","url":null,"abstract":"In collaborative software modeling the two main types of collaboration still present problems, such as the constant interruptions that hinder the cognitive process in synchronous collaboration, and the complicated and costly stages of conflict resolution in asynchronous collaboration. For this, this paper proposes a technique called \"UMLCollab\". This technique combines aspects from synchronous and asynchronous collaboration. Through experiments, developers applied the proposed solution and they achieved to an intermediate productivity in relation to traditional collaboration methods. The results showed that the \"UMLCollab\" improved the correctness of the changed models, the notion of developer regarding to the resolution of conflicts, and enabled the parallel changes occurring while other collaborators are working on without degrade the software diagrams being modelled locally.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123710803","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}
Nicolas Jashchenko Omori, G. Tavares, P. Ceravolo, Sylvio Barbon Junior
Organisations have seen a rise in the volume of data corresponding to business processes being recorded. Handling process data is a meaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, business processes are subject to changes during their executions, adding complexity to their analysis. This paper aims at evaluating currently available Process Mining tools that handle concept drifts, i.e. changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these tools briefly comparing their differences, advantages, and disadvantages.
{"title":"Comparing Concept Drift Detection with Process Mining Tools","authors":"Nicolas Jashchenko Omori, G. Tavares, P. Ceravolo, Sylvio Barbon Junior","doi":"10.1145/3330204.3330240","DOIUrl":"https://doi.org/10.1145/3330204.3330240","url":null,"abstract":"Organisations have seen a rise in the volume of data corresponding to business processes being recorded. Handling process data is a meaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, business processes are subject to changes during their executions, adding complexity to their analysis. This paper aims at evaluating currently available Process Mining tools that handle concept drifts, i.e. changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these tools briefly comparing their differences, advantages, and disadvantages.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114932815","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}
This paper presents the results a case study that apply opinion mining about health, security and education, using as source discussions in Facebook regional groups. The method used is quite different from other researches because it propose an approach to identify regional posts. Five different supervisioned learning algorithms was applied during the classification step. The results show that region's posts can be identified with this new approach.
{"title":"Opinion Mining in Facebook Regional Discussion Groups: A Case Study to Identify Health, Education and Security Posts in Discussion Groups","authors":"Leonardo Augusto Sápiras, Rodrigo Antônio Weber","doi":"10.1145/3330204.3330221","DOIUrl":"https://doi.org/10.1145/3330204.3330221","url":null,"abstract":"This paper presents the results a case study that apply opinion mining about health, security and education, using as source discussions in Facebook regional groups. The method used is quite different from other researches because it propose an approach to identify regional posts. Five different supervisioned learning algorithms was applied during the classification step. The results show that region's posts can be identified with this new approach.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130411821","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}
Michael William Chagas, Kleinner Farias, L. Gonçales, L. S. Kupssinskü, J. Gluz
Software maintenance is a costly task and error-prone for both software developers and users as well. By knowing how and what software requirements need to be changed, end users could perform maintenance assisted by tools. However, current literature lacks for tools that support automated maintenance in real-world scenarios and allow users interaction via natural language. Even worse, the current tools are unable to understand the semantic of requests, as well as perform the necessary transformations in the maintenance software. This paper, therefore, proposes Hermes, a natural language interface model for software transformation. It combines computational linguistics techniques and logic programming to perform automated maintenance requests in software. Hermes interacts with end user through state of the art language parsers and domain ontologies by interpreting the semantics of changes requests to build a typed graph that change the software. Hermes was evaluated through an empirical study with 8 participants to investigate its performance, the level of acceptance, and usability. The collected data show that Hermes was accurate, producing a high elevated correctness number of hits by finding correct transformations and has been highly accepted by the users. The results are encouraging and show the potential for using Hermes to properly produce software maintenance requests.
