Papers by Roshan Gangurde
Web page prediction using adaptive deer hunting with chicken swarm optimization based neural network model
International Journal of Modeling, Simulation, and Scientific Computing
The world wide web acts as the dominant tool for data transmission due to access such as data ret... more The world wide web acts as the dominant tool for data transmission due to access such as data retrieving and data transactions. The retrieval of data from the web is a complex procedure due to the large volume of web domain. The basic uses of the websites are described through web usage mining, which mines the weblog records to identify the pattern of accessing the web pages through the user. The web page prediction assists the web users in finding the plot and obtains the information as to their requirements. Several effective algorithms have been developed to mine association rules that make the predictive model more appropriate for web prediction. They can be commonly revised to ensure the changing feature of web access patterns. The Apriori algorithm involves extracting the recurrent itemset and interrelation rule that learns the relational data is commonly utilized for web page prediction. The Apriori algorithm remains the standard model for deriving the patterns and rules from...
Web Page Prediction Using Genetic Algorithm and Logistic Regression based on Weblog and Web Content Features
2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), 2020
As website users are increasing day by day, user behaviour analysis for improving the website per... more As website users are increasing day by day, user behaviour analysis for improving the website performance attracts many researchers. This paper introduces the web page prediction model by involving the Logistic Regression (LR), which takes web page content similarity as input in group of similar weblog rules. To get association rules, this work introduce Feed Forward Counter (FFC) model for identifying the association rule with single data iteration technique. Both regression and FFC increased the learning rate for enhancing the accuracy of page recommendation. For adopting the dynamic situation in the work, final prediction is done by Particle Swarm Optimization (PSO) algorithm, which uses learned regression value in fitness function value evaluation. Experiment is performed on instantaneous dataset attained from ProjectTunnel website, which is collection of weblog and keywords. Results shows that proposed Logistic Regression based Web Page Prediction Model (LWPPM) for next page prediction system has improved various evaluation parameters like precision, coverage, m-metric.
Noise Removal Framework for Market Basket Analysis
Rapid development in data analysis domain causes an ever growing demand for Market Basket Analysi... more Rapid development in data analysis domain causes an ever growing demand for Market Basket Analysis. However, predefined methods in this domain emphasize on different techniques which concentrate to select appropriate items. In this paper, we tried to develop a framework for cleaning the dataset that depends on the proposition that “Better noise removal brings out better data analysis”. Eliminating noisy objects is an essential goal of data preprocessing as noise hampers data analysis. Data cleaning techniques which are recently developed concentrates on noise removals that are the consequences of low-level data errors. It causes due to defective data gathering process, but data objects that are clearly connected or related only at some particular time or unrelated/unimportant can also be significantly interfere with data analysis. Thus, in order to improve the data analysis to a greater extent, noisy data with respect to the underlying analysis must be removed at data preprocessing ...
There is three main parallel association rule mining algorithms:-Count Distribution algorithm, Da... more There is three main parallel association rule mining algorithms:-Count Distribution algorithm, Data Distribution algorithm and Candidate Distribution algorithm. Existing parallel association rule mining algorithms suffer from many problems when mining huge transactional datasets. One major problem is that most of the parallel algorithms for a shared nothing environment are Apriori based algorithms. Apriori-based algorithms are proven to be non scalable due to many reasons, mainly: (1) the repetitive I/O disk scans, (2) the huge computation and communication 3) great deal of redundancy calculation involved during the candidacy generation. Since the databases to be mined are often very large, and the association rule mining is computationally and I/O intensive, we must rely on high-performance parallel mining method. This paper presents different parallel algorithms given by various researches to generate association rules by various methods. We have done comparative analysis of diffe...
Customer behaviour modelling is an important data mining approach for making operational and stra... more Customer behaviour modelling is an important data mining approach for making operational and strategic decisions. Market Basket Analysis (MBA) is used to determine products that customers purchase together. Knowing the products that a customer will shop as a group is very helpful to a retailer. The business can use this information in predicting sales at the right time, at the right place, and for the right customer. Moreover, Company Marketers can use the basket analysis results to determine new products to serve their existing loyal customers. In the present paper, Genetic Algorithm is used to determine the population of solutions, which consumes more time to produce a solution. In this paper, it is proposed to use the Extended HCleaner Algorithm to remove noisy data from the datasets. The pre-processed dataset is then submitted to an ANN model. From the ANN model, weights of the products are determined by an association. The products which get maximum weights are sent to Apriori ...
