DSpace Community:
http://hdl.handle.net/2440/299
2017-10-23T02:15:43ZRecognising user identity in twitter social networks via text mining
http://hdl.handle.net/2440/108779
Title: Recognising user identity in twitter social networks via text mining
Author: Keretna, S.; Hossny, A.; Creighton, D.
Abstract: Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, gtraining of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.2013-01-01T00:00:00ZMinimizing impact of bounded uncertainty on McNaughton's scheduling algorithm via interval programming
http://hdl.handle.net/2440/108778
Title: Minimizing impact of bounded uncertainty on McNaughton's scheduling algorithm via interval programming
Author: Hossny, A.; Nahavandi, S.; Creighton, D.
Abstract: Uncertainty of data affects decision making process as it increases the risk and the costs of the decision. One of the challenges in minimizing the impact of the bounded uncertainty on any scheduling algorithm is the lack of information, as only the upper bound and the lower bound are provided without any known probability or membership function. On the contrary, probabilistic uncertainty can use probability distributions and fuzzy uncertainty can use the membership function. McNaughton's algorithm is used to find the optimum schedule that minimizes the make span taking into consideration the preemption of tasks. The challenge here is the bounded inaccuracy of the input parameters for the algorithm, namely known as bounded uncertain data. This research uses interval programming to minimise the impact of bounded uncertainty of input parameters on McNaughton's algorithm, it minimises the uncertainty of the cost function estimate and increase its optimality. This research is based on the hypothesis that doing the calculations on interval values then approximate the end result will produce more accurate results than approximating each interval input then doing numerical calculations.2013-01-01T00:00:00ZSentiment analysis over social networks: an overview
http://hdl.handle.net/2440/108776
Title: Sentiment analysis over social networks: an overview
Author: Ahmed, K.; Tazi, N.; Hossny, A.
Abstract: The rapid increase in data on social media creates a need for mining such data to get valuable insights. The data type can be unstructured with large volumes. Sentiment analysis addresses such need by detecting opinions or emotions on the social media text. Sentiment analysis can be performed in various domains such as social, medical and industrial applications. This paper presents a survey about sentiment analysis addressing the different concepts in this area, problems and its solutions, available APIs, tools used and presenting a list of open challenges in this area.2016-01-01T00:00:00ZNoncommutative geometry and conformal geometry, II. Connes-Chern character and the local equivariant index theorem
http://hdl.handle.net/2440/108773
Title: Noncommutative geometry and conformal geometry, II. Connes-Chern character and the local equivariant index theorem
Author: Ponge, R.; Wang, H.
Abstract: This paper is the second part of a series of papers on noncommutative geometry and conformal geometry. In this paper, we compute explicitly the Connes-Chern character of an equivariant Dirac spectral triple. The formula that we obtain is used in the first paper of the series. The computation has two main steps. The first step is the justification that the CM cocycle represents the Connes-Chern character. The second step is the computation of the CM cocycle as a byproduct of a new proof of the local equivariant index theorem of Donnelly-Patodi, Gilkey and Kawasaki. The proof combines the rescaling method of Getzler with an equivariant version of the Greiner-Hadamard approach to the heat kernel asymptotics. Finally, as a further application of this approach, we compute the short-time limit of the JLO cocycle of an equivariant Dirac spectral triple.2016-01-01T00:00:00Z