Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

Solving fully fuzzy multi-objective linear programming problem with fuzzy dominant degrees

2020 ◽  
Vol 39 (3) ◽  
pp. 3577-3595
Author(s):  
Nguyen Van Hop
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
The Other ◽  
Absolute Value ◽  
Multi Objective ◽  
Different Types ◽  
Fuzzy Ranking ◽  
Better Than

In this paper, we investigate all relative relationships between two fuzzy numbers. Then, we introduce new relative measures to compare two fuzzy numbers instead of using absolute value to represent the fuzzy number. These measures address the dominant level that one fuzzy number is better than the other in terms of its position and shape. The so-called absolute fuzzy dominant degree and relative fuzzy dominant degree are developed to measure the differences between two fuzzy numbers applying for different types of constraint. These measures could capture all the shape’s characteristics and relative positions of fuzzy numbers. Finally, the fully fuzzy multi-objective decision making (FFMODM) problem is solved by using these fuzzy dominant degrees. For validation, we compare our approach to the fuzzy ranking method of the linear ranking function. Our obtained results show better performance.

Quota Women Are Threatening to Men

2017 ◽  
Vol 76 (3) ◽  
pp. 107-116 ◽  
Author(s):  
Klea Faniko ◽  
Till Burckhardt ◽  
Oriane Sarrasin ◽  
Fabio Lorenzi-Cioldi ◽  
Siri Øyslebø Sørensen ◽  
...  
Keyword(s):  
Decision Making ◽  
Organizational Performance ◽  
Gender Stereotypes ◽  
Perceived Threat ◽  
Preferential Treatment ◽  
Public Sector Employees ◽  
Different Types ◽  
Low Levels ◽  
Women In Decision Making ◽  
The Impact

Abstract. Two studies carried out among Albanian public-sector employees examined the impact of different types of affirmative action policies (AAPs) on (counter)stereotypical perceptions of women in decision-making positions. Study 1 (N = 178) revealed that participants – especially women – perceived women in decision-making positions as more masculine (i.e., agentic) than feminine (i.e., communal). Study 2 (N = 239) showed that different types of AA had different effects on the attribution of gender stereotypes to AAP beneficiaries: Women benefiting from a quota policy were perceived as being more communal than agentic, while those benefiting from weak preferential treatment were perceived as being more agentic than communal. Furthermore, we examined how the belief that AAPs threaten men’s access to decision-making positions influenced the attribution of these traits to AAP beneficiaries. The results showed that men who reported high levels of perceived threat, as compared to men who reported low levels of perceived threat, attributed more communal than agentic traits to the beneficiaries of quotas. These findings suggest that AAPs may have created a backlash against its beneficiaries by emphasizing gender-stereotypical or counterstereotypical traits. Thus, the framing of AAPs, for instance, as a matter of enhancing organizational performance, in the process of policy making and implementation, may be a crucial tool to countering potential backlash.

Beérkezett könyvek

2008 ◽  
Vol 63 (3) ◽  
pp. 607-608
Author(s):  
Csaba Pléh
Keyword(s):  
Decision Making ◽  
Human Mind ◽  
Frankfurt Am Main ◽  
Conscious Decision ◽  
Better Than

ErősFerenc, LénárdKataés BókayAntal(szerk.) Typus Budapestiensis. Tanulmányok a pszichoanalízis budapesti iskolájának történetéről éshatásáról. Thalassa, Budapest, 2008, 447 oldalHargittaiIstván: Doktor DNS. Őszinte beszélgetések James D. Watsonnal. Vince Kiadó, Budapest, 2008, 223 oldalKutrovátzGábor,LángBenedekésZemplénGábor: A tudomány határa. Typotex,Budapest, 2008, 376 oldalEngerl, C. andSinger, W. (eds) Better than conscious? Decision making, the human mind, and implications for institutions . MIT Press, Cambridge, 2008, xiv + 449 oldalKondor, Zsuzsanna: Embedded thinking. Multimedia and the new rationality. Peter Lang, Frankfurt am Main, 2008, xi + 169 oldalSíklakiIstván(szerk.): Szóbeli befolyásolás. I–II. Typotex, Budapest,_n

