Titlebook: International Conference on Innovative Computing and Communications; Proceedings of ICICC Siddhartha Bhattacharyya,Aboul Ella Hassanien,Ind

偶然

Prediction of Air Quality Using Time Series Data Mining,cial task. In this paper, an Apriori-based association rule mining algorithm, which is a modified version of the Continuous Target Sequential Pattern Discovery (CTSPD), is used to generate a set of association rules that help in predicting the concentration of air pollutants. This algorithm consider

共和國

Optimisation of C5.0 Using Association Rules and Prediction of Employee Attrition, Distance from Home, Environment Satisfaction, Work Life Balance and Education Field out of 36 variables present in the dataset. Association Rule Algorithm ‘Apriori’ along with Decision Tree Algorithm ‘C5.0’ is used. The processing time taken to predict an attrition using the selected attributes usi

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新陳代謝

Lyme-disease

SoundEx Algorithm Revisited for Indian Language,retrieval of records is done through exact match of the spelling of words. Thus, to improve this, phonetic algorithms were introduced to retrieve the records from the database where matching is done through phonetics of the word instead of spelling match. In this paper, we have tried to implement th

Friction

Sentiment Analysis and Feature Extraction Using Rule-Based Model (RBM),s’ attitude, opinions, sentiments, and emotions. As we know sentiment analysis is one of the fields of natural language processing (NLP) that evaluates opinion of users and their sentiments, based on these sentiments and opinions, an individual or group can review their product and services. In this

chapel

The Role of Big Data Predictive Analytics Acceptance and Radio Frequency Identification Acceptance ed for big data predictive analytics to utilize the current data in different industries. The efficiency of big data can be enhanced through the use of radio frequency identification (RFID) technique in supply chain management (SCM). The objective of this study is to establish and empirically invest

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