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Journal articles on the topic 'Web Usage Mining; Data Mining Algorithms; Mining Techniques and Pattern Discovery'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Et. al., V. Aruna,. "A Review on Design and Development Of Sequential Patterns Algorithms In Web Usage Mining." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 1634–39. http://dx.doi.org/10.17762/turcomat.v12i2.1448.

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In the recent years with the advancement in technology, a lot of information is available in different formats and extracting the knowledge from that data has become a very difficult task. Due to the vast amount of information available on the web, users are finding it difficult to extract relevant information or create new knowledge using information available on the web. To solve this problem Web mining techniques are used to discover the interesting patterns from the hidden data .Web Usage Mining (WUM), which is one of the subset of Web Mining helps in extracting the hidden knowledge presen

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Ng, Qi Yau, and Mohd Nazmee Wan Zainon Wan. "UNDERSTANDING WEB TRAFFIC ACTIVITIES USING WEB MINING TECHNIQUES." International Journal of Engineering Technologies and Management Research 4, no. 9 (2017): 18–26. https://doi.org/10.5281/zenodo.1006814.

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<strong><em>Web Usage Mining is a computational process of discovering patterns in large data sets involving methods using the artificial intelligence, machine learning, statistical analysis and database systems with the goal to extract valuable information from accessing server logs of World Wide Web data repositories and transform it into an understandable structure for further understanding and use. Main focus of this paper will be centered on exploring methods that expedites the log mining process and present the result of log mining process through data visualization and compare data-mini

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Gul, Sumeer, Shohar Bano, and Taseen Shah. "Exploring data mining: facets and emerging trends." Digital Library Perspectives 37, no. 4 (2021): 429–48. http://dx.doi.org/10.1108/dlp-08-2020-0078.

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Purpose Data mining along with its varied technologies like numerical mining, textual mining, multimedia mining, web mining, sentiment analysis and big data mining proves itself as an emerging field and manifests itself in the form of different techniques such as information mining; big data mining; big data mining and Internet of Things (IoT); and educational data mining. This paper aims to discuss how these technologies and techniques are used to derive information and, eventually, knowledge from data. Design/methodology/approach An extensive review of literature on data mining and its allie

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N.Sanfia, Sehnaz* Dr.I.Elizabeth Shanthi. "MINING OF WEB LOG FILES USING RELEVANT COMPUTING TECHNIQUES FOR IMPROVING FUTURE ANTICIPATION USAGE OF WEB NAVIGATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 5 (2016): 536–41. https://doi.org/10.5281/zenodo.51534.

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The Internet has evolved extensively over the past few decades. Web navigation refers to the process of navigating a network of information resources in the World Wide Web, which is organized as hypertext or hypermedia.  The navigation related to web navigation usability gets solved by comparing the actual and anticipated usage patterns. The actual usage pattern removed from web server logs are sporadically recorded in operational websites for handling the log data. This process is used to identify the users, user session and user task oriented transactions. The pattern can be discovered

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Ali Mohammed, Mohammed, Hala Abdulsalam jasim, and Ahmed Oday. "Discussion on techniques of data cleaning, user identification, and session identification phases of web usage mining from 2000 to 2022." Iraqi Journal for Computers and Informatics 51, no. 1 (2025): 37–51. https://doi.org/10.25195/ijci.v51i1.549.

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The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

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Pradip, Suresh Mane, Kumar Jetawat Ashok, and Jagannath Nikumbh Pravin. "Web Page Recommendation using Random Forest with Fire Fly Algorithm in Web Mining." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 499–505. https://doi.org/10.35940/ijeat.B4442.029320.

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Nowadays, internet has become the easiest way to obtain more information from the web and millions of users search internet to find out the information. The continuous growth of web pages and users interest to search more information about various topics increases the complexity of recommendation. The user's behavior is extracted by using the web mining techniques, which are used in web server log. The main aim of this research study is to identify the navigation pattern of users from the log files. There are three major steps in the web mining process namely pre-processing the data, class

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Merin, J. Brindha, Dr W. Aisha Banu, Akila R., and Radhika A. "Semantic Annotation Based Mechanism for Web Service Discovery and Recommendation." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 14, no. 3 (2023): 169–85. http://dx.doi.org/10.58346/jowua.2023.i3.013.

