Raheem SarwarManchester Metropolitan University | MMU · OTEHM
Raheem Sarwar
Doctor of Philosophy
About
54
Publications
7,158
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
646
Citations
Introduction
Education
September 2015 - August 2018
September 2012 - August 2014
Information Technology University
Field of study
- Computer Science
September 2008 - August 2012
Publications
Publications (54)
Intelligent abstractive text summarization of scholarly publications refers to machine-generated summaries that capture the essential ideas of an article while maintaining semantic coherence and grammatical accuracy. As information continues to grow at an overwhelming rate, text summarization has emerged as a critical area of research. In the past,...
The present work re-evaluates the evaluation method for text summarization tasks. Two state-of-the-art assessment measures e.g., Recall-Oriented Understudy for Gisting Evaluation (ROUGE) and Bilingual Evaluation Understudy (BLEU) are discussed along with their limitations before presenting a novel evaluation metric. The evaluation scores are signif...
In the modern era, where satellite imagery is vital for applications like ecological monitoring and national security, ensuring the safety and integrity of these data repositories is crucial. This study presents an improved satellite image encryption technique that combines the cryptographic strength of the circulant matrix in the Hill cipher with...
The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due to changes in certain supplements, medical conditions, obesity, and diet, which causes kidney function and ultimately leads to complications such as chronic kidney disease, kidney failure, and other r...
Image caption generation has emerged as a remarkable development that bridges the gap between Natural Language Processing (NLP) and Computer Vision (CV). It lies at the intersection of these fields and presents unique challenges, particularly when dealing with low-resource languages such as Urdu. Limited research on basic Urdu language understandin...
In response to the growing number of diabetes cases worldwide, Our study addresses the escalating issue of diabetic eye disease (DED), a significant contributor to vision loss globally, through a pioneering approach. We propose a novel integration of a Genetic Grey Wolf Optimization (G-GWO) algorithm with a Fully Convolutional Encoder-Decoder Netwo...
This paper focuses on exploring the differences in inquiries made by men and women within a religious context. Additionally, we aim to ascertain whether it’s feasible to forecast the popularity of answers and the factors contributing to their popularity. To achieve this, we compile a new dataset comprising 40,000 question-answer pairs categorized b...
Transportation systems primarily depend on vehicular flow on roads. Developed countries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous iss...
Authorship attribution involves determining the original author of an anonymous text from a pool of potential authors. Author attribution task has applications in several domains, such as plagiarism detection, digital text forensics, and information retrieval. While these applications extend beyond any single language, existing research has predomi...
In this investigation, we propose a solution for the author’s gender identification task called AGI-P. This task has several real-world applications across different fields, such as marketing and advertising, forensic linguistics, sociology, recommendation systems, language processing, historical analysis, education, and language learning. We creat...
The rapid growth of the internet in recent years has produced an enormous amount of data. The significant chunk of this data is unstructured. This unstructured data requires critical analysis and modelling to become useful for decision making. Due to the wild spread of internet across the globe, several applications are being developed every day. T...
This study highlights the scientific legacy and impact of Dr Saeed-Ul Hassan’s research on the world of science. He was a remarkable researcher in the fields of scientometrics, altmetrics, artificial intelligence, and data science, as evidenced by the Eugene Garfield Awards he received for innovation in citation analysis in 2017 and 2022. Based on...
This study highlights the scientific legacy and impact of Dr Saeed-Ul Hassan’s research on the world of science. He was a remarkable researcher in the fields of scientometrics, altmetrics, artificial intelligence, and data science, as evidenced by the Eugene Garfield Awards he received for innovation in citation analysis in 2017 and 2022. Based on...
Biographical writing is one of the earliest and most extensive forms of Arabic literature. Some scholars tend to assume that classical Arabic biographies, widely known as Tarāǧim, arose in conjunction with the study of the reliability of the Hadith transmitters (the reciters of the Prophet Mohammad's sayings) which lead to a proliferation of biogra...
Urdu is morphologically rich language and lacks the resources available in English. While several studies on the image captioning task in English have been published, this is among the pioneer studies on Urdu generative image captioning. The study makes several key contributions: (i) it presents a new dataset for Urdu image captioning, and (ii) it...
Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely different set of skills and knowledge. It is essential to fill the gap between the industry's required skills and those taugh...
This article aims to exploit social exchanges on scientific literature, specifically tweets, to analyse social media users’ sentiments towards publications within a research field. First, we employ the SentiStrength tool, extended with newly created lexicon terms, to classify the sentiments of 6,482,260 tweets associated with 1,083,535 publications...
Given a set of target language documents and their translators, the translator attribution task aims at identifying which translator translated which documents. The attribution and the identification of the translator’s style could contribute to fields including translation studies, digital humanities, and forensic linguistics. To conduct this inve...
In recent years, author gender identification has gained considerable attention in the fields of computational linguistics and artificial intelligence. This task has been extensively investigated for resource-rich languages such as English and Spanish. However, researchers have not paid enough attention to perform this task for Urdu articles. First...
The authorship identification task aims at identifying the original author of an anonymous text sample from a set of candidate authors. It has several application domains such as digital text forensics and information retrieval. These application domains are not limited to a specific language. However, most of the authorship identification studies...