Next Web Page Prediction using Genetic Algorithm and Feed Forward Association Rule based on Web-Log Features
International Journal of Performability Engineering, 2020
Discrete Dynamics in Nature and Society
The traditional meat and poultry farms use a fixed quantity of supply, which creates an imbalance... more The traditional meat and poultry farms use a fixed quantity of supply, which creates an imbalance between demand and supply. Due to this imbalance, a huge amount is spent on balancing the requirements. There is an inequality among demand and supply since typical meat and poultry farms use a fixed amount of supply. A lot of money is spent trying to balance the requirements because of this mismatch. In addition, when connecting and building the meat and poultry farm system, the procedure ignores the impact on the environment. The owner’s primary goals are to retain massive profits and raise reliability. The classical method neglects the effect on the environment while linking and designing the meat and poultry farm system. The main aim of the owner is to increase the quality and maintain the maximum profit. This paper deals with the meat and poultry farms in two folds. In the first step, the IoT based system is implemented for the traceability and demand-supply monitoring. The second ...
IAES International Journal of Artificial Intelligence (IJ-AI)
Recommendation of web page as per users’ interest is a broad and important area of research. Rese... more Recommendation of web page as per users’ interest is a broad and important area of research. Researcher adopts user behavior from actions present in cookies, logs and search queries. This paper has utilized a prior webpage fetching model using web page prediction. For this purpose, web content in form of text and weblog features are analyzed. As per dynamic user behavior, proposed model LWPP-BOA (Logistic Web Page Prediction By Biogeography Optimization Algorithm) predict page by using genetic algorithm. Based on user actions, weblog feature are developed in form of association rules, while web content gives a set of relevant text patterns. Page prediction as per random user behavior is enhanced by means of Biogeography Optimization Algorithm where crossover operation is performed as per immigration and emigration values. Here population updation depends on other parameters of chromosome except fitness value. Experiments are conducted on real dataset having web content and weblogs. ...
In the recent years, analyzing shopping baskets turned out to be very appealing to retailers. Sop... more In the recent years, analyzing shopping baskets turned out to be very appealing to retailers. Sophisticated technology made it possible for them to collect information of their customers and what they purchase. The introduction of electronic point-of-sale expanded the utilization and application of transactional data in Market Basket Analysis (MBA). In retail business, analyzing such information is exceedingly valuable for understanding purchasing behavior. Mining purchasing patterns allows retailers to adjust promotions, store settings and serve consumers better. Predictive analysis is an advanced branch of data engineering which generally predicts some occurrence or probability based on data. Predictive analytics uses data-mining techniques in order to make predictions about future events, and make recommendations based on these predictions. The process involves an analysis of historic data and based on that analysis to predict the future occurrences or events. A model can be created to predict using Predictive Analytics modelling techniques. The form of these predictive models varies depending on the data they are using. Predictive Analytics is composed of various statistical & analytical techniques used to develop models that will predict future occurrence, events or probabilities. Predictive analytics is able to not only deal with continuous changes, but discontinuous changes as well. Classification, prediction, and to some extent, affinity analysis constitute the analytical methods employed in predictive analytics.
In the recent years, analyzing shopping baskets turned out to be very appealing to retailers. Sop... more In the recent years, analyzing shopping baskets turned out to be very appealing to retailers. Sophisticated technology made it possible for them to collect information of their customers and what they purchase. The introduction of electronic point-of-sale expanded the utilization and application of transactional data in Market Basket Analysis (MBA). In retail business, analyzing such information is exceedingly valuable for understanding purchasing behavior. Mining purchasing patterns allows retailers to adjust promotions, store settings and serve consumers better. Predictive analysis is an advanced branch of data engineering which generally predicts some occurrence or probability based on data. Predictive analytics uses data-mining techniques in order to make predictions about future events, and make recommendations based on these predictions. The process involves an analysis of historic data and based on that analysis to predict the future occurrences or events. A model can be created to predict using Predictive Analytics modelling techniques. The form of these predictive models varies depending on the data they are using. Predictive Analytics is composed of various statistical & analytical techniques used to develop models that will predict future occurrence, events or probabilities. Predictive analytics is able to not only deal with continuous changes, but discontinuous changes as well. Classification, prediction, and to some extent, affinity analysis constitute the analytical methods employed in predictive analytics.
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Papers by Roshan Gangurde