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Web Mining is regarded as one among the data mining techniques that aids in fetching and extraction of necessary data from the web. Conversely, Web usage mining discovers and extracts essential patterns usage over the webs which are being further utilized by various web applications. In order to discover and explore web services that are registered with documents of Web Services-Inspection, Discovery and Integration registry, Universal Description wants specific search circumstance similar to URL, category and service name. The document of Web Service Description Language (WSDL) offers a condi

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Selvam, S. "Invention a Paradigm to Discovery the Network Navigation Using Poisson Distribution." Asian Journal of Electrical Sciences 9, no. 2 (2021): 9–12. http://dx.doi.org/10.51983/ajes-2020.9.2.2550.

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Due to increasing the act of Applied science College in Tamil Nadu, the level of competition for admission price is also increased. By implementing some dynamic strategies only the academic introduction s can meet their own competition. One survey clearly commonwealth that more than 75% of the Engineering Colleges their forcefulness is less than thirty % of their actual intake. Hence the surveillance is the job for the insane asylum s. One more survey shows that every year 10% of the applied science college’ windup their affiliation and blessing due to lack of admittance, and 5% of the enginee

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J., Umarani, and S. Manikandan Dr. "PATTERN DISCOVERY TECHNIQUES IN WEB USAGE MINING." International Journal of Scientific Research and Modern Education 3, no. 2 (2018): 1–3. https://doi.org/10.5281/zenodo.1332044.

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WWW is a very popular and interactive medium for broadcasting information today. Due to the vast, diverse and lively nature of web it advancesthe scalability, multimedia data and temporal issues respectively. The development of the web has given rise to large quantity of data that is freely available for user access.Web Usage Mining enhances the user experience while browsing web pages by using past history of web data. It also used to improve the web site navigation. Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web usage mining is

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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.

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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

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Patel, Ketul, and Dr A. R. Patel. "Process of Web Usage Mining to find Interesting Patterns from Web Usage Data." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 1 (2012): 144–48. http://dx.doi.org/10.24297/ijct.v3i1c.2767.

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The traffic on World Wide Web is increasing rapidly and huge amount of data is generated due to usersâ€™ numerous interactions with web sites. Web Usage Mining is the application of data mining techniques to discover the useful and interesting patterns from web usage data. It supports to know frequently accessed pages, predict user navigation, improve web site structure etc. In order to apply Web Usage Mining, various steps are performed. This paper discusses the process of Web Usage Mining consisting steps: Data Collection, Pre-processing, Pattern Discovery and Pattern Analysis. It has also p

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HOGO, MOFREH, MIROSLAV SNOREK, and PAWAN LINGRAS. "TEMPORAL VERSUS LATEST SNAPSHOT WEB USAGE MINING USING KOHONEN SOM AND MODIFIED KOHONEN SOM BASED ON THE PROPERTIES OF ROUGH SETS THEORY." International Journal on Artificial Intelligence Tools 13, no. 03 (2004): 569–91. http://dx.doi.org/10.1142/s0218213004001697.

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Temporal Web usage mining involves application of data mining techniques on temporal Web usage data to discover temporal usage patterns, which describe the temporal behavior of users on the Internet Web site, to understand the temporal users' behavior during different time slices. Clustering and classification are two important functions in Web mining. Classes, and associations in Web mining do not necessarily have crisp boundaries. Therefore the conventional clustering techniques became unsuitable to find such clusters and associations, where these conventional classification algorithms provi

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Banu, P. K. Nizar, and H. Inbarani. "Analysis of Click Stream Patterns using Soft Biclustering Approaches." International Journal of Information Technologies and Systems Approach 4, no. 1 (2011): 53–66. http://dx.doi.org/10.4018/jitsa.2011010104.