Machine learning specific scholarly full-text documents contain a number of result-figures expressing valuable data, including experimental results, evaluations, and cross-model comparisons. The scholarly search system often overlooks this vital information while indexing important terms using conventional text-based content extraction approaches....
Machine learning specific scholarly full-text documents contain a number of result-figures expressing valuable data, including experimental results, evaluations, and cross-model comparisons. The scholarly search system often overlooks this vital information while indexing important terms using conventional text-based content extraction approaches....
The primary purpose of this paper is author verification of the Nahj Al-Balagha, a book attributed to Imam Ali and over which Sunni and Shi'i Muslims are proposing different theories. Given the morphologically complex nature of Arabic, we test whether morphological segmentation, applied to the book and works by the two authors suspected by Sunnis t...
There has not been any research that provides an evaluation of the linguistic features extracted from the matn (text) of a Hadith. Moreover, none of the fairly large corpora are publicly available as a benchmark corpus for Hadith authenticity, and there is a need to build a “gold standard” corpus for good practices in Hadith authentication. We writ...
Most existing studies are focused on popular languages like English, Spanish, Chinese, Japanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning model for the sentiments expressed in this under-resourced language. We develop an open-source co...
Most existing studies are focused on popular languages like English, Spanish, Chinese, Japanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning model for the sentiments expressed in this under-resourced language. We develop an open-source co...
Most existing studies are focused on popular languages like English, Spanish, Chinese, Japanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning model for the sentiments expressed in this under-resourced language. We develop an open-source co...
While word segmentation is a solved problem in many languages, it is still a challenge in continuous-script or low-resource languages.
Like other NLP tasks, word segmentation is domain-dependent, which can be a challenge in low-resource languages like Thai and Urdu since there can be domains with insufficient data.
This investigation proposes a new...
This paper aims at an important task of computing the webometrics university ranking and investigating if there exists a correlation between webometrics university ranking and the rankings provided by the world prominent university rankers such as QS world university ranking, for the time period of 2005–2016. However, the webometrics portal provide...
This article aims to exploit social exchanges on scientific literature, specifically tweets, to analyse social media users' sentiments towards publications within a research field. First, we employ the SentiStrength tool, extended with newly created lexicon terms, to classify the sentiments of 6,482,260 tweets associated with 1,083,535 publications...
We argue that classic citation-based scientific document clustering approaches, like co-citation or Bibliographic Coupling, lack to leverage the social-usage of the scientific literature originate through online information dissemination platforms, such as Twitter. In this paper, we present the methodology Tweet Coupling, which measures the similar...
Native Language Identification (NLI) aims at identifying the native languages of authors by analyzing their text samples written in a non-native language. Most existing studies investigate this task for educational applications such as second language acquisition and require the learner corpora. This article performs NLI in a challenging context of...
Authorship identification helps to identify the true author of a given anonymous document from a set of candidate authors. The applications of this task can be found in several domains, such as law enforcement agencies and information retrieval. These application domains are not limited to a specific language, community, or ethnicity. However, most...
Stylometry has been successfully applied to perform authorship identification of singleauthor documents (AISD). The AISD task is concerned with identifying the original author of an anonymous document from a group of candidate authors. However, AISD techniques are not applicable to the authorship identification of multi-author documents (AIMD). Unl...
Traditional bibliometric techniques gauge the impact of research through quantitative indices based on the citations data. However, due to the lag time involved in the citation-based indices, it may take years to comprehend the full impact of an article. This paper seeks to measure the early impact of research articles through the sentiments expres...
This chapter presents a novel scientific research landscape of the Gulf Cooperation Council (GCC) in order to access the research productivity, scholarly impact, and international collaborations across all GCC countries over the time period of 2008–2018, using the Scopus database. While we observe a significant increase in investing the resources i...
Purpose
The purpose of this paper is to analyze the scientific collaboration of institutions and its impact on institutional research performance in terms of productivity and quality. The researchers examined the local and international collaborations that have a great impact on institutional performance.
Design/methodology/approach
Collaboratio...
Authorship attribution aims at identifying the original author of an anonymous text from a given set of candidate authors and has a wide range of applications. The main challenge in authorship attribution problem is that the real-world applications tend to have
hundreds of authors
, while each author may have a small number of text samples, e.g.,...
Cross-lingual authorship identification aims at finding the author of an anonymous document written in one language by using labeled documents written in other languages. The main challenge of cross-lingual authorship identification is that the stylistic markers (features) used in one language may not be applicable to other languages in the corpus....
This study analyzes the intra- and international collaboration of 11 member states of the Organization of Islamic Cooperation
(OIC) in science and technology (S&T) disciplines in the period 1996–2010, by applying various bibliometric indicators along
with publication and citation counts and our proposed average collaboration strength index, that me...
This case study analyzes scientific research landscape of the Islamic World in order to access the research productivity, scholarly impact and international collaborations across all Science and Technology (S&T) areas over the time period of 2000–2011, using the Scopus database. While Turkey is clearly leading among the Islamic countries, Iran take...