دانلود و نمایش مقالات مرتبط با Business Intelligence::صفحه 1
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نتیجه جستجو - Business Intelligence

تعداد مقالات یافته شده: 78
ردیف عنوان نوع
1 چارچوب حاکمیتی هوش تجاری در دانشگاه: مطالعه موردی دانشگاه دو لا کاستا
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 25
دانشگاه ها و شرکت ها دارای فرآیندهای تصمیم گیری هستند که به آنها اجازه می دهد تا به اهداف سازمانی دست پیدا کنند. در حال حاضر، تحلیل داده ها نقش مهمی در ایجاد دانش، بدست آوردن الگوهای مهم و پیش بینی استراتژی ها ایفا می کنند.این مقاله طراحی چارچوب نظارت هوش تجاری را برای دانشگاه دو لا کاستا ارائه کرده است که به آسانی برای سازمان های دیگر هم قابل استفاده است. برای این منظور، تشخیص انجام شده به منظور شناسایی میزان بلوغ تحلیلی انجام شده است. با استفاده از این چشم انداز، مدلی برای تقویت فرهنگ سازمانی ، زیر ساختارها، مدیریت داده، تحلیل داده و نظارت ارائه شده است.این مدل در بر گیرنده تعریف چارچوب نظارتی، اصول هدایت کننده، استراتژی ها، نهادهای تصمیم گیرنده و نقش ها می باشد. بنابراین، این چارچوب برای استفاده از کنترل های موثر جهت اطمینان از موفقیت پروژه های هوش تجاری و دست یابی به اهداف برنامه توسعه همراه با چسم انداز تحلیلی سازمان ارائه شده است.
کلمات کلیدی: هوش تجاری | نظارت | دانشگاه | تحلیل | تصمیم گیری
مقاله ترجمه شده
2 Intelligent decision-making of online shopping behavior based on internet of things
تصمیم گیری هوشمندانه از رفتار خرید آنلاین مبتنی بر اینترنت اشیا-2020
The development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different kinds of information sources have improved the consumers’ online shopping performance and make it possible to realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers online reviews search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human contact degrees of recycled water reuses with grip force test was measured. According to the human contact degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation time participants spent on the areas of interest (AOIs), we justify that consumers online reviews search behavior is substantially affected by human contact degrees of recycled products. It was found that consumers rely on safety perception reviews when buying high contact goods.
Keywords: Online reviews search behavior | Recycled products | Grip force sensor | Eye-tracking sensor | Internet of Things (IoT)
مقاله انگلیسی
3 Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های پیچیده مهندسی: از ردپای دیجیتال در حال تحول چه می توانیم یاد بگیریم؟-2020
The challenges of managing large complex engineering projects, such as those involving the design of infrastructure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of todays projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management information relating to them can be provided, and done so in a cost eff ;ective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.
Keywords: Big Data | Project Management | Business Intelligence | Knowledge Workers
مقاله انگلیسی
4 Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های مهندسی پیچیده: از رد پای دیجیتال در حال تکامل چه می توان یاد گرفت؟-2020
The challenges of managing large complex engineering projects, such as those involving the design of infra- structure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of todays projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management in- formation relating to them can be provided, and done so in a cost effective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.
Keywords: Big Data | Project Management | Business Intelligence | Knowledge Workers
مقاله انگلیسی
5 A deep learning methodology for automatic extraction and discovery of technical intelligence
یک روش یادگیری عمیق برای استخراج خودکار و کشف هوش فنی-2019
It is imperative and arduous to acquire product and business intelligence of global technical market. In this paper, a deep learning methodology is proposed to automatically extract and discover vital technical information from large-scale news dataset. More specifically, six kinds of technical elements are first defined to provide the concrete syntax information. Next, the CRF-BiLSTM approach is used to automatically extract technical entities, in which a conditional random field (CRF) layer is added on top of bidirectional long short-term memory (BiLSTM) layer. Then, three indicators including timeliness, influence and innovativeness are designed to evaluate the value of intelligence comprehensively. Finally, as a case study, technical news on three militaryrelated websites is utilized to illustrate the efficiency and effectiveness of the foregoing methodology with the result of 80.82 (F-score) in comparison to four other models. In more detail, data on unmanned systems are extracted to summarize the state-of-the-art, and track up-to-the-minute innovations and developments in this field.
