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Open Access
Article
Publication date: 22 November 2022

Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index…

Abstract

Purpose

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Design/methodology/approach

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Findings

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

Originality/value

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Details

Marine Economics and Management, vol. 5 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

Article
Publication date: 1 December 2002

Jeong‐Hyen Kim and Kyung‐Ho Lee

This paper reports on the design of a knowledge base for an automatic classification in the library science field, by using the facet classification principles of colon…

1494

Abstract

This paper reports on the design of a knowledge base for an automatic classification in the library science field, by using the facet classification principles of colon classification (CC). To do so, by designing and constructing a knowledge base that is able to be classified automatically, and by inputting titles or key words of volumes into the computer, it aims to create class numbers automatically through automatic subject recognition and processing of key words in titles through the facet combination method of CC. Especially, the knowledge base for classification was designed along with the principle of globe and cylinder, automatic classification which can be possible.

Details

The Electronic Library, vol. 20 no. 6
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 25 April 2008

Birger Hjørland

The purpose of this paper is to provide an answer to a critique put forward by Szostak against a paper written by the present author.

1392

Abstract

Purpose

The purpose of this paper is to provide an answer to a critique put forward by Szostak against a paper written by the present author.

Design/methodology/approach

The paper is based on a literature‐based conceptual analysis based on Hjørland and Nissen Pedersen and Szostak. The main points in a core theory of classification are outlined and Szostak's criticism is examined and answered.

Findings

The paper demonstrates theoretical differences between the views adduced by Hjørland and Nissen Pedersen on the one side and by Szostak on the other.

Practical implications

Theoretical clarification is important for the future development of the field.

Originality/value

The paper should be seen as one among others developing an argument for a theoretical foundation of classification informed by the theory of knowledge.

Details

Journal of Documentation, vol. 64 no. 3
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 2 October 2017

Craig R. Scott and SoeYoon Choi

The emerging area of message classification is one of growing relevance to a wide range of organizational communicators as a variety of non-state organizations and their…

Abstract

Purpose

The emerging area of message classification is one of growing relevance to a wide range of organizational communicators as a variety of non-state organizations and their members increasingly use and misuse various terms to restrict their communication. This includes formal classifications for data security, financial/knowledge management, human resources, and other functions as well as those used informally by organizational members. Especially in a data-rich environment where our word-processing programs, e-mail tools, and other technologies afford us opportunities to engage in classification, a wide range of people at all organizational levels may serve as custodians of their own data and thus have the ability (as well as perhaps the need) to classify messages in various ways. The purpose of this paper is to describe key classification terms ranging from those found in government (e.g. top secret, confidential) to those in the private sector (e.g. business use only, trademarked) to an even wider set of terms used informally by organizational members (e.g. personal, preliminary). The growing use of message classifications will likely create various challenges and opportunities for organizations, their members, and the broader public/society. A set of future research questions is offered for corporate communication researchers and practitioners, who are well positioned to examine this emerging phenomenon.

Design/methodology/approach

This paper draws on existing literature related to the growing use of message classifications to offer a list of classification terms and an agenda for future research.

Findings

This work describes key classification terms ranging from those found in government (e.g. top secret, confidential) to those in the private sector (e.g. business use only, trademarked) to an even wider set of terms used informally by organizational members (e.g. personal, preliminary). This expanded notion of classification will likely create various challenges and opportunities for organizations, their members, and the broader public/society.

Originality/value

The emerging area of message classification is one of growing relevance to a wide range of organizational communicators as a variety of non-state organizations and their members increasingly use and misuse various terms to restrict their communication. A set of future research questions is offered for corporate communication researchers and practitioners, who are well positioned to examine this emerging phenomenon.

Details

Corporate Communications: An International Journal, vol. 22 no. 4
Type: Research Article
ISSN: 1356-3289

Keywords

Book part
Publication date: 12 October 2018

Tahir Sufi and Narges Shojaie

Hotel classification systems are used to convey information about facilities and services. Yet, they have been prone to criticism for overemphasizing facilities at the…

Abstract

Hotel classification systems are used to convey information about facilities and services. Yet, they have been prone to criticism for overemphasizing facilities at the expense of other matters of importance to service quality. In contrast, online travel agents (OTAs) use innovative methods to evaluate satisfaction with hotels. Conventional systems will lose relevance if they do not step up to consider service aspects associated with customer satisfaction. This chapter probes five hotel classification systems along with one OTA and leverages the literature to propose an improved framework classification. This is based on nine critical areas that include service quality, infrastructure, facilities and services, human resources, sustainability, safety and security, accessibility, quality systems, and online hotel ratings.

