Search or ask a question

What are benefits of KDD in data mining?

Knowledge extraction

Cluster sampling

Best insight from top research papers

Knowledge Discovery in Databases (KDD) plays a crucial role in data mining by enabling the extraction of valuable insights from vast and complex datasets. KDD involves identifying meaningful patterns, predicting trends, and analyzing data to derive actionable knowledge . The benefits of KDD in data mining include enhancing decision-making processes, improving business strategies, understanding consumer behaviors, and aiding in various sectors like healthcare and finance . By utilizing KDD techniques, organizations can transform raw data into valuable information, leading to improved efficiency, better resource allocation, and enhanced competitiveness in the market. Additionally, KDD helps in uncovering hidden patterns, relationships, and trends within data, ultimately facilitating informed decision-making and strategic planning in diverse fields .

Answers from top 4 papers

PDF

Open Access

More filters

Papers (4)	Insight
Proceedings Article•DOI Data Mining in Education: Discussing Knowledge Discovery in Database (KDD) with Cluster Associative Study Abdulkadir Abdulahi Hasan, Huan Fang - Show less +1 more 28 May 2021 1 Citations	KDD in data mining offers enhanced knowledge extraction from large datasets, aids in predicting future behaviors, and facilitates strategic management tool development through modern techniques like cluster sampling.
Book Chapter•DOI Knowledge Discovery and Intelligent Data Mining 15 Dec 2022	KDD in data mining offers benefits like identifying patterns, predicting trends, and extracting valuable insights from large datasets, aiding in staying updated on consumer behaviors and demands.
Proceedings Article Issues and Challenges of KDD Model for Distributed Data Mining Techniques and Architecture Shafiqul Abidin 15 Mar 2023	KDD in data mining helps transform large data into actionable insights used in various fields like science, commerce, and health for tasks such as market analysis and client retention.
Proceedings Article•DOI An Optimized KDD Process for Collecting and Processing Ingested and Streaming Healthcare Data Argyro Mavrogiorgou, Athanasios Kiourtis, George Manias, Dimosthenis Kyriazis - Show less +3 more 24 May 2021 6 Citations	KDD in data mining helps extract valuable insights from vast healthcare data, aiding in pattern recognition and relationship analysis for improved decision-making and interpretation in healthcare organizations.

My columns

Related Questions

What are the benefits of vitamin d?5 answersVitamin D offers a wide array of benefits across various aspects of health. It plays a crucial role in maintaining calcium homeostasis, impacting bone health, and reducing the risk of cardiovascular diseases, metabolic syndrome, and type 2 diabetes. Additionally, vitamin D supplementation has shown promise in prophylactically reducing the incidence of sepsis in critically ill patients with suspected infections. Proper levels of vitamin D are essential for metabolic functions, hormonal balance, and immune system support, while deficiency can increase susceptibility to chronic diseases like cancer, obesity, and infections. Furthermore, vitamin D exhibits antioxidant and anti-inflammatory effects, potentially reducing the risk factors for chronic cardiometabolic diseases and cancer, thus improving overall health and quality of life.

What are the specific applications of Deep Neural Networks (DNNs) in data mining?5 answersDeep Neural Networks (DNNs) find diverse applications in data mining across various industries. In mining, DNNs are utilized for solving exploration, extraction, and reclamation-related challenges. In animal sciences, Artificial Neural Networks (ANNs), a type of DNN, are employed for pattern recognition, clustering, forecasting, and classification tasks. Additionally, DNNs are applied in the retail sector for fraud detection, customer retention, and investment performance analysis. Moreover, DNN technology is leveraged in multimedia film and television for extracting valuable information from audio, video, and text data. Furthermore, the development of DNNs has enhanced text classification tasks in data mining, enabling the extraction of semantic information from textual data.

How does the presence of a GDD affect the outcomes of DSEK in post-glaucoma patients?5 answersThe presence of a Glaucoma Drainage Device (GDD) can impact the outcomes of Descemet Stripping Endothelial Keratoplasty (DSEK) in post-glaucoma patients. Studies suggest that eyes with pre-existing GDDs have lower graft survival rates compared to those without GDDs. Additionally, the location of the GDD tube insertion, whether in the anterior chamber or ciliary sulcus, can influence outcomes. While both placements are effective, ciliary sulcus placement may result in lesser corneal decompensation, making it preferable for pseudophakic/aphakic patients, especially those with post-penetrating keratoplasty glaucoma. Furthermore, the type of glaucoma surgery, such as glaucoma-filtering surgeries versus tube shunt surgeries, can also impact graft survival rates after DSEK. Overall, careful consideration of GDD presence and placement is crucial in optimizing outcomes for post-glaucoma patients undergoing DSEK.

