Log in

Relevant bibliographies by topics / Business intelligence,data mining,utility / Journal articles

To see the other types of publications on this topic, follow the link: Business intelligence,data mining,utility.

Journal articles on the topic 'Business intelligence,data mining,utility'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Business intelligence,data mining,utility.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Rao, M. Venkata Krishna, Ch Suresh, K. Kamakshaiah, and M. Ravikanth. "Prototype Analysis for Business Intelligence Utilization in Data Mining Analysis." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (2017): 30. http://dx.doi.org/10.23956/ijarcsse.v7i7.93.

Full text

Abstract:

Tremendous increase of high availability of more disparate data sources than ever before have raised difficulties in simplifying frequent utility report across multiple transaction systems apart from an integration of large historical data. It is main focusing concept in data exploration with high transactional data systems in real time data processing. This problem mainly occurs in data warehouses and other data storage proceedings in Business Intelligence (BI) for knowledge management and business resource planning. In this phenomenon, BI consists software construction of data warehouse quer

APA, Harvard, Vancouver, ISO, and other styles

2

Altuntas, Serkan. "A novel approach based on utility mining for store layout: a case study in a supermarket." Industrial Management & Data Systems 117, no. 2 (2017): 304–19. http://dx.doi.org/10.1108/imds-01-2016-0040.

Full text

Abstract:

Purpose The purpose of this paper is to propose a novel approach based on utility mining for store layout. Design/methodology/approach A utility mining-based data mining algorithm is utilized in this paper. Findings A real-life case study in a supermarket is conducted to illustrate the proposed approach. The findings show that the proposed approach can be used easily and efficiently to arrange store layout. Research limitations/implications There are two limitations to this study. First, space allocation to each product family is not considered. Second, product placement in each product family

APA, Harvard, Vancouver, ISO, and other styles

3

Cheng, Haodong, Meng Han, Ni Zhang, Xiaojuan Li, and Le Wang. "A Survey of incremental high-utility pattern mining based on storage structure." Journal of Intelligent & Fuzzy Systems 41, no. 1 (2021): 841–66. http://dx.doi.org/10.3233/jifs-202745.

Full text

Abstract:

Traditional association rule mining has been widely studied, but this is not applicable to practical applications that must consider factors such as the unit profit of the item and the purchase quantity. High-utility itemset mining (HUIM) aims to find high-utility patterns by considering the number of items purchased and the unit profit. However, most high-utility itemset mining algorithms are designed for static databases. In real-world applications (such as market analysis and business decisions), databases are usually updated by inserting new data dynamically. Some researchers have proposed

APA, Harvard, Vancouver, ISO, and other styles

4

Thompson, M. W., J. Hiestermann, and L. Moyo. "PROVING THE CAPABILITY FOR LARGE SCALE REGIONAL LAND-COVER DATA PRODUCTION BY SELF-FUNDED COMMERCIAL OPERATORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W2 (November 16, 2017): 209–12. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w2-209-2017.

Full text

Abstract:

For service providers developing commercial value-added data content based on remote sensing technologies, the focus is to typically create commercially appropriate geospatial information which has downstream business value. The primary aim being to link locational intelligence with business intelligence in order to better make informed decisions. From a geospatial perspective this locational information must be relevant, informative, and most importantly current; with the ability to maintain the information timeously into the future for change detection purposes. Aligned with this, GeoTerraIm

APA, Harvard, Vancouver, ISO, and other styles

5

Jamalpur, Bhavana, and S. S. V. N. Sharma. "Data Mining and Business Intelligence Dashboards." International Journal of Asian Business and Information Management 3, no. 4 (2012): 39–44. http://dx.doi.org/10.4018/jabim.2012100104.

