scholarly journals A Graph-Based Method for Predicting the Helpfulness of Product Opinions

2020 ◽  
Vol 13 (4) ◽  
pp. 06-21
Author(s):  
Rogério Figueredo De Sousa ◽  
Rafael Tôrres Anchiêta ◽  
Maria das Graças Volpe Nunes
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Graph Structure ◽  
Regularization Technique ◽  
New Approach ◽  
Network Methods ◽  
Area Use ◽  
Few Data ◽  
The Relationship ◽  
F Measure

This paper presents a new approach to predict the helpfulness of opinions. Usually, researchers in this area use tables of attribute-value to aggregate the features that represent the evaluated texts. Although that representation is common, it considers that the objects are independent. We argue that among the discriminant factors of the helpfulness of opinions, there are dependent factors of the relationship among the opinion-forming elements. Thus, we modeled this task as a network, considering the information of relations among objects in the network (comments, stars, and words). A regularization technique of graphs is used to extract the relevant features of graph structure and, after that, the comments are classified as helpful or unhelpful. We compared our network model with two baselines methods, one based on fuzzy logic and another based on Neural Networks. Our model outperformed the fuzzy logic and Neutal Network methods in 0.17 and 0.19 of F-measure, respectively. The main advantages of our approach are that few data are necessary to helpfulness classification and the relationships may help in the understanding the classification, explaining the reasons for a determinate classification.

Using Neural Networks to Discover Patterns in International Equity Markets

2002 ◽  
pp. 205-219 ◽  
Author(s):  
Mary E. Malliaris ◽  
Linda Salchenberger
Keyword(s):  
Neural Networks ◽  
Equity Markets ◽  
Time Frame ◽  
Exact Nature ◽  
Statistical Tools ◽  
New Approach ◽  
International Equity Markets ◽  
International Equity ◽  
The Relationship

The use of neural networks represents a new approach to how this type of problem can be investigated. The economics and finance literature is full of studies that require the researcher to prespecify the exact nature of the relationship and select specific variables to test. In this study, we use a multistage approach that requires no prespecification of the model and allows us to look for associations and relationships that may not have been considered. Previous studies have been limited by the nature of statistical tools, which require the researcher to determine the variables, time frame, and markets to test. An intelligent guess may lead to the desired outcome, but neural networks are used to produce a more thorough analysis of the data, thus improving the researcher’s ability to uncover unanticipated relationships and associations.

Applying Interval Fuzzy Petri Net to Failure Analysis

2020 ◽  
Vol 11 (1) ◽  
pp. 14-30
Author(s):  
Lajmi Fatma ◽  
Jalel Ghabi ◽  
Hedi Dhouibi
Keyword(s):  
Fuzzy Logic ◽  
Failure Analysis ◽  
Petri Nets ◽  
Graphical Representation ◽  
Logic Gate ◽  
New Approach ◽  
Novel Method ◽  
Definition Of ◽  
Fuzzy Logic Technique ◽  
The Relationship

In this article, the authors propose a new approach for modelling and failure analysis by combining the graphical representation provided by Petri nets and fuzzy logic. The graphical method is used for describing the relationship between conditions and events. The use of Petri nets in failure analysis enables replacing logic gate functions in fault trees. The Fuzzy logic technique allows natural language descriptions of process entities as well as an if-then rule-based definition of production. In addition, this study devises an alternative, a trapezoidal graph method in order to account for failure scenarios. Examples validating this novel method in dealing with failure analysis are also provided.

Design of Fuzzy Logic Controller and its Distinctive Feature

2018 ◽  
Vol 22 (5) ◽  
pp. 740-746
Author(s):  
Takeshi Yamakawa ◽  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Deep Learning ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Linguistic Terms ◽  
New Approach ◽  
Distinctive Features ◽  
Logic Control

Prof. Lotfi A. Zadeh, who created a new approach to describe a knowledge of a human expert with a natural language, passed away on September 6, 2017. His significant accomplishment was to create a novel artificial intelligence (AI) which exhibits the knowledge of human experts in natural linguistic terms. This system is structured and clear in two points of why a result is obtained and how it is done. The system contrasts with AI systems based on neural networks or deep learning. In this paper, the design of a fuzzy logic controller and its application to controlling of the mouse-platform stabilization are described. In addition, the distinctive features of fuzzy logic control are discussed. The author wants to offer this paper on the altar of Prof. Zadeh.

scholarly journals Database security: combining neural networks and classification approach

2020 ◽  
pp. 95-115
Author(s):  
Jarosław Skaruz
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Detection System ◽  
Time Series Prediction ◽  
Database Security ◽  
Prediction Problem ◽  
New Approach ◽  
Classification Approach ◽  
Backpropagation Through Time ◽  
The Relationship

In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take the advantage of using SQL statements to be performed. The problem of detection of this class of attacks is transformed to time series prediction problem. SQL queries are used as a source of events in a protected environment. To differentiate between normal SQL queries and those sent by an attacker, we divide SQL statements into tokens and pass them to our detection system, which predicts the next token, taking into account previously seen tokens. In the learning phase tokens are passed to a recurrent neural network (RNN) trained by backpropagation through time (BPTT) algorithm. Then, two coefficients of the rule are evaluated. The rule is used to interpret RNN output. In the testing phase RNN with the rule is examined against attacks and legal data to find out how evaluated rule affects efficiency of detecting attacks. All experiments were conducted on Jordan network. Experimental results show the relationship between the rule and a length of SQL queries.