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As websites increase in complexity, locating needed information becomes a difficult task. Such difficulty is often related to the websites’ design but also ineffective and inefficient navigation processes. Research in web mining addresses this problem by applying techniques from data mining and machine learning to web data and documents. In this study, the authors examine web usage mining, applying data mining techniques to web server logs. Web usage mining has gained much attention as a potential approach to fulfill the requirement of web personalization. In this paper, the authors propose K-

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MR., Nilesh Kumar Dokania*1 &. MS. Jaspreet Kaur2. "A STUDY ON MINING PRODUCT OPINIONS AND REVIEWS ON THE WEB USING WEB SCRAPING." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 3 (2018): 365–73. https://doi.org/10.5281/zenodo.1199202.

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As enterprises expand and post increasing information about their business activities on their websites, website data promises to be a valuable source for investigating innovation. This article examines the practicalities and effectiveness of web mining as a research method for innovation studies. We use web mining to explore the R&D activities of 296 UK-based green goods small and mid-size enterprises. We find that website data offers additional insights when compared with other traditional unobtrusive research methods, such as patent and publication analysis. We examine the strengths and

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Ali Mohammed, Mohammed, Rula A. Hamid, and Reem Razzaq AbdulHussein. "Data Collection and Preprocessing in Web Usage Mining: Implementation and Analysis." Iraqi Journal for Computers and Informatics 50, no. 2 (2024): 54–74. http://dx.doi.org/10.25195/ijci.v50i2.486.

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Data collection and data preprocessing are crucial stages in web usage mining, mainly because of the unstructured, diverse, and noisy nature of log data. During data collection, log file datasets are loaded and merged. Effective and comprehensive data preprocessing plays a vital role in ensuring the efficiency and scalability of algorithms used in the pattern discovery phase of web usage mining. This work aims to address these phases by introducing two innovative approaches. The first approach focuses on determining the device used for accessing the web, distinguishing between computers and mo

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Vats, Deepak, and Avinash Sharma. "Analysis and Comparison of Various Web Mining Techniques." Journal of Computational and Theoretical Nanoscience 16, no. 10 (2019): 4125–34. http://dx.doi.org/10.1166/jctn.2019.8491.

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The reason at the back of data overloading dilemma faced by internet users on internet includes: excessive web information and billions of users around worldwide. Because of this, providing the internet users with more intended data is a challenging task in web applications. The lots of information available on internet are a fertile field for applying data mining techniques. This is what we call Web Mining (WM). The research in WM deals with research from many fields like database, Artificial Intelligence (machine learning [supervised, semi supervised, unsupervised and reinforcement], neural

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17

Jin, Jingquan, and Xin Lin. "Web Log Analysis and Security Assessment Method Based on Data Mining." Computational Intelligence and Neuroscience 2022 (August 25, 2022): 1–9. http://dx.doi.org/10.1155/2022/8485014.

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Web content mining describes the classification, clustering, and attribute analysis of a large number of text documents and multimedia files on the web. Special tasks include retrieval of data from the Internet search engine tool W; structured processing and analysis of web data. Today’s blog analysis has security concerns. We do experiments to investigate its safety. Through experiments, we draw the following conclusions: (1) Web log extraction can use efficient data mining algorithms to systematically extract logs from web servers, then determine the main access types or interests of users,

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Gandhimathi, D., and N. Anbazhagan. "Extracting of Positive and Negative Association Rules." International Journal of Emerging Research in Management and Technology 6, no. 8 (2018): 421. http://dx.doi.org/10.23956/ijermt.v6i8.175.

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Association rules analysis is a basic technique to expose how items/patterns are associated to each other. There are two common ways to measure association such as Support and Confidence. Several methods have been proposed in the literature to diminish the number of extracted association rules. Association Rule Mining is one of the greatest current data mining techniques designed to group objects together from huge databases aiming to take out the motivating correlation and relation with massive quantity of data. Association rule mining is used to discover the associated patterns from datasets

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Rekha, Sundari.M, and Reddy.PVGD Prasad. "PREPROCESSING OF WEB LOG DATA FOR WEB PERSONALIZATION." International Journal of Advances in Engineering & Technology 10, no. 1 (2017): 93–104. https://doi.org/10.5281/zenodo.3958601.

