Construction of the structural definition-based terminology ontology system and semantic search evaluation

2016 ◽  
Vol 34 (4) ◽  
pp. 705-732 ◽  
Author(s):  
Young Man Ko ◽  
Min Sun Song ◽  
Seung Jun Lee
Keyword(s):  
Keyword Search ◽  
Relevant Information ◽  
Semantic Search ◽  
Research Papers ◽  
Inference Control ◽  
Content Type ◽  
Search Results ◽  
Input Ratio ◽  
Structural Definition ◽  
Term Data

Purpose The purpose of this paper is to construct a structural definition-based terminology ontology system that defines the meanings of academic terms on the basis of properties and links terms with properties that are structured by conceptual categories (classes). This study also aims to test the possibility of semantic searches by generating inference rules and setting very complicated search scenarios. Design/methodology/approach For the study, 55,236 keywords from the articles of the “Korea Citation Index” were structurally defined and relationships among terms and properties were built. Then, the authors converted the RDB data into RDF and designed ontologies using the ontology developing tool Protégé. The authors also tested the designed ontology with the inference engine of the Protégé editor. The generated reference rules were tested by TBox and SPARQL queries. Findings The authors generated inference control rules targeting high-input-ratio data in the properties of classes by calculating the input ratio of real input data in the system, and then the authors executed a semantic search by SPARQL query by setting very complicated search scenarios, for which it would be difficult to deduce results via a simple keyword search. As a result, it was confirmed that the search results show the logical combination of semantically related term data. Practical implications The proposed terminology ontology system was constructed with the author keywords from research papers, it will be useful in searching the research papers which include the keywords as search results by the complex combination of semantic relation. And the Structural Terminology Net database could be utilized as an index database in retrieval services and the mining of informal big data through the application of well-defined semantic concepts to each term. Originality/value This paper presented a methodology for supporting IR using expanded queries based on a novel model of structural terminology-based ontology. The user who wants to access the specific topic can create query that brings the semantically relevant information. The search results show the logical combination of semantically related term data, which would be difficult to deduce results via traditional IR systems.

Construction of metadata database structured by conceptual elements of text structure and semantic search evaluation of Korean studies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Young Man Ko ◽  
Min Sun Song ◽  
Seung Jun Lee
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Interdisciplinary Studies ◽  
Text Structure ◽  
Semantic Search ◽  
Research Articles ◽  
Content Type ◽  
Search Results ◽  
Korean Studies ◽  
Data Points

Purpose This study aims to develop metadata of conceptual elements based on the text structure of research articles on Korean studies, to propose a search algorithm that reflects the combination of semantically relevant data in accordance with the search intention of research paper and to examine the algorithm whether there is a difference in the intention-based search results. Design/methodology/approach This study constructed a metadata database of 5,007 research articles on Korean studies arranged by conceptual elements of text structure and developed F1(w)-score weighted to conceptual elements based on the F1-score and the number of data points from each element. This study evaluated the algorithm by comparing search results of the F1(w)-score algorithm with those of the Term Frequency- Inverse Document Frequency (TF-IDF) algorithm and simple keyword search. Findings The authors find that the higher the F1(w)-score, the closer the semantic relevance of search intention. Furthermore, F1(w)-score generated search results were more closely related to the search intention than those of TF-IDF and simple keyword search. Research limitations/implications Even though the F1(w)-score was developed in this study to evaluate the search results of metadata database structured by conceptual elements of text structure of Korean studies, the algorithm can be used as a tool for searching the database which is a tuning process of weighting required. Practical implications A metadata database based on text structure and a search method based on weights of metadata elements – F1(w)-score – can be useful for interdisciplinary studies, especially for semantic search in regional studies. Originality/value This paper presents a methodology for supporting IR using F1(w)-score—a novel model for weighting metadata elements based on text structure. The F1(w)-score-based search results show the combination of semantically relevant data, which are otherwise difficult to search for using similarity of search words.

Artificial intelligence-based training learning from application

2019 ◽  
Vol 33 (2) ◽  
pp. 20-23 ◽  
Author(s):  
Ashwani Kumar Upadhyay ◽  
Komal Khandelwal
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Theoretical Foundation ◽  
Relevant Information ◽  
Relevant Research ◽  
Research Papers ◽  
Content Type ◽  
Training Systems ◽  
Effectiveness Of Training ◽  
Practical Implications

Purpose This paper aims to discuss the rationale, theoretical foundation, application, and future of artificial intelligence (AI)-based training. Design/methodology/approach A review of relevant research papers, articles and case studies is done to highlight developments in research and practice. Findings AI-based training systems are smart, intelligent and expert in handling queries. These systems can curate content, grade, evaluate, and provide feedback to trainee, thus making learning adaptive and contextual. Practical implications Application of AI is vital in the field of training, as it helps personalization and customization of training programs to increase the effectiveness of training. Originality/value Executives and researchers can save time by reading relevant information on the linkage, and its contribution to AI is discussed and summarized in an easy to read format.