Full text

Abstract:

Today, the most successful companies are those that can respond quickly and flexibly to market changes and opportunities. A detailed understanding and knowledge is required to analyze the business environment at different levels. This can be achieved by implementing value added information throughout the organization. There has been an increased demand in the development of IT that performs data manipulation operations to report and analyze the data. While sifting through all that data, organizing it, and then using it to make the business run more profitably has become a bigger challenge. Dec

APA, Harvard, Vancouver, ISO, and other styles

6

Bayer, Harun, Mustafa Aksogan, Enes Celik, and Adil Kondiloglu. "Big data mining and business intelligence trends." Journal of Asian Business Strategy 7, no. 1 (2017): 23–33. http://dx.doi.org/10.18488/journal.1006/2017.7.1/1006.1.23.33.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Boland, Giles W., James H. Thrall, and Richard Duszak. "Business Intelligence, Data Mining, and Future Trends." Journal of the American College of Radiology 12, no. 1 (2015): 9–11. http://dx.doi.org/10.1016/j.jacr.2014.10.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Post, Gerald V., and Albert Kagan. "Business Intelligence." International Journal of Business Intelligence Research 3, no. 3 (2012): 16–28. http://dx.doi.org/10.4018/jbir.2012070102.

Full text

Abstract:

Data mining and business intelligence tools have been adding features and gaining uses, and statistical tools developed for data mining tasks often require advanced knowledge and training to apply. Development of these selected tools requires tradeoffs in ease of use and power. This study asks users to evaluate the various tools and attributes to identify the relative value of the various components and provide direction for improvements and new tools. Evaluating multi-attribute software is a challenging task, and this study provides a method of evaluating the data and analyzing tradeoffs. A s

APA, Harvard, Vancouver, ISO, and other styles

9

Azevedo, Ana, and Manuel Filipe Santos. "QMBE: A data mining language for business intelligence." International Journal Of Data Mining And Emerging Technologies 1, no. 1 (2011): 22. http://dx.doi.org/10.5958/j.2249-3212.1.1.4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

C. H. Chen, Jason. "Research on Business Intelligence with Data Mining Applications." International Journal of Business and Economics Research 6, no. 2 (2017): 19. http://dx.doi.org/10.11648/j.ijber.20170602.11.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Abraham, Ajith. "Business Intelligence from Web Usage Mining." Journal of Information & Knowledge Management 02, no. 04 (2003): 375–90. http://dx.doi.org/10.1142/s0219649203000565.

Full text

Abstract:

The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to choose from several alternatives, the business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personal

APA, Harvard, Vancouver, ISO, and other styles

12

Mishra, Devendra Kumar. "CHALLENGES IN TEXT MINING FOR BUSINESS INTELLIGENCE." International Journal of Engineering Technologies and Management Research 5, no. 2 (2020): 301–4. http://dx.doi.org/10.29121/ijetmr.v5.i2.2018.660.

Full text

Abstract:

Today is the era of internet; the internet represents a big space where large amounts of data are added every day. This huge amount of digital data and interconnection exploding data. Big Data mining have the capability to retrieving useful information in large datasets or streams of data. Analysis can also be done in a distributed environment. The framework needed for analysis to this large amount of data must support statistical analysis and data mining. The framework should be design in such a way so that big data and traditional data can be combined, so results that come analyzing new data

APA, Harvard, Vancouver, ISO, and other styles

13

Bose, Ranjit. "Discovering Business Intelligence from the Subjective Web Data." International Journal of Business Intelligence Research 2, no. 4 (2011): 1–16. http://dx.doi.org/10.4018/jbir.2011100101.

Full text

Abstract:

The online word-of-mouth behavior that exists today in the Web represents new and measurable sources of information. The automated discovery or mining of consumer opinions from these sources is of great importance for marketing intelligence and product benchmarking. Techniques are now being developed to effectively and easily mine the consumer opinions from the Web data and to timely deliver them to companies and individual consumers. This study investigates this emerging field named ‘opinion mining’ in terms of what it is, what it can do, and how it could be used effectively for business inte

APA, Harvard, Vancouver, ISO, and other styles

14

KIM, JENNIFER, DAVID A. OSTROWSKI, HIROSHI YAMAGUCHI, and PHILLIP C. Y. SHEU. "SEMANTIC COMPUTING AND BUSINESS INTELLIGENCE." International Journal of Semantic Computing 07, no. 01 (2013): 87–117. http://dx.doi.org/10.1142/s1793351x13500013.