Details

Quality Services and Experiences in Hospitality and Tourism
Type: Book
ISBN: 978-1-78756-384-1

Keywords

Article
Publication date: 19 August 2022

Anjali More and Dipti Rana

Referred data set produces reliable information about the network flows and common attacks meeting with real-world criteria. Accordingly, this study aims to focus on the…

Abstract

Purpose

Referred data set produces reliable information about the network flows and common attacks meeting with real-world criteria. Accordingly, this study aims to focus on the use of imbalanced intrusion detection benchmark knowledge discovery in database (KDD) data set. KDD data set is most preferably used by many researchers for experimentation and analysis. The proposed algorithm improvised random forest classification with error tuning factors (IRFCETF) deals with experimentation on KDD data set and evaluates the performance of a complete set of network traffic features through IRFCETF.

Design/methodology/approach

In the current era of applications, the attention of researchers is immersed by a diverse number of existing time applications that deals with imbalanced data classification (ImDC). Real-time application areas, artificial intelligence (AI), Industrial Internet of Things (IIoT), etc. are dealing ImDC undergo with diverted classification performance due to skewed data distribution (SkDD). There are numerous application areas that deal with SkDD. Many of the data applications in AI and IIoT face the diverted data classification rate in SkDD. In recent advancements, there is an exponential expansion in the volume of computer network data and related application developments. Intrusion detection is one of the demanding applications of ImDC. The proposed study focusses on imbalanced intrusion benchmark data set, KDD data set and other benchmark data set with the proposed IRFCETF approach. IRFCETF justifies the enriched classification performance on imbalanced data set over the existing approach. The purpose of this work is to review imbalanced data applications in numerous application areas including AI and IIoT and tuning the performance with respect to principal component analysis. This study also focusses on the out-of-bag error performance-tuning factor.

Findings

Experimental results on KDD data set shows that proposed algorithm gives enriched performance. For referred intrusion detection data set, IRFCETF classification accuracy is 99.57% and error rate is 0.43%.

Research limitations/implications

This research work extended for further improvements in classification techniques with multiple correspondence analysis (MCA); hierarchical MCA can be focussed with the use of classification models for wide range of skewed data sets.

Practical implications

The metrics enhancement is measurable and helpful in dealing with intrusion detection systems–related imbalanced applications in current application domains such as security, AI and IIoT digitization. Analytical results show improvised metrics of the proposed approach than other traditional machine learning algorithms. Thus, error-tuning parameter creates a measurable impact on classification accuracy is justified with the proposed IRFCETF.

Social implications

Proposed algorithm is useful in numerous IIoT applications such as health care, machinery automation etc.

Originality/value

This research work addressed classification metric enhancement approach IRFCETF. The proposed method yields a test set categorization for each case with error reduction mechanism.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Book part
Publication date: 30 September 2003

Philip R Beaulieu

When decision makers encounter new assurance services that can be customized for individual clients, they must include them in their pre-existing categorization of…

Abstract

When decision makers encounter new assurance services that can be customized for individual clients, they must include them in their pre-existing categorization of assurance, a cognitive task known as postclassification. This paper draws upon three literatures (classification research in accounting, theory of assurance, and cognitive psychology) in order to suggest how this task might be modeled and studied empirically, using the example of SysTrust™. The role of a necessary condition for successful postclassification called the category use effect (Ross, 2000), in which decision makers are reminded of pre-existing categories when they learn to use new categories, is explained.

Details

Advances in Accounting Behavioral Research
Type: Book
ISBN: 978-1-84950-231-3

Article
Publication date: 6 September 2022

Hanane Sebbaq and Nour-eddine El Faddouli

The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts…

Abstract

Purpose

The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts transfer learning by using word2vec and a bidirectional gated recurrent units (GRU) that can fully take into account the context and improves the classification of the model. This study adds a layer based on attention mechanism (AM), which captures the context vector and gives keywords higher weight for text classification. Second, this study explains the authors’ model’s results with local interpretable model-agnostic explanations (LIME).