How is data mining used in business and industry?5 answersData mining is a powerful tool used in business and industry to uncover patterns and extract valuable insights from large datasets. It enables organizations to make more informed and strategic decisions, improve decision-making quality, and enhance overall profitability. By analyzing historical data, data mining can identify trends and predict future outcomes, allowing businesses to create targeted marketing campaigns, improve pricing strategies, and boost customer retention. Additionally, data mining helps businesses understand customer behavior, consumption habits, and future demand, which can inform product development and market forecasting. It is also used to generate useful knowledge from unstructured data, such as scientific data, sensor data, and business transactions, to handle the growing volume of information. Overall, data mining is an essential step in the knowledge discovery process and provides organizations with a competitive advantage in today's fast-paced market.

How does the CRISP-DM methodology compare to other data mining methodologies, such as SEMMA and KDD?5 answersThe CRISP-DM methodology is a widely adopted standardized process for managing data mining projects. It has been used in various domains, including the financial services sector. However, there are perceived gaps in CRISP-DM that have been identified through case studies. These gaps have led to adaptations and extensions of the CRISP-DM process to address specific requirements in different industries. Despite its age, CRISP-DM is still considered the de facto standard for developing data mining projects. It is particularly suitable for goal-directed and process-driven projects, where the process model view holds. However, for more exploratory data science projects, a more flexible and trajectory-based model may be needed. Overall, CRISP-DM provides a structured framework for data mining projects, but adaptations may be necessary to address specific gaps and requirements in different sectors.

How is sql server beneficial?5 answersSQL Server is beneficial because it provides increased security, scalability, and power for organizations of all sizes. It helps reduce the maintenance burden on database administrators by allowing automation of routine tasks. SQL Server integrates multiple elements into a common architecture, reducing data impedance mismatches and providing what customers want. Additionally, SQL Server uses indexes to quickly retrieve records, reducing the number of disk IO and improving query performance. Overall, SQL Server is a comprehensive and powerful database solution that allows for secure and scalable enterprise applications, reduces administrative effort through automation, integrates multiple elements into a common architecture, and improves query performance through the use of indexes.

See what other people are reading

What are the benefits of using bibliometric analysis in scientific research?

Bibliometric analysis in scientific research offers numerous advantages. It aids in identifying research gaps, potential future directions, and new study prospects. Additionally, it helps in mapping relationships between concepts, research trends, and the state of the art in a particular field. Bibliometrics also assists in evaluating scientific output, impact, and trends, thereby fostering innovation and improving outcomes in various disciplines, including health research. Furthermore, it provides insights into the growth and development of specific research topics, such as FinTech, by analyzing publication trends, author collaborations, and citation structures. Overall, bibliometric analysis serves as a valuable tool for researchers to enhance their understanding of research landscapes, avoid duplication of efforts, and make informed decisions for future research endeavors.What are the disadvantages of using warehouse management system?

Disadvantages of using warehouse management systems (WMS) include high life cycle costs, challenging physical layouts, inadequate resources, security risks, and high energy consumption. Implementing WMS can be complex and risky due to insufficient knowledge of internal processes, leading to high costs and time-consuming involvement of experts. Challenges in WMS implementation also stem from the need for skilled personnel, data security concerns, and system integration issues. Additionally, the current manual intervention in warehouse operations can lead to issues like grain wastage, inferior quality distribution, and lack of transparency in food grain transportation. These factors highlight the barriers and drawbacks associated with adopting and utilizing warehouse management systems effectively.What are the benefits of trial transcripts?

Trial transcripts offer various advantages in different contexts. They can enhance precision oncology trials by integrating transcriptomics to predict patient responses to targeted therapies. Additionally, real-world data (RWD) integrated with transcriptomics can provide insights into disease pathways and clinical outcomes, aiding in personalized medicine. Moreover, trial transcripts can improve the accuracy of audio data recognition, facilitating the processing of trial information for multiple terminals. Overall, trial transcripts play a crucial role in advancing medical research, optimizing patient selection for treatments, and improving the efficiency of clinical trials through data integration and analysis.What is the impact of reducing subsumed rules on the accuracy of fuzzy inference systems?

Reducing subsumed rules in fuzzy inference systems can significantly enhance accuracy. Various methods have been proposed to address rule redundancy issues, such as rule fusion, space projection mechanisms, genetic optimization, and automatic search algorithms. By merging similar rules and projecting feature spaces effectively, the number of rules can be minimized without compromising accuracy. These approaches not only streamline the fuzzy rule base but also improve the system's modeling performance, demonstrating superior results compared to conventional methods even with fewer rules. Employing techniques like genetic optimization and automatic rule deletion ensures that the final knowledge base is more efficient and practical for real-world applications.What are the benefits of warehouse management system in managing inventory?