Complex Identification Technique of Aircraft Gas Turbine Engine’s Health

2003 ◽  
Author(s):  
A. M. Pashayev ◽  
R. A. Sadiqov ◽  
P. S. Abdullayev
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Artificial Neural Networks ◽  
Gas Turbine ◽  
Soft Computing ◽  
Technical Condition ◽  
New Approach ◽  
Identification Technique ◽  
Artificial Neural

The new approach to identification of the aviation GTE technical condition is considered (examined) at an fuzzy, limitation and uncertainty of the information. This approach is based on applicability of fuzzy logic and artificial neural networks (Soft computing).

Synthetic Well-Log Generation: New Approach to Predict Formation Bulk Density While Drilling Using Neural Networks and Fuzzy Logic

2020 ◽  
Author(s):  
Ahmed Gowida ◽  
Salaheldin Elkatatny ◽  
Abdulazeez Abdulraheem ◽  
Dhafer Al Shehri
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Bulk Density ◽  
Well Log ◽  
New Approach

Colonialism and the Highland Clearances

2017 ◽  
Vol 8 (1) ◽  
pp. 22-48 ◽  
Author(s):  
Iain Mackinnon
Keyword(s):  
Industrial Development ◽  
Comparative Approach ◽  
Indigenous Research ◽  
Internal Colonialism ◽  
New Approach ◽  
A Site ◽  
Relationship Of ◽  
The Relationship ◽  
Imperial State ◽  
Late Modern

This article employs a new approach to studying internal colonialism in northern Scotland during the 18th and 19th centuries. A common approach to examining internal colonial situations within modern state territories is to compare characteristics of the internal colonial situation with attested attributes of external colonial relations. Although this article does not reject the comparative approach, it seeks to avoid criticisms that this approach can be misleading by demonstrating that promoters and managers of projects involving land use change, territorial dispossession and industrial development in the late modern Gàidhealtachd consistently conceived of their work as projects of colonization. It further argues that the new social, cultural and political structures these projects imposed on the area's indigenous population correspond to those found in other colonial situations, and that racist and racialist attitudes towards Gaels of the time are typical of those in colonial situations during the period. The article concludes that the late modern Gàidhealtachd has been a site of internal colonization where the relationship of domination between colonizer and colonized is complex, longstanding and occurring within the imperial state. In doing so it demonstrates that the history and present of the Gaels of Scotland belongs within the ambit of an emerging indigenous research paradigm.

Ozone Concentration Prediction using Artificial Neural Networks

2017 ◽  
Vol 68 (10) ◽  
pp. 2224-2227 ◽  
Author(s):  
Camelia Gavrila
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Ozone Concentration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Time Data ◽  
Marquardt Algorithm ◽  
Sensitivity Tests ◽  
Artificial Neural ◽  
The Relationship

The aim of this paper is to determine a mathematical model which establishes the relationship between ozone levels together with other meteorological data and air quality. The model is valid for any season and for any area and is based on real-time data measured in Bucharest and its surroundings. This study is based on research using artificial neural networks to model nonlinear relationships between the concentration of immission of ozone and the meteorological factors: relative humidity (RH), global solar radiation (SR), air temperature (TEMP). The ozone concentration depends on following primary pollutants: nitrogen oxides (NO, NO2), carbon monoxide (CO). To achieve this, the Levenberg-Marquardt algorithm was implemented in Scilab, a numerical computation software. Performed sensitivity tests proved the robustness of the model and its applicability in predicting the ozone on short-term.

Comparative analysis of intelligent planning methods

2012 ◽  
Vol 9 (2) ◽  
pp. 53-57 ◽  
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Mobile Robots ◽  
Sensory Information ◽  
Working Environment ◽  
Planning Methods ◽  
Intelligent Planning

The main stages of solving the problem of planning movements by mobile robots in a non-stationary working environment based on neural networks, genetic algorithms and fuzzy logic are considered. The features common to the considered intellectual algorithms are singled out and their comparative analysis is carried out. Recommendations are given on the use of this or that method depending on the type of problem being solved and the requirements for the speed of the algorithm, the quality of the trajectory, the availability (volume) of sensory information, etc.

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