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Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

Web services composition engineering (WSCE) is a big challenge because of the increasing complexity, openness and extensibility of services based on the information system (IS). In the absence of an adequate framework for IS engineering, the authors assume that the overall problem is consequently no longer easy to resolve. This paper aims to explore some of the issues underlying WSCE through a framework, which is built based on the state of the art. The proposed framework is structured around five views that mainly highlight aspects of personalization and security concerns. The main objectives of this framework are: to help understand and clarify the basics of the WSCE domain; to evaluate web services composition (WSC) methods; to analyze and compare existing personalization, secure methods and identify new research axes; and to identify the main criteria of the ongoing approach for the design of a secure IS based on personalized WSC.

This work develops a framework that is used as an analytical study to compare the existing WSCE methods and come up with research issues. Then, the proposed framework is considered as an abstract model for the new WSCE approach.

A set of criteria that the proposed framework should consider when developing a new approach to a secure IS based on personalized WSs composition.

The paper has theoretical implications as the personalization and security issues provide a research roadmap toward the realization of an approach for the design of a secure IS based on personalized WSs composition.

As proof, the authors are interested in a web services repository of a real mall. To do this, the authors deployed the application in a cloud environment and observed the results of personalization and security concepts in WSCE.

None of the existing comparison frameworks has raised both personalization and security issues in WSs composition, while personalization and security must be present in the whole composition process.

Topic segmentation is one of the active research fields in natural language processing. Also, many topic segmenters have been proposed. However, the current challenge of researchers is the improvement of these segmenters by using external resources. Therefore, the purpose of this paper is to integrate study and evaluate a new external semantic resource in topic segmentation.

New topic segmenters (TSS-Onto and TSB-Onto) are proposed based on the two well-known segmenters C99 and TextTiling. The proposed segmenters integrate semantic knowledge to the segmentation process by using a domain ontology as an external resource. Subsequently, an evaluation is made to study the effect of this resource on the quality of topic segmentation along with a comparative study with related works.

Based on this study, the authors showed that adding semantic knowledge, which is extracted from a domain ontology, improves the quality of topic segmentation. Moreover, TSS-Ont outperforms TSB-Ont in terms of quality of topic segmentation.

The main limitation of this study is the used test corpus for the evaluation which is not a benchmark. However, we used a collection of scientific papers from well-known digital libraries (ArXiv and ACM).

The proposed topic segmenters can be useful in different NLP applications such as information retrieval and text summarizing.

The primary original contribution of this paper is the improvement of topic segmentation based on semantic knowledge. This knowledge is extracted from an ontological external resource.