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<em>World Wide Web has its impact on almost every facet of human lives. It is the prevailing and most popularly known information source that is very simply assessable and searchable. Prior to web, useful information can be gathered by referring a document or gathering the data from the expert’s in the related areas, but with the rapid advancements in information technology, web has rigorously changed data seeking behavior of the users. The rapid growth in size and use of World Wide Web with its unique characteristics made web data mining an upcoming and area of demand in the present era

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20

Diwandari, Saucha, and Ahmad Tri Hidayat. "Predicting Analysis of User’s Interest from Web Log Data in e-Commerce using Classification Algorithms." Jurnal Ilmu Komputer dan Informasi 15, no. 1 (2022): 33–38. http://dx.doi.org/10.21609/jiki.v15i1.1024.

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The accelerated development of e-commerce has been a concern for business people. Business people should be able to gain customer interest in a variety of ways so that their companies can compete with others. Analyzing click-flow data will help organizations or firms assess customer loyalty, provide advertising privileges, and develop marketing strategies through user interests. By understanding consumer preferences, clickstream data analysis may be used to determine who is participating, assist companies in evaluating customer contentment, boost productivity, and design marketing strategies.

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Rajeev, Kumar. "A Framework of Web Mining Algorithm-Based Hidden Pattern in India E-Government Application Using Blockchain Technology." International Journal of Applied Engineering and Management Letters (IJAEML) 5, no. 1 (2021): 106–14. https://doi.org/10.5281/zenodo.4940047.

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<strong>Purpose: </strong><em>The</em> <em>Indian Government should be analyzing these problems and organized a special team who has responsibility for all inquiry and reduced these types of problem and India’s Government should be informed about new health projects to people by public relations or advertising.  Now, with the advent of data analysis techniques and tools, this process of finding patterns in the behavior of applications can be taken to a next higher level. The methods and algorithms used exclusively in data mining for medical purposes are known as Medical Data Mining.

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Samridha, M., Chawla Akshar, Roy Shagnik, and M. Neharidha. "Semantic Network." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 1 (2020): 240–43. https://doi.org/10.35940/ijeat.A1798.1010120.

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Knowledge representation is an emerging field of research in Artificial Intelligence, Big data analytics, Semantic web, and Data Mining. Knowledge represented in an effective way helps in easy traversal, searching, reasoning, prediction, and inference. There are number of approaches, algorithms, techniques, and models that have been proposed for the same. Every approach has their own pros and cons. Hence our aim is to propose a simple and extremely effective way to represent knowledge, which has a greater expressiveness compared to logic and reverberates within the methods of people process da

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23

Siriwan, Kajornkasirat, Hnusuwan Benjawan, Puttinaovarat Supattra, Puangsuwan Kritsada, and Kaewsuwan Nawapon. "Recommender system for dengue prevention using machine learning." IAES International Journal of Artificial Intelligence (IJ-AI) 14, no. 2 (2025): 1106–15. https://doi.org/10.11591/ijai.v14.i2.pp1106-1115.

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The study aimed to develop a recommender system for dengue prevention using environmental factors and mosquito larvae data. Data were collected from 100 households in Surat Thani, Thailand using mosquito larval survey in January 2020. Data mining techniques: frequent pattern growth (FP-Growth) and Apriori algorithms were used to find association rules and to compare accuracies for selecting a suitable model. The recommender system was designed as a web application. FP-Growth is more suitable for these data than Apriori algorithm. The factors associated with dengue infection, including communit

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24

Ahmad, Ali, and Gafar Hassan. "Web Mining overview: Techniques, Tools, and Ethical Implications." Journal of Computer Sciences and Informatics, 2024, 1. http://dx.doi.org/10.5455/jcsi.20240624085736.

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In an era of unprecedented data growth, web mining has become essential for uncovering actionable insights from the vast expanse of online information. This study provides a comprehensive overview of web mining, focusing on extracting valuable insights such as user behavior patterns, trend identification, and novel information discovery. It categorizes web mining into three pivotal areas: web content mining, web structure mining, and web usage mining, and highlights key techniques, tools, and algorithms associated with each. The paper addresses critical challenges including data privacy, algor

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25

Bharati, K. F. "Hybrid Algorithm for Improving Efficiency of Keywords based Search Engine." International Journal of Computer Science and Informatics, April 2012, 271–74. http://dx.doi.org/10.47893/ijcsi.2012.1051.