{"title":"Hermes: A Natural Language Interface Model for Software Transformation","authors":"Michael William Chagas, Kleinner Farias, L. Gonçales, L. S. Kupssinskü, J. Gluz","doi":"10.1145/3330204.3330253","DOIUrl":"https://doi.org/10.1145/3330204.3330253","url":null,"abstract":"Software maintenance is a costly task and error-prone for both software developers and users as well. By knowing how and what software requirements need to be changed, end users could perform maintenance assisted by tools. However, current literature lacks for tools that support automated maintenance in real-world scenarios and allow users interaction via natural language. Even worse, the current tools are unable to understand the semantic of requests, as well as perform the necessary transformations in the maintenance software. This paper, therefore, proposes Hermes, a natural language interface model for software transformation. It combines computational linguistics techniques and logic programming to perform automated maintenance requests in software. Hermes interacts with end user through state of the art language parsers and domain ontologies by interpreting the semantics of changes requests to build a typed graph that change the software. Hermes was evaluated through an empirical study with 8 participants to investigate its performance, the level of acceptance, and usability. The collected data show that Hermes was accurate, producing a high elevated correctness number of hits by finding correct transformations and has been highly accepted by the users. The results are encouraging and show the potential for using Hermes to properly produce software maintenance requests.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130992099","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}
Anderson S. Barroso, Kleber H. de J. Prado, M. S. Soares, R. Nascimento
The activity of analyzing personality of software developers has been a topic discussed by many researchers over the past few years. However, their relation to software metrics has hardly been mentioned in the literature. This work aims to identify the influence of human personality on quality of software products. At first, a psychological test was performed using the MBTI model for a set of academy students and, subsequently, CK metrics were applied to individual software developed by members of the same group. As a result, it was evidenced, through statistical analysis, that the Response For a Classe(RFC) and Weighted Methods Per Class (WMC) metric, do not have a significant relationship with MBTI types. In another analysis, taking into account ideal average values for each CK metric, it was evidenced that Depth of Inheritance(DIT) metric have a significant relationship with MBTI types. Therefore, additional studies are needed to determine any deeper connection between personality and software quality.
{"title":"How personality traits influences quality of software developed by students","authors":"Anderson S. Barroso, Kleber H. de J. Prado, M. S. Soares, R. Nascimento","doi":"10.1145/3330204.3330237","DOIUrl":"https://doi.org/10.1145/3330204.3330237","url":null,"abstract":"The activity of analyzing personality of software developers has been a topic discussed by many researchers over the past few years. However, their relation to software metrics has hardly been mentioned in the literature. This work aims to identify the influence of human personality on quality of software products. At first, a psychological test was performed using the MBTI model for a set of academy students and, subsequently, CK metrics were applied to individual software developed by members of the same group. As a result, it was evidenced, through statistical analysis, that the Response For a Classe(RFC) and Weighted Methods Per Class (WMC) metric, do not have a significant relationship with MBTI types. In another analysis, taking into account ideal average values for each CK metric, it was evidenced that Depth of Inheritance(DIT) metric have a significant relationship with MBTI types. Therefore, additional studies are needed to determine any deeper connection between personality and software quality.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129133560","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}
Mallú Eduarda Batista, Paulo Afonso Parreira Júnior, H. Costa
Code clones are source code parts that are identical or have some degree of similarity to another part of the code. Cloning arises for a variety of reasons, including copy and paste and the reuse of ad-hoc code by programmers. Detection of information system clones is aimed at propagating changes by all clones at the development, maintenance and evolution stages, preserving data consistency, correcting errors, and so on. Clones can be classified as 1, 2, 3 and 4, depending on their similarity and characteristics that classify them as such. Several techniques and tools have been created with the objective of detecting code clones, and for this, they use techniques of representation of the source code in text, token, tree, graphic, hybrid and metrics. This systematic mapping work presents answers to the four research questions, which aim to identify, count and catalog, data from a set of 875 articles, of which 128 were selected, for the selection of relevant information seeking to provide content for the collection of data objectified. In all, 52 clone detection tools were identified, which reinforce the current theme; 26 ways of presenting source code to detect clones, where the commonly used ones stand out for ease of understanding and handling; 13 programming languages in 6 paradigms and the identification, highlighting the great presence of clones detection in object oriented information systems, of all 4 types of clones, as well as semantic and syntactic clones, which reinforces the current questioning of authors of this division search line into four types.
