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Text Mining Business Policy Documents: Applied Data Science in Finance 文本挖掘业务策略文档:在金融中的应用数据科学
Int. J. Bus. Intell. Res. Pub Date : 2020-07-01 DOI: 10.4018/ijbir.20200701.oa1
M. Spruit, D. Ferati
{"title":"Text Mining Business Policy Documents: Applied Data Science in Finance","authors":"M. Spruit, D. Ferati","doi":"10.4018/ijbir.20200701.oa1","DOIUrl":"https://doi.org/10.4018/ijbir.20200701.oa1","url":null,"abstract":"In a time when the employment of natural language processing techniques in domains such as biomedicine, national security, finance, and law is flourishing, this study takes a deep look at its application in policy documents. Besides providing an overview of the current state of the literature that treats these concepts, the authors implement a set of natural language processing techniques on internal bank policies. The implementation of these techniques, together with the results that derive from the experiments and expert evaluation, introduce a meta-algorithmic modelling framework for processing internal business policies. This framework relies on three natural language processing techniques, namely information extraction, automatic summarization, and automatic keyword extraction. For the reference extraction and keyword extraction tasks, the authors calculated precision, recall, and F-scores. For the former, the researchers obtained 0.99, 0.84, and 0.89; for the latter, this research obtained 0.79, 0.87, and 0.83, respectively. Finally, the summary extraction approach was positively evaluated using a qualitative assessment.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128873221","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
Recommendation and Sentiment Analysis Based on Consumer Review and Rating 基于消费者评论和评级的推荐和情感分析
Int. J. Bus. Intell. Res. Pub Date : 2020-07-01 DOI: 10.4018/ijbir.2020070102
Pin Ni, Yuming Li, Victor I. Chang
{"title":"Recommendation and Sentiment Analysis Based on Consumer Review and Rating","authors":"Pin Ni, Yuming Li, Victor I. Chang","doi":"10.4018/ijbir.2020070102","DOIUrl":"https://doi.org/10.4018/ijbir.2020070102","url":null,"abstract":"Accurate analysis and recommendation on products based on online reviews and rating data play an important role in precisely targeting suitable consumer segmentations and therefore can promote merchandise sales. This study uses a recommendation and sentiment classification model for analyzing the data of beer product based on online beer reviews and rating dataset of beer products and uses them to improve the recommendation performance of the recommendation model for different customer needs. Among them, the beer recommendation is based on rating data; 10 classification models are compared in text sentiment analysis, including the conventional machine learning models and deep learning models. Combining the two analyses can increase the credibility of the recommended beer and help increase beer sales. The experiment proves that this method can filter the products with more negative reviews in the recommendation algorithm and improve user acceptance.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121252490","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: 5
Predictive Data Mining Model for Electronic Customer Relationship Management Intelligence 面向电子客户关系管理智能的预测数据挖掘模型
Int. J. Bus. Intell. Res. Pub Date : 2020-07-01 DOI: 10.4018/ijbir.2020070101
B. Ahmed, Mohamed Larabi Ben Maâti, Mohammed Al-Sarem
{"title":"Predictive Data Mining Model for Electronic Customer Relationship Management Intelligence","authors":"B. Ahmed, Mohamed Larabi Ben Maâti, Mohammed Al-Sarem","doi":"10.4018/ijbir.2020070101","DOIUrl":"https://doi.org/10.4018/ijbir.2020070101","url":null,"abstract":"The rising adoption of e-CRM strategies in marketing and customer relationship management has necessitated to more needs especially where a specific customer segment is targeted and the services are personalized. This paper presents a distributed data mining model using access-control architecture in a bid to realize the needs for an online CRM that intends to deliver web content to a specific group of customers. This hybrid model utilizes the integration of the mobile agent and client server technologies that could easily be updated from the already existing web platforms. The model allows the management team to derive insights from the operations of the system since it focuses on e-personalization and web intelligence hence presenting a better approach for decision support among organizations. To achieve this, a software approach made of access-control functions, data mining algorithms, customer-profiling capability, dynamic web page creation, and a rule-based system is utilized.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123939522","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