Warehouse Management Systems (WMS) offer numerous benefits in managing inventory efficiently. They enable businesses to control warehouse operations, including inventory management, order processing, and transportation management. Additionally, WMS can reduce the time required for inventory management tasks through the use of interconnected multi-robot systems. Moreover, a well-designed WMS allows for online order delivery for both in-person customers and online shoppers, enhancing customer service and satisfaction. Furthermore, WMS can optimize workflow, improve warehouse area optimization, and enhance the overall supply chain performance, leading to a more resource-efficient and dependable inventory management system.How following the Web Search Sources updates and Algorithms Developments augment web search user capacity and search skills?

Following the Web Search Sources updates and Algorithms Developments can significantly augment web search user capacity and search skills. By analyzing user-contributed content, identifying topic entities, determining relationships, and generating ontology models, search engines can provide additional topic entities to enhance search queries. Incorporating path information from other users' search trajectories can aid in improving search results and user experience. Furthermore, systems can identify and display remarkable information within search results, enhancing user experience and search skills. Additionally, augmenting search results with user-defined suggestions derived from social network content can provide practical information and improve user search capabilities. These advancements collectively contribute to enhancing user capacity and search skills by providing more relevant and personalized search results, ultimately improving the overall search experience.How does allergic rhinitis affect academic performance?

Allergic rhinitis (AR) significantly impacts academic performance among students. Studies reveal that AR prevalence among college students ranges from 19.22% to 31.1%, with a notable proportion experiencing impaired academic productivity and attendance, affecting both girls and boys equally. Children with AR also face challenges, with up to 40% affected, leading to decreased school productivity and performance. The negative consequences of AR on academic activities are evident, with students reporting fatigue, mood changes, and difficulty sleeping, all of which can hinder their educational pursuits. Furthermore, the impact extends to work and academic productivity, with a significant loss reported among employed and student patients, emphasizing the need for timely intervention and management strategies to mitigate the effects of AR on academic performance.What are the Top Priorities of Grade 10 Student?

The top priorities of Grade 10 students encompass various aspects crucial for their academic and personal development. Research indicates that Grade 10 students value career planning, self-regulated learning (SRL) skills, and academic progression. They recognize the significance of career planning in shaping their future and seek guidance to identify their passions and abilities. Additionally, fostering SRL skills among Grade 10 learners is essential for improving academic achievement and overcoming learning challenges, with a focus on enhancing time management, attitudes, and motivation. Moreover, student progression is highlighted as a top priority, emphasizing the importance of academic advancement and success in educational programs. By addressing these priorities, educators and stakeholders can support Grade 10 students in their journey towards a successful academic and professional future.Is there a negative correlation between social adjustment and academic performance?

The research findings from multiple studies provide insights into the relationship between social adjustment and academic performance. While some studies show a negative correlation between certain aspects of social adjustment, such as avoidant and anxiety attachment styles, with academic achievement, others highlight positive associations between social capital constructs like transfer capital, 4-year faculty social capital, and 4-year staff social capital with post-transfer grade point average and social adjustment. Additionally, social skills like hairyo and kakawari skills are positively correlated with academic grades, school satisfaction, self-esteem, and negatively correlated with feelings of victimization and depression. Overall, the relationship between social adjustment and academic performance is multifaceted, with both positive and negative correlations depending on the specific aspects of social adjustment and academic outcomes studied.Does globalization impacted bidar district of karnataka?

Globalization has indeed impacted Bidar District in Karnataka. The process of globalization has led to changes in various sectors, including agriculture. Data mining and knowledge discovery have been applied in Bidar District for soil classification and fertility analysis, aiming to empower farmers with advanced techniques for better crop yields. Furthermore, the impact of liberalization, privatization, and globalization (LPG) policies on entrepreneurship performance among small and medium enterprises (SMEs) has been studied, showing a significant correlation between the variables influenced by LPG policies and the performance of SMEs. These changes reflect the broader trend of globalization affecting local economies and societies, emphasizing the need for adaptation and innovation to thrive in the globalized world.What are some common methods for incorporating objective measures into the results-process-context framework?

In the context of incorporating objective measures into the results-process-context framework, various methods are proposed in the literature. One approach involves converting test results into universally applicable common metrics like T scores and percentile ranks, which can aid in reporting and discussing results with patients effectively. Another method focuses on extending the classical definition of process performance indicators (PPIs) for an object-centric context, which involves analyzing how customized performance measures are defined and integrating these requirements into established metamodels for automatic calculation of PPIs. Additionally, utilizing a multi-criteria evaluation framework that integrates Value Focused Thinking (VFT), Goal-Question-Metric (GQM) methods, and techniques from multi-criteria decision analysis can help in expediting the evaluation phase of the knowledge discovery via data mining process.