Search results

1 – 2 of 2
To view the access options for this content please click here
Article
Publication date: 14 May 2019

Ahsan Mahmood, Hikmat Ullah Khan, Zahoor Ur Rehman, Khalid Iqbal and Ch. Muhmmad Shahzad Faisal

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the…

Abstract

Purpose

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the named entities in a computer readable text having an annotation of categorization tags for information extraction. NER is an active research area in information management and information retrieval systems. NER serves as a baseline for machines to understand the context of a given content and helps in knowledge extraction. Although NER is considered as a solved task in major languages such as English, in languages such as Urdu, NER is still a challenging task. Moreover, NER depends on the language and domain of study; thus, it is gaining the attention of researchers in different domains.

Design/methodology/approach

This paper proposes a knowledge extraction framework using finite-state transducers (FSTs) – KEFST – to extract the named entities. KEFST consists of five steps: content extraction, tokenization, part of speech tagging, multi-word detection and NER. An extensive empirical analysis using the data corpus of Urdu translation of Sahih Al-Bukhari, a widely known hadith book, reveals that the proposed method effectively recognizes the entities to obtain better results.

Findings

The significant performance in terms of f-measure, precision and recall validates that the proposed model outperforms the existing methods for NER in the relevant literature.

Originality/value

This research is novel in this regard that no previous work is proposed in the Urdu language to extract named entities using FSTs and no previous work is proposed for Urdu hadith data NER.

Details

The Electronic Library , vol. 37 no. 2
Type: Research Article
ISSN: 0264-0473

Keywords

To view the access options for this content please click here
Article
Publication date: 1 February 2021

Junaid Aftab, Huma Sarwar, Anam Amin and Alina Kiran

Leadership has a decisive role in the success of all types of businesses and firms, including small- and medium-sized enterprises (SMEs), and the ethical behavior of…

Abstract

Purpose

Leadership has a decisive role in the success of all types of businesses and firms, including small- and medium-sized enterprises (SMEs), and the ethical behavior of leaders is a key component which brings a sense of respect, fulfillment, trustworthiness and acceptance among the employees, which later become visible in their job performance (JP). This study aims to check the immediate effect of ethical leadership (EL) on employee’s JP (EJP) and also explore the indirect mediating effect of corporate social responsibility (CSR) on this EL and EJP nexus.

Design/methodology/approach

Primary data was obtained from the employees of manufacturing SMEs of Northern Italy using a cross-sectional design from the end of 2019 to the start of 2020. This paper circulated 450 self-administered questionnaires using simple random sampling, and 202 (44.88%) valid questionnaires were returned. The PROCESS macro was performed using statistical package for social sciences to ensure whether or not EL affects EJP and is there any mediation effect of CSR present in this nexus.

Findings

The results indicate that EL has a strong positive connection with EJP and CSR. Interestingly, CSR positively influences EJP. Furthermore, the results also report the strong mediating effect of CSR in the nexus of EL and EJP.

Originality/value

This scholarly work seeks to contribute not only to the literature of EL and EJP but also enriches the understanding of this EL-EJP association by highlighting the indirect effect of mediating variable CSR in the SME sector.

Details

Social Responsibility Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1747-1117

Keywords

1 – 2 of 2