Business Intelligence for Human Capital Management 人力资本管理的商业智能
Int. J. Bus. Intell. Res. Pub Date : 2020-01-01 DOI: 10.4018/ijbir.2020010103
M. Sousa, Ivo Dias
{"title":"Business Intelligence for Human Capital Management","authors":"M. Sousa, Ivo Dias","doi":"10.4018/ijbir.2020010103","DOIUrl":"https://doi.org/10.4018/ijbir.2020010103","url":null,"abstract":"This article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131275326","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: 2
Ethical Issues and Concerns in Collection of Marketing Information and Marketing Intelligence: Ethical Issue in Collection of Information 营销信息和营销情报收集中的伦理问题与关注:信息收集中的伦理问题
Int. J. Bus. Intell. Res. Pub Date : 2019-07-01 DOI: 10.4018/IJBIR.2019070102
Pratap Chandra Mandal
{"title":"Ethical Issues and Concerns in Collection of Marketing Information and Marketing Intelligence: Ethical Issue in Collection of Information","authors":"Pratap Chandra Mandal","doi":"10.4018/IJBIR.2019070102","DOIUrl":"https://doi.org/10.4018/IJBIR.2019070102","url":null,"abstract":"Companies require capturing relevant marketing information and marketing intelligence about customers to understand their requirements, formulate marketing strategies, serve them better, and develop customer relationships. Sometimes, it is difficult to collect information because individuals hesitate to share personal information due to a number of reasons. They worry about the manner in which companies use the shared information, and the safety, security, and privacy of the information. The article discusses the sensitive issues of intrusion of privacy of customers, the ethics involved, the responsibilities of marketing researchers regarding sensitive information shared by customers, the possible misuse of the shared information, the preventive measures against misuse of research findings, and the initiatives taken by companies and authorities to protect the privacy of customers. Such actions by companies will instill trust and faith in the minds of customers.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115098254","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
Exploring Big Data Footprints and Ethics: An Undergraduate Student Focus 探索大数据足迹和伦理:一个本科生的焦点
Int. J. Bus. Intell. Res. Pub Date : 2019-07-01 DOI: 10.4018/IJBIR.2019070101
Virginia M. Miori, R. Herschel
{"title":"Exploring Big Data Footprints and Ethics: An Undergraduate Student Focus","authors":"Virginia M. Miori, R. Herschel","doi":"10.4018/IJBIR.2019070101","DOIUrl":"https://doi.org/10.4018/IJBIR.2019070101","url":null,"abstract":"Big Data is collected via engagement in online activity and undergraduate students tend to be particularly heavy users of digital media. This article explores their online activity to assess their participation and usage patterns as well as their ethical perspectives. The research finds that these students have a somewhat substantial Big Data footprint since they actively engage in social media, use smart devices, shop online, use streaming services, and employ digital tools. Social connectedness necessitates the potential for their privacy being compromised and the findings suggest that introverts are more concerned about this issue then extroverts are. However, people of both types are concerned about conveying a positive image online. The majority of those surveyed primarily identified with the values expressed by the Utilitarian and Kantian ethical perspectives and less so with those expressed by Social Contract Theory and Virtue Ethics. However, study participants did not consistently ground their moral values in any one of these ethical theories.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130606358","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
Incorporating External Data Into a BI Solution at a Public Waste Management Organization 将外部数据整合到公共废物管理组织的BI解决方案中
Int. J. Bus. Intell. Res. Pub Date : 2019-07-01 DOI: 10.4018/IJBIR.2019070104
Mattias Strand, Anna Syberfeldt