Full text

Abstract:

With rapidly expanding data collections becoming increasingly available, the application of Semantic Computing has become imperative to leverage this resource for industrial applications. This paper presents a survey of Semantic Computing in the area of Business Intelligence. We examine semantic analytical techniques and tools as applied for prediction analysis and decision support. We also define the role of Semantic Computing as applied in the context of Data Mining, Text Mining and Big Data Analytics. Additionally, we describe how business data is queried with Structured Natural Language as

APA, Harvard, Vancouver, ISO, and other styles

15

Gopala Krishna, yosyula Satyavenu, G. V. S. CH S. L. V. Prasad, Shaik Shamshad Begam, Konda Sreenu, and Donavalli Venkata Vidya Deepthi. "Friendly Approach on Business Intelligence Using Web Data Mining." International Journal Of Recent Advances in Engineering & Technology 8, no. 6 (2020): 1–7. http://dx.doi.org/10.46564/ijraet.2020.v08i06.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Holmes, Sarah. "Data Mining and Business Intelligence: A Guide to Productivity." Government Information Quarterly 20, no. 4 (2003): 423–26. http://dx.doi.org/10.1016/j.giq.2003.07.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Poovammal, E., and M. Ponnavaikk. "Utility Independent Privacy Preserving Data Mining on Vertically Partitioned Data." Journal of Computer Science 5, no. 9 (2009): 666–73. http://dx.doi.org/10.3844/jcssp.2009.666.673.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Kocakoç, Ipek Deveci, and Sabri Erdem. "Business Intelligence Applications in Retail Business: OLAP, Data Mining & Reporting Services." Journal of Information & Knowledge Management 09, no. 02 (2010): 171–81. http://dx.doi.org/10.1142/s0219649210002541.

Full text

Abstract:

As a result of today's competitive business environment, companies have been trying to improve the utilization of funds effectively in their budgets for information technology investments. These companies retrieve more information with the same set of resources by means of business intelligence methods. According to Rubin (Chabrow, 2004) IT budgets are not simply declining or levelling off, rather, companies are shifting from a pure cost-cut mode to a model that emphasises agility and efficiency. Tremendous daily growth of the company data requires more funds and investment for establishing th

APA, Harvard, Vancouver, ISO, and other styles

19

Chubukova, Ponomarenko, and Nedbailo. "Using data mining to process business data." Problems of Innovation and Investment Development, no. 23 (April 10, 2020): 71–77. http://dx.doi.org/10.33813/2224-1213.23.2020.8.

Full text

Abstract:

The subject of the research is the approach to the possibility of applying data mining methods in the framework of business analytics in order to optimize the adoption of management decisions by the company.The purpose of writing this article is to study of data mining methods features use of primary data, which act as a valuable resource of the company, which can be used to ensure competitive- ness in a particular market. Methodology. The research methodology is system- structural and comparative analyzes (to study the approaches of data mining data for the complex analysis of first data); mo

APA, Harvard, Vancouver, ISO, and other styles

20

Wang, Jun-Zhe, Yi-Cheng Chen, Wen-Yueh Shih, Lin Yang, Yu-Shao Liu, and Jiun-Long Huang. "Mining High-utility Temporal Patterns on Time Interval–based Data." ACM Transactions on Intelligent Systems and Technology 11, no. 4 (2020): 1–31. http://dx.doi.org/10.1145/3391230.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Kasemsap, Kijpokin. "Multifaceted Applications of Data Mining, Business Intelligence, and Knowledge Management." International Journal of Social and Organizational Dynamics in IT 5, no. 1 (2016): 57–69. http://dx.doi.org/10.4018/ijsodit.2016010104.

Full text

Abstract:

This article reviews the literature in the search for the multifaceted applications of data mining (DM), business intelligence (BI), and knowledge management (KM). The literature review highlights the overviews of DM, BI, and KM; the practical applications of DM, BI, and KM; and the prospects of DM, BI, and KM in terms of marketing, business, human resources, and manufacturing. DM plays a key role in organizing huge amount of data and condensing it into valuable information. BI involves the delivery and integration of relevant and useful business information in an organization. KM allows compa

