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Article
Publication date: 29 October 2018

Shrawan Kumar Trivedi and Shubhamoy Dey

To be sustainable and competitive in the current business environment, it is useful to understand users’ sentiment towards products and services. This critical task can be…

Abstract

Purpose

To be sustainable and competitive in the current business environment, it is useful to understand users’ sentiment towards products and services. This critical task can be achieved via natural language processing and machine learning classifiers. This paper aims to propose a novel probabilistic committee selection classifier (PCC) to analyse and classify the sentiment polarities of movie reviews.

Design/methodology/approach

An Indian movie review corpus is assembled for this study. Another publicly available movie review polarity corpus is also involved with regard to validating the results. The greedy stepwise search method is used to extract the features/words of the reviews. The performance of the proposed classifier is measured using different metrics, such as F-measure, false positive rate, receiver operating characteristic (ROC) curve and training time. Further, the proposed classifier is compared with other popular machine-learning classifiers, such as Bayesian, Naïve Bayes, Decision Tree (J48), Support Vector Machine and Random Forest.

Findings

The results of this study show that the proposed classifier is good at predicting the positive or negative polarity of movie reviews. Its performance accuracy and the value of the ROC curve of the PCC is found to be the most suitable of all other classifiers tested in this study. This classifier is also found to be efficient at identifying positive sentiments of reviews, where it gives low false positive rates for both the Indian Movie Review and Review Polarity corpora used in this study. The training time of the proposed classifier is found to be slightly higher than that of Bayesian, Naïve Bayes and J48.

Research limitations/implications

Only movie review sentiments written in English are considered. In addition, the proposed committee selection classifier is prepared only using the committee of probabilistic classifiers; however, other classifier committees can also be built, tested and compared with the present experiment scenario.

Practical implications

In this paper, a novel probabilistic approach is proposed and used for classifying movie reviews, and is found to be highly effective in comparison with other state-of-the-art classifiers. This classifier may be tested for different applications and may provide new insights for developers and researchers.

Social implications

The proposed PCC may be used to classify different product reviews, and hence may be beneficial to organizations to justify users’ reviews about specific products or services. By using authentic positive and negative sentiments of users, the credibility of the specific product, service or event may be enhanced. PCC may also be applied to other applications, such as spam detection, blog mining, news mining and various other data-mining applications.

Originality/value

The constructed PCC is novel and was tested on Indian movie review data.

Article
Publication date: 14 November 2016

Shrawan Kumar Trivedi and Shubhamoy Dey

The email is an important medium for sharing information rapidly. However, spam, being a nuisance in such communication, motivates the building of a robust filtering system with…

Abstract

Purpose

The email is an important medium for sharing information rapidly. However, spam, being a nuisance in such communication, motivates the building of a robust filtering system with high classification accuracy and good sensitivity towards false positives. In that context, this paper aims to present a combined classifier technique using a committee selection mechanism where the main objective is to identify a set of classifiers so that their individual decisions can be combined by a committee selection procedure for accurate detection of spam.

Design/methodology/approach

For training and testing of the relevant machine learning classifiers, text mining approaches are used in this research. Three data sets (Enron, SpamAssassin and LingSpam) have been used to test the classifiers. Initially, pre-processing is performed to extract the features associated with the email files. In the next step, the extracted features are taken through a dimensionality reduction method where non-informative features are removed. Subsequently, an informative feature subset is selected using genetic feature search. Thereafter, the proposed classifiers are tested on those informative features and the results compared with those of other classifiers.

Findings

For building the proposed combined classifier, three different studies have been performed. The first study identifies the effect of boosting algorithms on two probabilistic classifiers: Bayesian and Naïve Bayes. In that study, AdaBoost has been found to be the best algorithm for performance boosting. The second study was on the effect of different Kernel functions on support vector machine (SVM) classifier, where SVM with normalized polynomial (NP) kernel was observed to be the best. The last study was on combining classifiers with committee selection where the committee members were the best classifiers identified by the first study i.e. Bayesian and Naïve bays with AdaBoost, and the committee president was selected from the second study i.e. SVM with NP kernel. Results show that combining of the identified classifiers to form a committee machine gives excellent performance accuracy with a low false positive rate.

Research limitations/implications

This research is focused on the classification of email spams written in English language. Only body (text) parts of the emails have been used. Image spam has not been included in this work. We have restricted our work to only emails messages. None of the other types of messages like short message service or multi-media messaging service were a part of this study.

Practical implications

This research proposes a method of dealing with the issues and challenges faced by internet service providers and organizations that use email. The proposed model provides not only better classification accuracy but also a low false positive rate.

Originality/value

The proposed combined classifier is a novel classifier designed for accurate classification of email spam.

Details

VINE Journal of Information and Knowledge Management Systems, vol. 46 no. 4
Type: Research Article
ISSN: 2059-5891

Keywords

Article
Publication date: 23 January 2019

Mayank Shrivastava, Anthony Abu, Rajesh Dhakal and Peter Moss

This paper aims to describe current trends in probabilistic structural fire engineering and provides a comprehensive summary of the state-of-the-art of performance-based…

Abstract

Purpose

This paper aims to describe current trends in probabilistic structural fire engineering and provides a comprehensive summary of the state-of-the-art of performance-based structural fire engineering (PSFE).

