[PDF] Top 20 Towards a Machine Learning Approach for Earnings Manipulation Detection

... traditional approach, the continuous audit approach incorporates sophisticated methods such as data mining and machine learning techniques (Omar, Koya, Sanusi, & Shafie, ...fraud ... See full document

... outlier detection based IDS have the disadvantage of being computational expensive because the profile generated over a period needs to be updated against each system activity [12, ...17]. Machine ... See full document

... common approach to detecting spoofing attacks is to collect both real and fake data (spoofing attempts) and then try to learn a suitable classifier to predict whether a test sample is a real access or a spoofing ... See full document

... URL detection plays a serious role for many cyber security applications, and networking ...this approach we showed phishing URL detection by using machine learning algorithm called ... See full document

... In the neural networks community ensemble has been proposed by several authors (Boyun, 2007; GangLiu et al., 2010; Muhammad et al., 2011). Their method is based on multi-classifier combination using Dempster-Shafer ... See full document

... spam detection using various machine learning ...prominent machine learning techniques that have been proposed to solve the problem of review spam detection and the performance ... See full document

... intrusion detection are introduced. At last, a multi classifier approach is talked about that outcome into detection of known and unknown attacks with high accuracy and low false alarm ...the ... See full document

... a machine learning approach for perturbation detection and filtering, combined with a consensus algorithm for performance augmentation by cooperative data fusion at multiple ...proposed ... See full document

... vector machine (SVM ). SVM is known machine learning technique that has been used effectively to solve classification problems ...(supervised learning), the algorithm outputs an optimal ... See full document

... The time complexity is calculated based on the programmatical implementation. The State Estimator tokenizes the words in a nested loop so that the tokens can be identified hence making a time complexity as O(n 2 ). The ... See full document

... It is a group of related models that are used mbeddings. These models are layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and ... See full document

... the detection and resolution of abbreviations. The most popular approach relies on the use of heuristics to detect patterns of upper- case words consisting of a limited number of letters, which occur in ... See full document

... The detection strategy developed in this paper leverages the applications reliance on the platform APIs and their structured packaging to extract certain properties that could serve as indicators of suspicious ... See full document

... Intrusion Detection System (NIDS) has emerged as an indispensable ...Intrusion Detection System (IDS) can be categorized based on detection approach for determining the occurrence of ... See full document

... Intrusion detection system is a software application or a device placed at strategic places on a network to monitor and detect anomalies in network traffic [12][13] as shown in Figure ...complementary ... See full document

... KNN based Machine Learning Approach for Text and Document mining [54] Survey of review spam detection using machine learning techniques [55] Support vector machines and Word2vec for text[r] ... See full document

... In this dissertation, System provides a fundamental evaluation of ML algorithms on the detection of streaming spam tweets. In this evaluation, system works on offline tweets and real time tweets which are timely ... See full document

... the hidden layer. Given any nonzero constant there always exists an integer such that a SLFN with such hidden neurons and with randomly chosen input weights and hidden biases can learn distinct observations with its ... See full document

... deep learning approach, the efficiency of image recognition and object detection has increased dramatically over the past seven ...object detection, linguistic segmentation, image recovery and ... See full document

... an approach [32] to identify atypical review patterns by way of finding unexpected rules and rule ...used machine learning techniques and semi-supervised method, on the basis of manually labeled fake ... See full document