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Web mining is the application of data mining techniques to discover interesting patterns from the Web. Web usage mining is the process of extracting useful information from server logs i.e users history. While discovering interesting patterns in multi agents the efficiency is decreased. In our paper presents hybrid algorithm is designed for the improvement of the efficiency of keywords based search engine. The model divides mining task into several parallel agents which coordinately work together, and the mining efficiency is improved greatly. The hybrid algorithm is Evolved from HITS, algorit

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26

Pattnaik, Sabyasachi, Jui Pattnayak, and Priyaranjan Dash. "E-Learning: A Milestone in the Research of Data Mining." International Journal of Computer and Communication Technology, April 2012, 82–86. http://dx.doi.org/10.47893/ijcct.2012.1119.

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Data Mining and Data Warehousing are two most important techniques for pattern discovery and centralized data management in today’s technology. ELearning is one of the most significant applications of data mining. The main objective is to provide a proposal for a functional model and service architecture. The standards and system architecture are analyzed here. This paper gives importance to the integration of Web Services on the e-Learning application domain, because Web Service is the most advanced choice for distance education now. The process of e-Learning can be possible more effectively

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B., Prathyusha, Sharma Rupali, Yamini Y., and Amitha Bhavana Reddy R. "MINING SERENDIPITOUS DRUGS FROM REVIEWS USING MACHINE LEARNING TECHNIQUES." October 18, 2022. https://doi.org/10.5281/zenodo.7221238.

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The word serendipity means ‘happy accident’. Making discoveries by accident has contributed a lot to medical history. Serendipitous drug use is when a patient takes a prescription for a separate known indication and unintentionally experiences relief from comorbid illnesses or symptoms. The discovery of numerous new medication indications has benefited greatly from serendipity throughout history. Drug-repositioning hypotheses might be created and validated if patient-reported serendipitous drug usage in social media could be computationally discovered. We looked into deep neural ne

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28

"Web Page Recommendation using Random Forest with Fire Fly Algorithm in Web Mining." International Journal of Engineering and Advanced Technology 9, no. 3 (2020): 499–505. http://dx.doi.org/10.35940/ijeat.b4442.029320.

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Abstract:

Nowadays, internet has become the easiest way to obtain more information from the web and millions of users search internet to find out the information. The continuous growth of web pages and users interest to search more information about various topics increases the complexity of recommendation. The user's behavior is extracted by using the web mining techniques, which are used in web server log. The main aim of this research study is to identify the navigation pattern of users from the log files. There are three major steps in the web mining process namely pre-processing the data, classific

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29

Kumar, Rajeev. "A Framework of Web Mining Algorithm-Based Hidden Pattern in India E-Government Application Using Blockchain Technology." International Journal of Applied Engineering and Management Letters, June 14, 2021, 106–14. http://dx.doi.org/10.47992/ijaeml.2581.7000.0096.

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Purpose: The Indian Government should be analyzing these problems and organized a special team who has responsibility for all inquiry and reduced these types of problem and India’s Government should be informed about new health projects to people by public relations or advertising. Now, with the advent of data analysis techniques and tools, this process of finding patterns in the behavior of applications can be taken to a next higher level. The methods and algorithms used exclusively in data mining for medical purposes are known as Medical Data Mining. Many studies in the fields of e-governmen

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30

"Semantic Network." Regular 10, no. 1 (2020): 240–43. http://dx.doi.org/10.35940/ijeat.a1798.1010120.

Full text

Abstract:

Knowledge representation is an emerging field of research in Artificial Intelligence, Big data analytics, Semantic web, and Data Mining. Knowledge represented in an effective way helps in easy traversal, searching, reasoning, prediction, and inference. There are number of approaches, algorithms, techniques, and models that have been proposed for the same. Every approach has their own pros and cons. Hence our aim is to propose a simple and extremely effective way to represent knowledge, which has a greater expressiveness compared to logic and reverberates within the methods of people process da

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