Design/methodology/approach

PSFE has been introduced to overcome the limitations of current conventional design approaches used for the design of fire-exposed structures, which investigate assumed worst-case fire scenarios and include multiple thermal and structural analyses. PSFE permits buildings to be designed in relation to a level of life safety or economic loss that may occur in future fire events with the help of a probabilistic approach.

Findings

This paper brings together existing research on various sources of uncertainty in probabilistic structural fire engineering, such as elements affecting post-flashover fire development, material properties, fire models, fire severity, analysis methods and structural reliability.

Originality/value

Prediction of economic loss would depend on the extent of damage, which is further dependent on the structural response. The representative prediction of structural behaviour would depend on the precise quantification of the fire hazard. The incorporation of major uncertainty sources in probabilistic structural fire engineering is explained, and the detailed description of a pioneering analysis method called incremental fire analysis is presented.

Details

Journal of Structural Fire Engineering, vol. 10 no. 2
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 11 November 2013

Giovanni Petrone, John Axerio-Cilies, Domenico Quagliarella and Gianluca Iaccarino

A probabilistic non-dominated sorting genetic algorithm (P-NSGA) for multi-objective optimization under uncertainty is presented. The purpose of this algorithm is to create a…

Abstract

Purpose

A probabilistic non-dominated sorting genetic algorithm (P-NSGA) for multi-objective optimization under uncertainty is presented. The purpose of this algorithm is to create a tight coupling between the optimization and uncertainty procedures, use all of the possible probabilistic information to drive the optimizer, and leverage high-performance parallel computing.

Design/methodology/approach

This algorithm is a generalization of a classical genetic algorithm for multi-objective optimization (NSGA-II) by Deb et al. The proposed algorithm relies on the use of all possible information in the probabilistic domain summarized by the cumulative distribution functions (CDFs) of the objective functions. Several analytic test functions are used to benchmark this algorithm, but only the results of the Fonseca-Fleming test function are shown. An industrial application is presented to show that P-NSGA can be used for multi-objective shape optimization of a Formula 1 tire brake duct, taking into account the geometrical uncertainties associated with the rotating rubber tire and uncertain inflow conditions.

Findings

This algorithm is shown to have deterministic consistency (i.e. it turns back to the original NSGA-II) when the objective functions are deterministic. When the quality of the CDF is increased (either using more points or higher fidelity resolution), the convergence behavior improves. Since all the information regarding uncertainty quantification is preserved, all the different types of Pareto fronts that exist in the probabilistic framework (e.g. mean value Pareto, mean value penalty Pareto, etc.) are shown to be generated a posteriori. An adaptive sampling approach and parallel computing (in both the uncertainty and optimization algorithms) are shown to have several fold speed-up in selecting optimal solutions under uncertainty.

Originality/value

There are no existing algorithms that use the full probabilistic distribution to guide the optimizer. The method presented herein bases its sorting on real function evaluations, not merely measures (i.e. mean of the probabilistic distribution) that potentially do not exist.

Details

Engineering Computations, vol. 30 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 16 November 2015

Keng Hoon Gan and Keat Keong Phang

This paper aims to focus on automatic selection of two important structural concepts required in an XML query, namely, target and constraint concepts, when given a keywords query…

Abstract

Purpose

This paper aims to focus on automatic selection of two important structural concepts required in an XML query, namely, target and constraint concepts, when given a keywords query. Due to the diversities of concepts used in XML resources, it is not easy to select a correct concept when constructing an XML query.

Design/methodology/approach

In this paper, a Context-based Term Weighting model that performs term weighting based on part of documents. Each part represents a specific context, thus offering better capturing of concept and term relationship. For query time analysis, a Query Context Graph and two algorithms, namely, Select Target and Constraint (QC) and Select Target and Constraint (QCAS) are proposed to find the concepts for constructing XML query.

Findings

Evaluations were performed using structured document for conference domain. For constraint concept selection, the approach CTX+TW achieved better result than its baseline, NCTX, when search term has ambiguous meanings by using context-based scoring for the concepts. CTX+TW also shows its stability on various scoring models like BM25, TFIEF and LM. For target concept selection, CTX+TW outperforms the standard baseline, SLCA, whereas it also records higher coverage than FCA, when structural keywords are used in query.

Originality/value

The idea behind this approach is to capture the concepts required for term interpretation based on parts of the collections rather than the entire collection. This allows better selection of concepts, especially when a structured XML document consists many different types of information.

