In the community of sentiment analysis, supervised learning techniques have been shown to perform very well. When transferred to another domain, however, a supervised sentiment classifier often performs extremely bad. This is so-called domain-transfer problem. In this work, we attempt to attack this problem by making the maximum use of both the old-domain data and the unlabeled new-domain data....

Intrusion detection can be considered as a classification task that attempts to classify a request to access network services as safe or malicious. Data mining techniques are being used to extract valuable information that can help in detecting intrusions. In this paper, we evaluate the performance of rule based classifiers like: JRip, RIDOR, NNge and Decision Table (DT) with Naïve Bayes (NB) a...

Background: Industrial energy management has emerged as an important component in monitoring consumption particularly with the recent trend of migrating towards IR 4.0. The capability to detect anomalies is essential it serves a precautionary step for real-time response mitigate maximum demand penalty. purpose this research was develop high accuracy detection algorit...