My favorite research is search engine interoperability, ontology, knowledge management and knowledge organization in general. Research has also been conducted in the field of public libraries and related issues.
Member of the Iranian Library and Information Science Association (ILISA)
Member of the Iranian Public Library Promotion Association (IPLPA)
Member of the National Elite Foundation
Knowledge and Information Organization and Management
Ontology and Thesaurus
Document Organization
Public Libraries
- Ph.D., Designing microdata schema for Iranian-Islamic information context's manuscripts and studying the reaction of web search engines to the records based on that schema, University of Isfahan [Isfahan - Iran]
- Master's degree, A Feasibility Study for Implementing Knowledge Management in the Academic Libraries of Isfahan City based on Bukowitz and William’s Model, University of Isfahan [Isfahan - Iran]
The main objective of this paper was to evaluate the user experience (UX) of students in higher education by conducting usability testing in the e-learning context, specifically utilizing the University of Isfahan (UI) Learning Management System (LMS). The survey method was used in the current study and to collect data we utilized random sampling to evaluate the usability aspects defined in ISO 9241-11 standards based on a modified system usability scale (SUS) involving 377 end-users. The data were analyzed using Microsoft Excel software and findings showed that SUS score for the University of Isfahan's LMS is 60.05 which falls in the 'OK usability' range and is acceptable. Also, we explored the features of AI-enhanced LMSs using a ranking question to comprehensively understand students' perspectives suggesting that Chatbots for support and intelligent content recommendations are among the most expected features for prominent educational outcomes. From the NPS assessment, -43 implies areas for improvement. © 2024 IEEE.
Digital Library Perspectives (20595816)40(2)pp. 244-263
Purpose: This study aims to adjust Thesis-type properties on Schema.org using metadata models and standards (MS) (Bibframe, electronic thesis and dissertations [ETD]-MS, Common European Research Information Format [CERIF] and Dublin Core [DC]) to enrich the Thesis-type properties for better description and processing on the Web. Design/methodology/approach: This study is applied, descriptive analysis in nature and is based on content analysis in terms of method. The research population consisted of elements and attributes of the metadata model and standards (Bibframe, ETD-MS, CERIF and DC) and Thesis-type properties in the Schema.org. The data collection tool was a researcher-made checklist, and the data collection method was structured observation. Findings: The results show that the 65 Thesis-type properties and the two levels of Thing and CreativeWork as its parents on Schema.org that corresponds to the elements and attributes of related models and standards. In addition, 12 properties are special to the Thesis type for better comprehensive description and processing, and 27 properties are added to the CreativeWork type. Practical implications: Enrichment and expansion of Thesis-type properties on Schema.org is one of the practical applications of the present study, which have enabled more comprehensive description and processing and increased access points and visibility for ETDs in the environment Web and digital libraries. Originality/value: This study has offered some new Thesis type properties and CreativeWork levels on Schema.org. To the best of the authors’ knowledge, this is the first time this issue is investigated. © 2023, Emerald Publishing Limited.
Iranian Journal of Information Processing Management (22518231)39(2)pp. 565-598
Information fusion is a vital process in information management systems which aims to merge information from multiple sources to provide a more comprehensive and accurate view of specialized domain. In structured information management systems there are several methods for aggregating, consolidating, and fusioning information, but their approaches have not yet provided a clear pattern. The aim of the current research is to explain the concept and appropriate models of information fusion in information management systems and its use in relationship-based databases such as thesaurus. The research method is a conceptual type with an analytical approach. The research population consisted of texts and outputs in the field of information fusion, and the data collected by the library method. The findings showed that information fusion models are in four general categories of models based on information flow, workflow and activity, roles and functions of entities, and understanding concepts. The Omnibus workflow and activity model and the model based on the roles and functions of Endsley's entity as selected models according to the basic JDL are suitable for use in relationship-based information management systems such as thesauruses and ontologies, and they have the ability to be used with some changes. The main disadvantage of the reviewed information fusion models is not paying attention to the characteristics of specific information structures such as thesauruses. Not considering role of expert users in information systems based on user decisions that have the task of extracting specialized information and ignoring the collective participation system to solve complex problems, including finding similarities and solving it in the mass of information, not describing the required functions to solve the problems, managing the effects in case of system or user errors and restoring fusioned and consolidated information, as well as non-implementation of methods with operational examples in such structures, can be counted among these problems. In general, in each model of information fusion in information management systems based on thesaurus, the general processes of finding similarities, examining similarities, aggregating parameters and information fusion and managing the effectiveness of sub-systems should be considered. Unlike traditional information fusion methods that focus more on merge data, semantic information fusion emphasizes fusioning related knowledge and concepts stored in thesauruses instead of merging data and information. Therefore, it is suggested to pay attention to semantic approaches in the process of integrating and fusioning new models. © 2024 Iranian Research Institute for Scientific Information and Documentation. All rights reserved.