APA, Harvard, Vancouver, ISO, and other styles

22

Bhanap, Smita, and Dr Seema Kawthekar. "Data Mining for Business Intelligence in Social Network: A survey." IARJSET 2, no. 12 (2015): 129–31. http://dx.doi.org/10.17148/iarjset.2015.21223.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Rashid Al-Azmi, Abdul-Aziz. "Data, Text and Web Mining for Business Intelligence : A Survey." International Journal of Data Mining & Knowledge Management Process 3, no. 2 (2013): 1–21. http://dx.doi.org/10.5121/ijdkp.2013.3201.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Chinnam, Siva Koteswara Rao, AV Krishna Prasad, B. Premamayudu, Moka Vinod, and Hye-Jin Kim. "Acquiring Business Intelligence through Temporal Mining of Smart Meter Data." International Journal of Software Engineering and Its Applications 10, no. 9 (2016): 141–48. http://dx.doi.org/10.14257/ijseia.2016.10.9.12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Singh, Jitendra. "Business Intelligence: Achieving Fineness through Data, Text and Web Mining." International Journal of Computer Applications 128, no. 12 (2015): 46–52. http://dx.doi.org/10.5120/ijca2015906691.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Mena, Jesus. "Machine-learning the business: Using data mining for competitive intelligence." Competitive Intelligence Review 7, no. 4 (1996): 18–25. http://dx.doi.org/10.1002/cir.3880070406.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Lawrence, Kenneth D., Dinesh R. Pai, Ronald Klimberg, and Sheila M. Lawrence. "Enterprise Information System and Data Mining." International Journal of Business Intelligence Research 1, no. 3 (2010): 34–41. http://dx.doi.org/10.4018/jbir.2010070103.

Full text

Abstract:

The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data min

APA, Harvard, Vancouver, ISO, and other styles

28

Azevedo, Ana, and Manuel Filipe Santos. "Closing the Gap between Data Mining and Business Users of Business Intelligence Systems." International Journal of Business Intelligence Research 3, no. 4 (2012): 14–53. http://dx.doi.org/10.4018/jbir.2012100102.

Full text

Abstract:

Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI too

APA, Harvard, Vancouver, ISO, and other styles

29

Gan, Wensheng, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, and Philip S. Yu. "ProUM: Projection-based utility mining on sequence data." Information Sciences 513 (March 2020): 222–40. http://dx.doi.org/10.1016/j.ins.2019.10.033.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Kopčeková, Alena, Michal Kopček, and Pavol Tanuška. "BUSINESS INTELLIGENCE IN PROCESS CONTROL." Research Papers Faculty of Materials Science and Technology Slovak University of Technology 21, no. 33 (2013): 43–53. http://dx.doi.org/10.2478/rput-2013-0039.

Full text

Abstract:

Abstract The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of sep

APA, Harvard, Vancouver, ISO, and other styles

31

Wang, Hai, and Shouhong Wang. "A knowledge management approach to data mining process for business intelligence." Industrial Management & Data Systems 108, no. 5 (2008): 622–34. http://dx.doi.org/10.1108/02635570810876750.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Qiu, Ling, Yingjiu Li, and Xintao Wu. "Protecting business intelligence and customer privacy while outsourcing data mining tasks." Knowledge and Information Systems 17, no. 1 (2007): 99–120. http://dx.doi.org/10.1007/s10115-007-0113-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Collier, Scott, Dana Edberg, and David Croasdell. "Retreading Tire Management with Business Intelligence." International Journal of Business Intelligence Research 3, no. 4 (2012): 54–73. http://dx.doi.org/10.4018/jbir.2012100103.

Full text

Abstract:

Justifying the development of a business intelligence system is challenging when the primary beneficiaries of the system are internal to the company responsible for that development; it is even harder to justify when the system is designed to produce a new service that is radically different than current in-house manufactured products. This case explores the possibility of a tire manufacturer developing a business intelligence system to help their customers manage very large heavy equipment tires within the mining industry. These tires are one of the biggest expenses for mining companies and t

APA, Harvard, Vancouver, ISO, and other styles

34

Siswono, Siswono. "Peran Business Intelligence dalam Solusi Bisnis." ComTech: Computer, Mathematics and Engineering Applications 4, no. 2 (2013): 812. http://dx.doi.org/10.21512/comtech.v4i2.2518.

Full text

Abstract:

The purpose of this study is to give examine the use of Business Intelligence as a critical technology solutions in the decision making by management. Business Intelligence application is able to address the needs of organizations in improving problem analytical skills encountered in making decisions with the ability tocollect, store, analyze and provide access to data, as well as dovarious activities such as statistical analysis, forecasting, and data mining.