{"title":"Incorporating External Data Into a BI Solution at a Public Waste Management Organization","authors":"Mattias Strand, Anna Syberfeldt","doi":"10.4018/IJBIR.2019070104","DOIUrl":"https://doi.org/10.4018/IJBIR.2019070104","url":null,"abstract":"Organizations are showing an increasing interest in incorporating external data into their business intelligence solutions. Such data allows for advanced analytics and enables more comprehensive and inclusive decision-making. However, external data incorporation is relatively unexplored in the literature, and scientifically published details on up-and-running BI solutions are very sparse. In addition, published literature concerning the incorporation of external data into BI solutions is often rather synoptic or rather old (originating from data warehouse related literature). Therefore, the authors present the results of an action case study at a public waste management organization, illustrating detailed aspects of external data incorporation related to the back-end of the solution such as data selection, source characteristics, acquisition technologies and frequencies, and integration approaches. Given that the external origin of the data poses specific problems that must be overcome in order to allow for successful incorporation initiatives, special attention was paid to such problems.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124665289","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
A Business Intelligence Project-Oriented Course: A Breast Cancer Research Case 商业智能项目导向课程:一个乳腺癌研究案例
Int. J. Bus. Intell. Res. Pub Date : 2019-07-01 DOI: 10.4018/IJBIR.2019070103
Dima Alberg
{"title":"A Business Intelligence Project-Oriented Course: A Breast Cancer Research Case","authors":"Dima Alberg","doi":"10.4018/IJBIR.2019070103","DOIUrl":"https://doi.org/10.4018/IJBIR.2019070103","url":null,"abstract":"The Business Intelligence Project-Oriented Course has been taught in the department of Industrial Engineering and Management since 2016. In this course, the students learn to build websites and business intelligence systems which enable to perform data analysis and research in order to get valuable business insights and to retrieve specific business information. The article is devoted to BI course implementation in the Department of Industrial Engineering and Management of Sami Shamoon College of Engineering (SCE).","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121045748","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
Critical Barriers to Business Intelligence Open Source Software Adoption 商业智能开源软件采用的关键障碍
Int. J. Bus. Intell. Res. Pub Date : 2019-01-01 DOI: 10.4018/IJBIR.2019010104
Placide Poba-Nzaou, Sylvestre Uwizeyemungu, M. Saada
{"title":"Critical Barriers to Business Intelligence Open Source Software Adoption","authors":"Placide Poba-Nzaou, Sylvestre Uwizeyemungu, M. Saada","doi":"10.4018/IJBIR.2019010104","DOIUrl":"https://doi.org/10.4018/IJBIR.2019010104","url":null,"abstract":"Over the past few years, managers have been hard pressed to become more data-driven, and one of the prerequisites in doing so is through the adoption of Business Intelligence (BI) tools. However (1) the adoption of BI tools remains relatively low (2) the acquisition costs of proprietary BI tools are relatively high and (3) the level of satisfaction with these BI tools remain low. Given the potential of open source BI (OSBI) tools, there is a need for analyzing barriers that prevent organizations from adopting OSBI. Drawing a systematic review and a Qualitative Survey of BI Experts, this study proposes a framework that categorizes and structures 23 barriers to OSBI adoption by organizations including 4 that were identified by BI Experts but not explicitly found in the literature. This paper contributes to OSS and Information Systems (IS) research literature on BI adoption in general and provides specific insights to practitioners.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"514 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380757","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: 9
3PM Revisited: Dissecting the Three Phases Method for Outsourcing Knowledge Discovery 重访:剖析外包知识发现的三阶段方法
Int. J. Bus. Intell. Res. Pub Date : 2019-01-01 DOI: 10.4018/IJBIR.2019010105
Richard Ooms, M. Spruit, Sietse Overbeek
{"title":"3PM Revisited: Dissecting the Three Phases Method for Outsourcing Knowledge Discovery","authors":"Richard Ooms, M. Spruit, Sietse Overbeek","doi":"10.4018/IJBIR.2019010105","DOIUrl":"https://doi.org/10.4018/IJBIR.2019010105","url":null,"abstract":"This article revisits the Three Phases Method (3PM) which was published in 2010 in this journal. The 3PM is aimed at outsourcing data mining to improve corporate performance. This follow-up work aims to provide more insight into the 3PM by describing every phase of the method in detail as Meta-Algorithmic Models, through descriptions of the activities and concepts of the method and visualising the process and deliverables in Process Deliverable Diagram notation to simplify adoption of the method by practitioners.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129021452","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
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