Cuckoo inspired fast search algorithm for fractal image encoding

Ismail, B. Mohammed; Reddy, B. Eswara; Reddy, T. Bhaskara

doi:10.1016/j.jksuci.2016.11.003

Cited by 20 publications

(15 citation statements)

References 22 publications

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“…The graph is plotted by taking the rating on X-axis and the no of users on y-axis. As the graph, shows based on the users taken the movies are ranked and plotted on a scale of [5] rating.…”

Section: Resultsmentioning

confidence: 99%

“…Content Based Filtering is one such method where the recommendations are based on the information about the product and predict it to the user who has a similar need. [5] Collaborative Filtering is the method which filters not only based upon the user's past activity but also compares it with the several other users who gave similar type of rating and then give an accurate prediction. [6] They are two types of collaborative filtering techniques where the prediction is done as: 1) User based collaborative filtering 2) Item-based collaborative filtering User based collaborative filtering which is also called as memorybased filtering recommends the products based on the user's likes and interests.…”

Section: Introductionmentioning

confidence: 99%

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Collaborative filtering-based recommendation of online social voting

Ismail

Prakash

Rao

2018

IJET

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Social voting is becoming the new reason behind social recommendation these days. It helps in providing accurate recommendations with the help of factors like social trust etc. Here we propose Matrix factorization (MF) and nearest neighbor-based recommender systems accommodating the factors of user activities and also compared them with the peer reviewers, to provide a accurate recommendation. Through experiments we realized that the affiliation factors are very much needed for improving the accuracy of the recommender systems. This information helps us to overcome the cold start problem of the recommendation system and also y the analysis this information was much useful to cold users than to heavy users. In our experiments simple neighborhood model outperform the computerized matrix factorization models in the hot voting and non hot voting recommendation. We also proposed a hybrid recommender system producing a top-k recommendation inculcating different single approaches.

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“…The graph is plotted by taking the rating on X-axis and the no of users on y-axis. As the graph, shows based on the users taken the movies are ranked and plotted on a scale of [5] rating.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Collaborative filtering-based recommendation of online social voting

Ismail

Prakash

Rao

2018

IJET

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“…Early Detection of Lung Cancer utilizing SVM Classifier [9] in Biomedical Image Processing used Deep learning for detection of small cell lung cancer using CT Scanning. It is likewise recommended that CT scan [10] picture is utilized as information picture, is handled and beginning period lung disease is recognized utilizing a SVM (support vector machine) calculation as a classifier in the grouping stage to improve exactness, affectability and explicitness [11][12][13][14]…”

Section: Non-small Cell Lung Cancer (Nsclc) Is a Main Demise Malady Imentioning

confidence: 99%

Lung Cancer Prediction using Data Mining Techniques

2019

IJRTE

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The major cause for death in human beings is because of cancer .Lung cancer is one of the most common and serious types of cancer that severely harms the human body. In order to cure the cancer early cancer detection is required. If lung cancer is diagnosed at early stages many lives will be saved. The other name for lung cancer is lung carcinoma, an uncontrolled malignant tumor distinguished by undisciplined cell growth in lung cells. There are many people suffering from this kind of cancer and confining to death. If this is left untreated, this may grow later than lung by metastasis into other parts of body. Many of the cancers starts from lungs, called as primary lung carcinoma. There are two types of small cell lung carcinoma (SCLC), non small cell lung carcinoma(NSCLC). The main reason for lung cancer is smoking of cigarette. There are many researches targeting on exact approaches for treating cancer. To predict the survival rate for NSCLC patients data mining techniques can be used with selection of algorithms. The algorithms used to detect the lung cancer are Support vector machine (SVM), Decision tree, k-Nearest neighbour, Random forest, Logistic regression. In this paper By implementing 2 different datasets and various packages and libraries in python, it is compared and on implementation found suitable algorithms have more accuracy on certain data sets for optimum prediction rate of lung cancer..

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“…The Clinical Text analysis and Extraction system (cTAKES) made by experts the Mayo center started in the 19th century .kept up. cTAKES uses a design mechanism called Apache UIMA [11]. cTAKES makes use of various programming segments to group the pieces of the framework.…”

Section: B Medical Nlpmentioning

confidence: 99%

A Machine Learning Technique for Reducing Hospital Readmissions for Diabetic Diseases

ismail.b*,

Praveen,

Srikanth

2019

IJITEE

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The number of readmissions in diabetic diseases keeps increasing from time to time in patients from various hospitals. This brings a dreadful name to the hospital and is also considered as an act of irresponsibility of the doctors. So in order to reduce the readmissions of diabetic patients, we propose an approach which uses a machine learning technique to compare the hospital records of various patients. We have used various diabetic dataset features for our technique to predict the readmission probability rates of patients. We compared our proposed technique with existing Machine Learning algorithms like Random Forest, K-means clustering, Support Vector Machine(SVM) and found the best possible prediction with proposed approach using receiver operating characteristic( ROC) curve.

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Cuckoo inspired fast search algorithm for fractal image encoding

Cited by 20 publications

References 22 publications

Collaborative filtering-based recommendation of online social voting

Collaborative filtering-based recommendation of online social voting

Lung Cancer Prediction using Data Mining Techniques

A Machine Learning Technique for Reducing Hospital Readmissions for Diabetic Diseases

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