Keywords: Technical intelligence | CRF-BiLSTM | Deep learning | Intelligence monitoring
مقاله انگلیسی
6 Big Data Architecture for Water Resources Management: A Systematic Mapping Study
معماری داده های بزرگ برای مدیریت منابع آب: یک مطالعه نقشه برداری سیستماتیک-2018
The combination of growth in demand for water, climate and hydrological gap, pushed the decision makers and water resource managers to search strategies for effective management of water resources. In this sense, the new generation of Business Intelligence technologies, known as Big Data, allows mass processing of complex data on a large scale. In recent years, several solutions have been proposed for management issues of water resources in general using Big Data. In this paper we provide an overview of proposed architectures features, serving as a starting point for further research
Keywords: Big Data; architecture; water; resources ;systematic mapping
مقاله انگلیسی
7 Big Data Compliance for Innovative Clinical Models
مطابقت داده های بزرگ برای مدل های بالینی نوآورانه-2018
In the healthcare sector, information is the most important aspect, and the human body in particular is the major source of data production: as a result, the new challenge for world healthcare is to take advantage of these huge amounts of data de-structured among themselves. In order to benefit from this advantage, technology offers a solution called Big Data Analysis that allows the management of large amounts of data of a different nature and coming from different sources of a “computerized” healthcare, as there are considerable changes made by the input of digital technology in all major health areas. Clinical intelligence consists of all the analytical methods made possible through the use of computer tools, in all the processes and disciplines of extraction and transformation of crude clinical data into significant insights, new purposes and knowledge that provide greater clinical efficacy and best health pronouncements about past performance, current operations and future events. It can therefore be stated that clinical intelligence, through patient data analysis, will become a standard operating procedure that will address all aspects of care delivery. The purpose of this paper is to present clinical intelligence approaches through Data Mining and Process Mining, showing the differences between these two methodologies applied to perform “real process” extraction to be compared with the procedures in the corporate compliance template (the so called “Model 231”) by “conformance checking”.
Keywords: Big Data healthcare , Clinical intelligence , Data Mining , Process Mining , Business intelligence
مقاله انگلیسی
8 A service-oriented framework for collating retail intelligence
یک چارچوب سرویس گرا برای جمع آوری اطلاعات خرده فروشی-2018
This paper presents a case study that explores the impact of a software development project on a Small to Medium Enterprise in the United Kingdom as a means of delivering improved understanding of data in the retail sector. In this paper, the link between the actions undertaken by management in retail and the relationship with the environment provided by IT systems is considered. Many retailers in the United Kingdom make use of sensor devices to understand the behaviour of their customers. As retail outlets grow over a period of time, the diversity of sensor devices may change as new devices are installed. Equally, outlets that are operated within retail groups will collect and store data locally. As a consequence, management within the retail sector face a number of challenges to understand the operation of individual outlets and the holistic performance of retail chains. As a result, both the IT systems and also the working practices employed to complete the day to day tasks essential to meet the needs of a retailer’s customers rapidly become unfit for purpose. The case study considered in this paper reviews the requisite practices adopted by a service provider in the business intelligence sector, and the positive impact that the company realised through the re-engineering of both IT systems and business workflows. This paper demonstrates the efficacy of applying current software engineering methods to the redesign of IT-based business practices as opposed to more traditional approaches.
Keywords: Distributed applications ، Software architectures ، Web-based service
مقاله انگلیسی
9 Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach
معادن حداکثر الگوهای مکرر در پایگاه داده های معاملاتی و جریان داده های پویا: رویکرد مبتنی بر جرقه-2018
Mining maximal frequent patterns (MFPs) in transactional databases (TDBs) and dynamic data streams (DDSs) is substantially important for business intelligence. MFPs, as the smallest set of patterns, help to reveal customers’ purchase rules and market basket analysis (MBA). Although, numerous studies have been carried out in this area, most of them extend the main-memory based Apriori or FP-growth algorithms. Therefore, these approaches are not only unscalable but also lack parallelism. Consequently, ever increasing big data sources requirements cannot be met. In addition, mining performance in some existing approaches degrade drastically due to the presence of null transactions. We, therefore, proposed an efficient way to mining MFPs with Apache Spark to overcome these issues. For the faster computation and efficient utilization of memory, we utilized a prime number based data transformation technique, in which values of individual transaction have been preserved. After removing null transactions and infrequent items, the resulting transformed dataset becomes denser compared to the original distributions. We tested our proposed algorithms in both real static TDBs and DDSs. Experimental results and performance analysis show that our approach is efficient and scalable to large dataset sizes.
Keywords: Big data ، Transactional databases ، Dynamic data streams ، Null transactions ، Prime number theory ، Data mining ، Apache Spark ، Maximal frequent patterns
مقاله انگلیسی
10 Semantic privacy-preserving framework for electronic health record linkage
چارچوب حفظ محتواي معنايي براي پيوند رکورد سلامت الکترونيک-2018
The combination of digitized health information and web-based technologies offers many possibilities for data analysis and business intelligence. In the healthcare and biomedical research domain, applications depending on electronic health records (EHRs) identify pri vacy preservation as a major concern. Existing solutions cannot always satisfy the evolving research demands such as linking patient records across organizational boundaries due to the potential for patient re-identification. In this work, we show how semantic methods can be applied to support the formulation and enforcement of access control policy whilst ensuring that privacy leakage can be detected and prevented. The work is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN – www.addn.org.au), the national paediatric type-1 diabetes data registry, and the Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) platform that supports Australia-wide access to urban and built environment data sets. We demon strate that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, finer-grained access control encompassing data risk disclosure mechanisms can be supported. We discuss the contributions that can be made using this approach to socio-economic development and political management within business sys tems, and especially those situations where secure data access and data linkage is required.
مقاله انگلیسی
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