• Corpus ID: 28544883

Analysis Of Machine Learning Techniques By Using Blogger

@inproceedings{Hemalatha2014AnalysisOM,
  title={Analysis Of Machine Learning Techniques By Using Blogger},
  author={M. Hemalatha},
  year={2014}
}
Blogs are the recent fast progressing media which depends on information system and technological advancement. The mass media is not much developed for the developing countries are in government terms and their schemes are developed based on governmental concepts, so blogs are provided for knowledge and ideas sharing. This article has highlighted and performed simulations from obtained information, 100 instances of Bloggers by using Weka 3. 6 Tool, and by applying many machine learning… 

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References

SHOWING 1-10 OF 34 REFERENCES
Analyzing Political Trends in the Blogosphere
TLDR
This paper applies sentiment and time series analysis techniques in combination with aggregation methods on blog data to estimate the temporal development of opinions on politicians in the blogosphere.
A Novel Approach for Social Behavior Analysis of the Blogosphere
TLDR
A system of blog analyzing, named Blogizer, has been designed to analyze blogs and the detailed analysis and the proof of concept case study provides promising results.
Crosslanguage blog mining and trend visualisation
TLDR
A crosslanguage blog mining and trend visualisation system to analyse blogs across languages and topics and to prove the correctness of the system the correlation between trends in blogs and news articles for a subset of blogs and topics was computed.
Personal Blogging; Individual Differences and Motivations
The present chapter examines current research of blogging practices; it focuses on the personal blog, a blog created and maintained by an individual and not used for financial or occupational gain.
NETWORK-BASED INTRUSION DETECTION USING NEURAL NETWORKS
TLDR
This work explores network based intrusion detection using classifying, self-organizing maps for data clustering and MLP neural networks for detection and shows that many of these attacks can be found by a careful analysis of network data.
Intrusion Detection with Neural Networks
TLDR
A backpropagation neural network called NNID (Neural Network Intrusion Detector) was trained in the identification task and tested experimentally on a system of 10 users, suggesting that learning user profiles is an effective way for detecting intrusions.
Classifying attacks in a network intrusion detection system based on artificial neural networks
TLDR
A new approach of intrusion detection system based on neural network is presented, which detects the attacks and classify them in 6 groups with the approximately 90.78% accuracy with the two hidden layers of neurons in the neural network.
Induction of Decision Trees
TLDR
This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, which is described in detail.
Survey: Using Genetic Algorithm Approach in Intrusion Detection Systems Techniques
TLDR
A survey were performed approaches based on intrusion detection systems (IDS), and on implementing of GAs (GAs) on IDS, for modeling and recognizing normal and abusive system behavior.
Generating Accurate Rule Sets Without Global Optimization
TLDR
This paper presents an algorithm for inferring rules by repeatedly generating partial decision trees, thus combining the two major paradigms for rule generation—creating rules from decision trees and the separate-and-conquer rule-learning technique.
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