Design/methodology/approach

Bloom's taxonomy levels of cognition are commonly used as a reference standard for identifying e-learning contents. Many action verbs in Bloom's taxonomy, however, overlap at different levels of the hierarchy, causing uncertainty regarding the cognitive level expected. Some studies have looked into the cognitive classification of e-learning content but none has looked into learning objectives. On the other hand, most of these research papers just adopt classical machine learning algorithms. The main constraint of this study is the availability of annotated learning objectives data sets. This study managed to build a data set of 2,400 learning objectives, but this size remains limited.

Findings

This study’s experiments show that the proposed model achieves highest scores of accuracy: 90.62%, F1-score and loss. The proposed model succeeds in classifying learning objectives, which contain ambiguous verb from the Bloom’s taxonomy action verbs, while the same model without the attention layer fails. This study’s LIME explainer aids in visualizing the most essential features of the text, which contributes to justifying the final classification.

Originality/value

In this study, the main objective is to propose a model that outperforms the baseline models for learning objectives classification based on the six cognitive levels of Bloom's taxonomy. In this sense, this study builds the bidirectional GRU (BiGRU)-attention model based on the combination of the BiGRU algorithm with the AM. This study feeds the architecture with word2vec embeddings. To prove the effectiveness of the proposed model, this study compares it with four classical machine learning algorithms that are widely used for the cognitive classification of text: Bayes naive, logistic regression, support vector machine and K-nearest neighbors and with GRU. The main constraint related to this study is the absence of annotated data; there is no annotated learning objective data set based on Bloom’s taxonomy's cognitive levels. To overcome this problem, this study seemed to have no choice but to build the data set.

Book part
Publication date: 1 May 2019

Kai Ewing

Books serve as important information resources and provide space for reflection and identity-building for many lesbian, gay, bisexual, transgender, and queer/questioning…

Abstract

Books serve as important information resources and provide space for reflection and identity-building for many lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ+) people. Many in this community have experienced reduced feelings of isolation through engagement with the writings of others. Providing a safe space for such engagement is vital. Library and information science (LIS) professionals are in an optimal position to meet such needs, particularly when efforts are made to implement changes based on explicitly expressed concerns.

This chapter provides a case study of the LGBTQ Center of Durham, North Carolina, to illustrate how the organization is integrating the local LGBTQ+ community into its library by using the community’s own vocabulary and interests to inform the center’s practices and policies. The chapter also offers a guide to the locally responsive, LGBTQ+-specific classification system created for the LGBTQ Center of Durham’s library collection. This classification system was designed to represent library materials for its Durham and surrounding-area users in a useful, accessible, and respectful manner – a feat that the library committee did not feel could be accomplished using existing classification systems.

Building on the case study for applicability, the author makes recommendations for how LIS professionals who wish to better serve LGBTQ+ users can incorporate the community into their library and/or collection. The author provides additional suggestions for action, with varying levels of commitment, for library professionals and volunteers. Through resource development, training, collection development, and classification revision, libraries can more closely align their practices with the needs of users of all gender identities and sexual orientations.

Details

LGBTQ+ Librarianship in the 21st Century: Emerging Directions of Advocacy and Community Engagement in Diverse Information Environments
Type: Book
ISBN: 978-1-78756-474-9

Keywords

Book part
Publication date: 20 July 2017

Daniel Martínez-Ávila

This chapter reviews the historical tension between global and local interests in library classifications. More specifically, this chapter presents the concept and…

Abstract

This chapter reviews the historical tension between global and local interests in library classifications. More specifically, this chapter presents the concept and characteristics of the reader-interest classifications as they were reported in the literature of the past century, including its alleged advantages and detected shortcomings, in order to discuss their presence and consequences in current cases of reader-interest classifications such as BISAC. Following an implicit post-structuralist approach, issues such as the role of standardization and centralization in these projects, the focus and philosophy underlying the construction of these classifications, and the underlying global interests of the book industry are analyzed in order to determine the social consequences and viability of these local classifications. It is concluded that libraries that consider adopting a reader-interesting classification must really think of the interest of the users (in plural) and not only of the global book industry that dominates the development of the standards.

Details

The Organization of Knowledge
Type: Book
ISBN: 978-1-78714-531-3

Keywords

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