APA, Harvard, Vancouver, ISO, and other styles

35

Selene Xia, Belle, and Peng Gong. "Review of business intelligence through data analysis." Benchmarking: An International Journal 21, no. 2 (2014): 300–311. http://dx.doi.org/10.1108/bij-08-2012-0050.

Full text

Abstract:

Purpose – The purpose of this paper is to explore the role of business intelligence (BI) in a consulting company. The authors propose to analyze quality through data analysis and efficiency under different business contexts. The best processes and tools in data mining are also explored. Design/methodology/approach – Management perspectives of data analysis from Florilla Consulting Company are collected using an inductive research approach. Based on a large sample of qualitative data, cost-and-benefit analysis is used to assess the BI technologies as a strategic necessity to Florilla Consulting

APA, Harvard, Vancouver, ISO, and other styles

36

Kim, Heonho, Unil Yun, Yoonji Baek, et al. "Damped sliding based utility oriented pattern mining over stream data." Knowledge-Based Systems 213 (February 2021): 106653. http://dx.doi.org/10.1016/j.knosys.2020.106653.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Ryang, Heungmo, and Unil Yun. "High utility pattern mining over data streams with sliding window technique." Expert Systems with Applications 57 (September 2016): 214–31. http://dx.doi.org/10.1016/j.eswa.2016.03.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Zihayat, Morteza, and Aijun An. "Mining top-k high utility patterns over data streams." Information Sciences 285 (November 2014): 138–61. http://dx.doi.org/10.1016/j.ins.2014.01.045.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Zhu, Jian Xin. "Arithmetic Research on Data Mining Technology and Associative Rules Mining." Applied Mechanics and Materials 556-562 (May 2014): 3949–51. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3949.

Full text

Abstract:

Data mining is a technique that aims to analyze and understand large source data reveal knowledge hidden in the data. It has been viewed as an important evolution in information processing. Why there have been more attentions to it from researchers or businessmen is due to the wide availability of huge amounts of data and imminent needs for turning such data into valuable information. During the past decade or over, the concepts and techniques on data mining have been presented, and some of them have been discussed in higher levels for the last few years. Data mining involves an integration of

APA, Harvard, Vancouver, ISO, and other styles

40

Kohavi, Ron, Dan Sommerfield, and James Dougherty. "Data Mining Using $\mathcal{MLC}++$ a Machine Learning Library in C++." International Journal on Artificial Intelligence Tools 06, no. 04 (1997): 537–66. http://dx.doi.org/10.1142/s021821309700027x.

Full text

Abstract:

Data mining algorithms including maching learning, statistical analysis, and pattern recognition techniques can greatly improve our understanding of data warehouses that are now becoming more widespread. In this paper, we focus on classification algorithms and review the need for multiple classification algorithms. We describe a system called [Formula: see text], which was designed to help choose the appropriate classification algorithm for a given dataset by making it easy to compare the utility of different algorithms on a specific dataset of interest. [Formula: see text] not only provides a

APA, Harvard, Vancouver, ISO, and other styles

41

Sjarif, Nilam Nur Amir, Nurulhuda Firdaus Mohd Azmi, Siti Sophiayati Yuhaniz, and Doris Hooi Ten Wong. "A Review of Market Basket Analysis on Business Intelligence and Data Mining." International Journal of Business Intelligence and Data Mining 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijbidm.2021.10024452.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Sjarif, Nilam Nur Amir, Nurulhuda Firdaus Mohd Azmi, Siti Sophiayati Yuhaniz, and Doris Hooi Ten Wong. "A review of market basket analysis on business intelligence and data mining." International Journal of Business Intelligence and Data Mining 18, no. 3 (2021): 383. http://dx.doi.org/10.1504/ijbidm.2021.114475.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Peng, Zhen Long, and You Lan Huang. "Research on E-Commerce Intelligence Based on IOT and Big Data." Applied Mechanics and Materials 496-500 (January 2014): 1889–94. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1889.

Full text

Abstract:

The computer technology together with network technology, communication technology have built a complex basic platform of computer network and a middle platform network which relate human to human, human to machine and machine to machine. Hundreds of millions of GB data generated from these platforms is stored in Cloud Computing Center. Based on this background, the paper analyzes the historical inevitability of IOT and big data, expounds the concept, process and methods of big data mining, and analyzes the natural relationship between big data mining and business intelligence. Through the dee

APA, Harvard, Vancouver, ISO, and other styles

44

Gottfried, Anne, Caroline Hartmann, and Donald Yates. "Mining Open Government Data for Business Intelligence Using Data Visualization: A Two-Industry Case Study." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 4 (2021): 1042–65. http://dx.doi.org/10.3390/jtaer16040059.