{"title":"An Exploratory Study on Detection of Cloned Code in Information Systems","authors":"Mallú Eduarda Batista, Paulo Afonso Parreira Júnior, H. Costa","doi":"10.1145/3330204.3330277","DOIUrl":"https://doi.org/10.1145/3330204.3330277","url":null,"abstract":"Code clones are source code parts that are identical or have some degree of similarity to another part of the code. Cloning arises for a variety of reasons, including copy and paste and the reuse of ad-hoc code by programmers. Detection of information system clones is aimed at propagating changes by all clones at the development, maintenance and evolution stages, preserving data consistency, correcting errors, and so on. Clones can be classified as 1, 2, 3 and 4, depending on their similarity and characteristics that classify them as such. Several techniques and tools have been created with the objective of detecting code clones, and for this, they use techniques of representation of the source code in text, token, tree, graphic, hybrid and metrics. This systematic mapping work presents answers to the four research questions, which aim to identify, count and catalog, data from a set of 875 articles, of which 128 were selected, for the selection of relevant information seeking to provide content for the collection of data objectified. In all, 52 clone detection tools were identified, which reinforce the current theme; 26 ways of presenting source code to detect clones, where the commonly used ones stand out for ease of understanding and handling; 13 programming languages in 6 paradigms and the identification, highlighting the great presence of clones detection in object oriented information systems, of all 4 types of clones, as well as semantic and syntactic clones, which reinforces the current questioning of authors of this division search line into four types.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"17 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131741301","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}
A. Monteiro, A. D. Souza, B. Batista, Mauricio Zaparoli
The social media exerts an important role in publishing information and newspaper online. The quality of this information and the sentiment analysis might help predict the price of diverse market asset and cause great gains and losses. In this scenario, many researchers have been studying the diverse aspects that influence this area. Recently, cryptocurrencies have gained a spotlight between financial assets and, one of its characteristics is the fact that its market is strongly influenced by opinions and speculation being a proper area for sentiment analysis and data mining techniques. However, there is not any complete theoretical and technical framework about this subject. Due to its interdisciplinary characteristics involving topics in economics, human behavior, and artificial intelligence, there is a lack of clarity about the techniques and tools used in sentiment analysis in the cryptocurrencies scenario. The goal of this paper is to analyze related research in market prediction based on text mining and other artificial intelligence techniques and generate a systematic mapping about the main research, identifing the possible gaps in this field. This work might help the research community to better structure this emerging area and identify more exactly aspects that require research and are of essential importance.
{"title":"Market Prediction in Criptocurrency: A Systematic Literature Mapping","authors":"A. Monteiro, A. D. Souza, B. Batista, Mauricio Zaparoli","doi":"10.1145/3330204.3330272","DOIUrl":"https://doi.org/10.1145/3330204.3330272","url":null,"abstract":"The social media exerts an important role in publishing information and newspaper online. The quality of this information and the sentiment analysis might help predict the price of diverse market asset and cause great gains and losses. In this scenario, many researchers have been studying the diverse aspects that influence this area. Recently, cryptocurrencies have gained a spotlight between financial assets and, one of its characteristics is the fact that its market is strongly influenced by opinions and speculation being a proper area for sentiment analysis and data mining techniques. However, there is not any complete theoretical and technical framework about this subject. Due to its interdisciplinary characteristics involving topics in economics, human behavior, and artificial intelligence, there is a lack of clarity about the techniques and tools used in sentiment analysis in the cryptocurrencies scenario. The goal of this paper is to analyze related research in market prediction based on text mining and other artificial intelligence techniques and generate a systematic mapping about the main research, identifing the possible gaps in this field. This work might help the research community to better structure this emerging area and identify more exactly aspects that require research and are of essential importance.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114399526","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}
Tiago Moraes Ferreira, Fernando Costella, Alisson Borges Zanetti, Silvano Elias da Silva, A. L. Zanatta, Ana Carolina Bertoletti De Marchi
Collective intelligence is an interdisciplinary topic that has been explored by different areas of knowledge, like information systems, being a common practice of knowledge exchange through new forms of organization and flexible coordination in real time. Crowdsourcing emerges in this context as an act of externalizing, through the Internet, a task traditionally done internally in the organization for an undefined (and often large) group of people. However, one of the challenges found in this model is how users select and interact with available tasks for execution. Therefore, this work presents a prototype task recommendation system tool, with user experience-oriented design (UX), called CrowdRec, executed through the Google Ventures Design Studio method in conjunction with the Quant-UX tool. To evaluate the results, the TAM analysis with a five-point Likert scale was used. The results show positive interactions in the prototype.
{"title":"CrowdRec","authors":"Tiago Moraes Ferreira, Fernando Costella, Alisson Borges Zanetti, Silvano Elias da Silva, A. L. Zanatta, Ana Carolina Bertoletti De Marchi","doi":"10.1145/3330204.3330235","DOIUrl":"https://doi.org/10.1145/3330204.3330235","url":null,"abstract":"Collective intelligence is an interdisciplinary topic that has been explored by different areas of knowledge, like information systems, being a common practice of knowledge exchange through new forms of organization and flexible coordination in real time. Crowdsourcing emerges in this context as an act of externalizing, through the Internet, a task traditionally done internally in the organization for an undefined (and often large) group of people. However, one of the challenges found in this model is how users select and interact with available tasks for execution. Therefore, this work presents a prototype task recommendation system tool, with user experience-oriented design (UX), called CrowdRec, executed through the Google Ventures Design Studio method in conjunction with the Quant-UX tool. To evaluate the results, the TAM analysis with a five-point Likert scale was used. The results show positive interactions in the prototype.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125069847","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}
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