جستجوی مقالات مرتبط با کلیدواژه ": semantic search" در نشریات گروه "کتابداری و مدیریت اطلاعات"

Various studies show that lexical or keyword search is not enough, because in this search the meaning of words and semantic relationships between keywords are ignored and semantic understanding is not achieved in this search. The purpose of this research is to investigate and measure the semantic search of users. Semantic search refers to a search that goes beyond the traditional search, i.e., the matching of the keywords of the search request with the keywords of the documents in the system and seeks to understand the meaning and semantic relationships between the keywords in the user's search request, which is used with the development and expansion of the semantic web and ontologies. The focus of this search is on obtaining a higher level of meaning from documents and inquiries and based on its content, which this high level meaning may be provided by ontologies. Semantic search expands the meaning and seeks machine understanding of the user's intent, query request and relationships between words and elevates the user's search strategy to a meaningful experience. In fact, semantic search describes the effort to produce accurate results by understanding the searcher's intent, texture and context of the query request, and the relationship between words. This search is of great interest to users and researchers due to its many advantages and applications. But besides the many advantages, it has over traditional and keyword search. It also has some problems and complications that elimination of these problems leads to the improvement and promotion of semantic search and helps users a lot.

The present study is quantitative in terms of approach and applied in terms of purpose, which has been done by survey method. The data collection tool was a researcher-made questionnaire. The statistical population of the study was 189 Iranian researchers who had published at least a research article on COVID-19, which Indexed in PubMed.

Based on the research findings, from the perspective of Iranian researchers, the degree of recall and precision to semantic search in the PubMed is moderate (3). The amount of semantic gap in semantic search is relatively high (>3), the degree of accuracy and precision in retrieving results in semantic search is moderate (3), the degree of conceptual relevance in semantic search is moderate (3), the rate of retrieval of meaningful multi-word concepts in semantic search is moderate (3) and the rate of improvement and upgrade of overall performance in semantic search is relatively high (>3) in semantic searches at the database has been extensive.

The results of the research in general showed that semantic search is a dynamic and challenging search that despite its various strengths and advantages for users in research, but still has its weaknesses and drawbacks that should be reviewed and revised by semantic search support experts such as ontology designers for the semantic search system. Understanding, identifying, and eliminating these weaknesses and problems, make semantic search to be a better way to respond to researchers for their research, as a result, researchers and users can achieve to richer results for compile their research work.

In order to increase in relevant retrieved results and users satisfaction achievement, Information retrieval systems, are seeking a way to change keyword-based search to concept-based search. These systems use the tools that can convert terms to concepts. Over the years, this provided the basis of tools production such as classification schema, vocabularies, subject headings and thesauri. Recently, ontologies use in Complementing of this process. The main problem of this research is that The Great information retrieval systems of the world that claim to use of ontologies and thesauri how use the semantic features of these tools in their information retrieval process. In this paper 7 information retrieval systems due use of these tools, were selected. The semantic features presented in form of research checklist with literature review. These features include 5 general categories concept search, synonyms search, suggestion for search, use of ontologies and display. The researcher examined these features with structured observation in form of checklist. Though these systems use these tools for searching and retrieving, but don`t show the expected features. In studied factors, ERIC database and national library of Australia achieved the maximum scores (32 and 24) and national archive of Australia and Britain museum had minimum scores (12 and 13).