Full text

Abstract:

The business intelligence (BI) market has grown at a tremendous rate in the past decade due to technological advancements, big data and the availability of open source content. Despite this growth, the use of open government data (OGD) as a source of information is very limited among the private sector due to a lack of knowledge as to its benefits. Scant evidence on the use of OGD by private organizations suggests that it can lead to the creation of innovative ideas as well as assist in making better informed decisions. Given the benefits but lack of use of OGD to generate business intelligenc

APA, Harvard, Vancouver, ISO, and other styles

45

Bouaoula, Wassila, Farid Belgoum, Arifusalam Shaikh, Mohammed Taleb-Berrouane, and Carlos Bazan. "The impact of business intelligence through knowledge management." Business Information Review 36, no. 3 (2019): 130–40. http://dx.doi.org/10.1177/0266382119868082.

Full text

Abstract:

Competition among companies has intensified during the last few decades and hence monitoring the organization’s environment has become a priority. Monitoring the internal and external environments involves collecting, retrieving, managing, and disseminating large volumes of data and information. Companies are able to handle these complex tasks very efficiently through knowledge management (KM). A valuable tool of KM is business intelligence (BI), that is, the set of coordinated actions of research, treatment, and distribution of information that can help support the company’s competitiveness.

APA, Harvard, Vancouver, ISO, and other styles

46

Feng, Lin, Le Wang, and Bo Jin. "UT-Tree: Efficient mining of high utility itemsets from data streams." Intelligent Data Analysis 17, no. 4 (2013): 585–602. http://dx.doi.org/10.3233/ida-130595.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Yun, Unil, Donggyu Kim, Eunchul Yoon, and Hamido Fujita. "Damped window based high average utility pattern mining over data streams." Knowledge-Based Systems 144 (March 2018): 188–205. http://dx.doi.org/10.1016/j.knosys.2017.12.029.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Villegas-Ch, William, Xavier Palacios-Pacheco, and Sergio Luján-Mora. "A Business Intelligence Framework for Analyzing Educational Data." Sustainability 12, no. 14 (2020): 5745. http://dx.doi.org/10.3390/su12145745.

Full text

Abstract:

Currently, universities are being forced to change the paradigms of education, where knowledge is mainly based on the experience of the teacher. This change includes the development of quality education focused on students’ learning. These factors have forced universities to look for a solution that allows them to extract data from different information systems and convert them into the knowledge necessary to make decisions that improve learning outcomes. The information systems administered by the universities store a large volume of data on the socioeconomic and academic variables of the stu

APA, Harvard, Vancouver, ISO, and other styles

49

HILDERMAN, ROBERT J., HOWARD J. HAMILTON, COLIN L. CARTER, and NICK CERCONE. "MINING ASSOCIATION RULES FROM MARKET BASKET DATA USING SHARE MEASURES AND CHARACTERIZED ITEMSETS." International Journal on Artificial Intelligence Tools 07, no. 02 (1998): 189–220. http://dx.doi.org/10.1142/s0218213098000111.

Full text

Abstract:

We propose the share-confidence framework for knowledge discovery from databases which addresses the problem of mining characterized association rules from market basket data (i.e., itemsets). Our goal is to not only discover the buying patterns of customers, but also to discover customer profiles by partitioning customers into distinct classes. We present a new algorithm for classifying itemsets based upon characteristic attributes extracted from census or lifestyle data. Our algorithm combines the A priori algorithm for discovering association rules between items in large databases, and the

APA, Harvard, Vancouver, ISO, and other styles

50

ElSeddawy, Ahmed, and Mohamed Hegazy. "A PROPOSED MINING APPROACH BASED ON BUSINESS INTELLIGENCE BY USING DATA SCIENCES TECHNIQUES." International Journal of Intelligent Computing and Information Sciences 21, no. 1 (2021): 132–48. http://dx.doi.org/10.21608/ijicis.2021.57633.1052.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!