Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Process (HDP), named (SAR-HDP). The phrase-based (or aspect-based) Bayesian model (SAR-HDP) did not consider the words sentence being drawn from a single topic due to the presence of multiple aspects in a single review, which belonged to a multiple-aspect topic (i.e., category). Beyond its consideration of the semantic information for aspect identi cation, the proposed model further upheld the semantic information discerned between the drawn topics and aspects identi ed to maintain topic consistency. Empirical investigation showed that the approach positioned successfully outperformed standard parametric models and nonparametric models in terms of aspect categorisation when subjected to restaurant and hotel reviews sourced from Amazon and TripAdvisor.
If we go beyond the technical aspects of the Web 2.0, and we focus specifically on its interactive characteristics, we may say it represents not only a fundamental shift in the structure of the press institutions and its practices but also a shift in the relationships that existed, previously, between the press and the audience. Web 2.0 has enabled the newspapers to renovate their representations and practices of the profession and opens to the new horizons either in terms of readership or advertising revenues. Parallel to that it also has empowered the user to transcend the passivity he has always been confined in and has become a more active participant in the creation and generation of media contents even though this practice is somew
... Show MoreIn this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop
... Show MoreThis study came to discuss the subject of industries dependent on petrochemical industries in Iraq (plastic as a model) during the period 2005–2020, and the study concluded that the plastic industries contribute to areas of advancement and progress and opportunities to deal efficiently with the challenges posed by the new variables, the most important of which is the information revolution. communications and trade liberalization, and this is what contributes to the competitiveness of these industries. And because the petrochemical industry in Iraq has an active role in establishing plastic industrial clusters and clusters of micro, small, and medium industries by providing the necessary feedstock for these industries in various fields
... Show MoreCybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
... Show MoreCybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
... Show MoreThe parameter and system reliability in stress-strength model are estimated in this paper when the system contains several parallel components that have strengths subjects to common stress in case when the stress and strengths follow Generalized Inverse Rayleigh distribution by using different Bayesian estimation methods. Monte Carlo simulation introduced to compare among the proposal methods based on the Mean squared Error criteria.
Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
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