Details

International Journal of Web Information Systems, vol. 11 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Book part
Publication date: 18 July 2017

Kala Saravanamuthu

Accounting’s definition of accountability should include attributes of socioenvironmental degradation manufactured by unsustainable technologies. Beck argues that emergent…

Abstract

Accounting’s definition of accountability should include attributes of socioenvironmental degradation manufactured by unsustainable technologies. Beck argues that emergent accounts should reflect the following primary characteristics of technological degradation: complexity, uncertainty, and diffused responsibility. Financial stewardship accounts and probabilistic assessments of risk, which are traditionally employed to allay the public’s fear of uncontrollable technological hazards, cannot reflect these characteristics because they are constructed to perpetuate the status quo by fabricating certainty and security. The process through which safety thresholds are constructed and contested represents the ultimate form of socialized accountability because these thresholds shape how much risk people consent to be exposed to. Beck’s socialized total accountability is suggested as a way forward: It has two dimensions, extended spatiotemporal responsibility and the psychology of decision-making. These dimensions are teased out from the following constructs of Beck’s Risk Society thesis: manufactured risks and hazards, organized irresponsibility, politics of risk, radical individualization and social learning. These dimensions are then used to critically evaluate the capacity of full cost accounting (FCA), and two emergent socialized risk accounts, to integrate the multiple attributes of sustainability. This critique should inform the journey of constructing more representative accounts of technological degradation.

Details

Parables, Myths and Risks
Type: Book
ISBN: 978-1-78714-534-4

Keywords

Article
Publication date: 12 January 2024

Pengyun Zhao, Shoufeng Ji and Yuanyuan Ji

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

Abstract

Purpose

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

Design/methodology/approach

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Findings

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Originality/value

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 16 November 2015

Maria Creuza Borges de Araújo, Luciana Hazin Alencar and Joana Coelho Viana

This paper aims to put forward a group multicriteria supplier selection model to select suppliers adequate to companies needs in food industries. Selecting the right suppliers has…

2222

Abstract

Purpose

This paper aims to put forward a group multicriteria supplier selection model to select suppliers adequate to companies needs in food industries. Selecting the right suppliers has become a strategic problem for firms. This decision should take into account several factors,which involve both quantitative and qualitative considerations and,usually,includes many interested parties.

Design/methodology/approach

The proposed model consists of two phases. Initially,a survey of food industries in Brazil was carried out so as to identify the factors that should be considered in the supplier selection decision process. In the second step,a selection model was developed,based on these findings and the factors identified,and an application of the model was conducted.

Findings

This model uses criteria that are important for the food industries in Brazil and,considering this criteria,helps companies to select the adequate suppliers to their needs. Additionally,the model considers the preferences of the managers who actively participate in the process.

Originality/value

The model helps the company in the selection of suppliers,as it is very important for the corporation to have partnerships with suppliers who can adequately meet its needs. Additionally,a group method was applied,which allows all the managers that will be affected by this decision to participate.

Details

Management Research Review, vol. 38 no. 11
Type: Research Article
ISSN: 2040-8269

Keywords

Article
Publication date: 1 March 2010

Pier Angelo Mori and Nicola Doni

The main aim of this paper is to review some of the newest and most promising advances in auction theory with an eye to applications to procurement practice. Here we focus in…

Abstract

The main aim of this paper is to review some of the newest and most promising advances in auction theory with an eye to applications to procurement practice. Here we focus in particular on four topics related to multidimensional auctions: 1) how to define a proper scoring rule when the awarding bodies lack the necessary information regarding its own preferences and suppliers’ technology; 2) how to cope with the information disclosure policy regarding the discretional evaluation of some aspects of each contractual proposal; 3) how to use contractors’ reputations based on their past performance in the awarding process; 4) how to control the risk of collusion and corruption in the awarding phase.

Details

Journal of Public Procurement, vol. 10 no. 1
Type: Research Article
ISSN: 1535-0118

Open Access
Article
Publication date: 18 May 2023

Klender Cortez, Martha del Pilar Rodríguez-García and Christian Reich

This research aims to analyse the variables related to the purchase intention of COVID-19 rapid tests in Monterrey, Mexico's metropolitan area.

Abstract

Purpose

This research aims to analyse the variables related to the purchase intention of COVID-19 rapid tests in Monterrey, Mexico's metropolitan area.

Design/methodology/approach

The chosen method was probit regression. The results show that purchase intention depends on the consumer's perceived value and the perception of having a potential contagion and/or presenting symptoms related to the virus. Regarding limitations, the sampling method used in this investigation is a nonprobabilistic convenience approach delivered through a digital platform, which may not be the first option in other contexts.

Findings

The findings indicate that the probability of the purchase intention of rapid COVID tests increases when consumers perceive symptoms of the disease and when they have higher education or are female rather than concerning price or income, as suggested by classical demand theory.

Research limitations/implications

Probabilistic sampling was impossible due to the difficulty of collecting surveys during the COVID-19 pandemic. Instead, a nonprobabilistic sample of a representative random selection of different zip codes from the responses received was considered.

Originality/value

The originality of the paper is its contribution to consumer behaviour during the COVID-19 pandemic in a Latin American context.

Details

Journal of Economics, Finance and Administrative Science, vol. 28 no. 55
Type: Research Article
ISSN: 2218-0648

Keywords

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