Impact of Environmental Degradation on Human Health

2016 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
_______ Archana ◽  
Charu Datta ◽  
Pratibha Tiwari
Keyword(s):  
Environmental Degradation ◽  
Human Population ◽  
Environmental Problems ◽  
Population Increase ◽  
Human Beings ◽  
The People ◽  
Wide Range ◽  
Different Types ◽  
Economic Institute ◽  
Day By Day

Degradation of environment is one of the most serious challenges before the mankind in today’s world. Mankind has been facing a wide range of problem arising out of the degradation of environment. Not only the areas under human inhabitation, but the areas of the planet without human population have also been suffering from these problems. As the population increase day by day, the amenities are not improved simultaneously. With the advancement of science and technologies the needs of human beings has been changing rapidly. As a result different types of environmental problems have been rising. Environmental degradation is a wide- reaching problem and it is likely to influence the health of human population is great. It may be defined the deterioration of the environment through depletion of resources such as air, water, and soil. The destruction of ecosystem and extinction of wildlife. Environmental degradation has occurred due to the recent activities in the field of socio-economic, institute and technology. Poverty still remains a problem as the root of several environmental problems to create awareness among the people about the ill effect of environmental pollution. In the whole research it is clear that all factors of environmental degradation may be reduced through- Framing the new laws on environmental degradation, Environment friend policy, Controlling all the ways and means of noise, air, soil and water pollution, Through growing more and more trees and by adapting the proper sanitation policy.  

Making the most of individual differences in joint decisions

2018 ◽  
Author(s):  
Bahador Bahrami
Keyword(s):  
Decision Making ◽  
Direct Evidence ◽  
Cross Cultural ◽  
Collective Decision Making ◽  
Wisdom Of Crowds ◽  
Trade Off ◽  
Adaptive Value ◽  
Joint Decisions ◽  
Cultural Data ◽  
Better Than

Evidence for and against the idea that “two heads are better than one” is abundant. This chapter considers the contextual conditions and social norms that predict madness or wisdom of crowds to identify the adaptive value of collective decision-making beyond increased accuracy. Similarity of competence among members of a collective impacts collective accuracy, but interacting individuals often seem to operate under the assumption that they are equally competent even when direct evidence suggest the opposite and dyadic performance suffers. Cross-cultural data from Iran, China, and Denmark support this assumption of similarity (i.e., equality bias) as a sensible heuristic that works most of the time and simplifies social interaction. Crowds often trade off accuracy for other collective benefits such as diffusion of responsibility and reduction of regret. Consequently, two heads are sometimes better than one, but no-one holds the collective accountable, not even for the most disastrous of outcomes.

scholarly journals Skill and strategic control

Synthese ◽  
2021 ◽  
Author(s):  
Ellen Fridland
Keyword(s):  
Decision Making ◽  
Empirical Evidence ◽  
Mental Imagery ◽  
Sports Psychology ◽  
Mental Practice ◽  
Strategic Control ◽  
Cognitive Representations ◽  
Personal Level ◽  
The Right ◽  
Better Than

AbstractThis paper provides an account of the strategic control involved in skilled action. When I discuss strategic control, I have in mind the practical goals, plans, and strategies that skilled agents use in order to specify, structure, and organize their skilled actions, which they have learned through practice. The idea is that skilled agents are better than novices not only at implementing the intentions that they have but also at forming the right intentions. More specifically, skilled agents are able formulate and modify, adjust and adapt their practical intentions in ways that are appropriate, effective, and flexible given their overall goals. Further, to specify the kind of action plans that are involved in strategic control, I’ll rely on empirical evidence concerning mental practice and mental imagery from sports psychology as well as evidence highlighting the systematic differences in the cognitive representations of skills between experts and non-experts. I’ll claim that, together, this evidence suggests that the intentions that structure skilled actions are practical and not theoretical, that is, that they are perceptual and motor and not abstract, amodal, or linguistic. Importantly, despite their grounded nature, these plans are still personal-level, deliberate, rational states. That is, the practical intentions used to specify and structure skilled actions are best conceived of as higher-order, motor-modal structures, which can be manipulated and used by the agent for the purpose of reasoning, deliberation, decision-making and, of course, the actual online structuring and organizing of action.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

scholarly journals Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Support Vector ◽  
Variational Autoencoder ◽  
Different Types ◽  
Static Images ◽  
Long Short Term Memory ◽  
2D And 3D ◽  
Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

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