GeTFIRST: ontology-based keyword search towards semantic disambiguation

2015 ◽  
Vol 11 (4) ◽  
pp. 442-467 ◽  
Author(s):  
Hoang-Minh Nguyen ◽  
Hong-Quang Nguyen ◽  
Khoi-Nguyen Tran ◽  
Xuan-Vinh Vo
Keyword(s):  
Information Retrieval ◽  
Information Integration ◽  
Keyword Search ◽  
Classification Tree ◽  
Empirical Evaluation ◽  
Relevant Information ◽  
Ranking Algorithm ◽  
Content Type ◽  
Information Retrieval Methods ◽  
Search Approach

Purpose – This paper aims to improve the semantic-disambiguation capability of an information-retrieval system by taking advantages of a well-crafted classification tree. The unstructured nature and sheer volume of information accessible over networks have made it drastically difficult for users to seek relevant information. Many information-retrieval methods have been developed to address this problem, and keyword-based approach is amongst the most common approach. Such an approach is often inadequate to cope with the conceptualization associated with user needs and contents. This brings about the problem of semantic ambiguation that refers to the disagreement in meaning of terms between involving parties of a communication due to polysemy, leading to increased complexity and lesser accuracy in information integration, migration, retrieval and other related activities. Design/methodology/approach – A novel ontology-based search approach, named GeTFIRST (short for Graph-embedded Tree Fostering Information Retrieval SysTem), is proposed to disambiguate keywords semantically. The contribution is twofold. First, a search strategy is proposed to prune irrelevant concepts for accuracy improvement using our Graph-embedded Tree (GeT)-based ontology. Second, a path-based ranking algorithm is proposed to incorporate and reward the content specificity. Findings – An empirical evaluation was performed on United States Patent And Trademark Office (USPTO) patent datasets to compare our approach with full-text patent search approaches. The results showed that GeTFIRST handled the ambiguous keywords with higher keyword-disambiguation accuracy than traditional search approaches. Originality/value – The search approach of this paper copes with the semantic ambiguation by using our proposed GeT-based ontology and a path-based ranking algorithm.

A systematic literature review of healthcare supply chain and implications of future research

2019 ◽  
Vol 13 (4) ◽  
pp. 405-435 ◽  
Author(s):  
Anuj Dixit ◽  
Srikanta Routroy ◽  
Sunil Kumar Dubey
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Inventory Management ◽  
Cold Chain ◽  
Future Research ◽  
Research Papers ◽  
Content Type ◽  
Drug Manufacturing ◽  
Customer Training

Purpose This paper aims to review the healthcare supply chain (HSC) literature along various areas and to find out the gap in it. Design/methodology/approach In total, 143 research papers were reviewed during 1996-2017. A critical review was carried out in various dimensions such as research methodologies/data collection method (empirical, case study and literature review) and inquiry mode of research methodology (qualitative, quantitative and mixed), country-specific, targeted area, research aim and year of publication. Findings Supply chain (SC) operations, performance measurement, inventory management, lean and agile operation, and use of information technology were well studied and analyzed, however, employee and customer training, tracking and visibility of medicines, cold chain management, human resource practices, risk management and waste management are felt to be important areas but not much attention were made in this direction. Research limitations/implications Mainly drug and vaccine SC were considered in current study of HSC while SC along healthcare equipment and machine, hospitality and drug manufacturing related papers were excluded in this study. Practical implications This literature review has recognized and analyzed various issues relevant to HSC and shows the direction for future research to develop an efficient and effective HSC. Originality/value The insight of various aspects of HSC was explored in general for better and deeper understanding of it for designing of an efficient and competent HSC. The outcomes of the study may form a basis to decide direction of future research.

scholarly journals Development of Intelligent Information System for Digital Cultural Contents

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 238
Author(s):  
Yuna Hur ◽  
Jaechoon Jo
Keyword(s):  
Information System ◽  
User Satisfaction ◽  
Keyword Search ◽  
Relevant Information ◽  
Matter Content ◽  
System Stability ◽  
Knowledge Network ◽  
Intelligent Information ◽  
Subject Matter Content ◽  
Depth Interviews

A significant amount of digital cultural contents is shared online, but learners do not know where subject matter content is or how to find it. Therefore, there is a need for a service to improve educational quality by effectively providing relevant information in response to searches for content that is useful to learners. This study developed and tested the usability and utility of an intelligent information system that effectively searches and visualizes digital cultural contents. The system collects data on digital cultural contents, automatically classifies them, and creates content triple data to automatically display the results with a 3D timeline, knowledge network map, and keyword relation network map through content search, triple search, and keyword search. We also conducted a survey and in-depth interviews to verify users’ satisfaction with respect to the use and utility of the system. For the experiment, we developed survey questions to measure user satisfaction and conducted in-depth interviews regarding the system’s utility with a total of 65 subjects. The results show that the response for satisfaction with regard to the use and utility was generally “satisfied”. In addition, the system stability was evaluated as “high”.

scholarly journals What people study when they study Tumblr

2017 ◽  
Vol 73 (3) ◽  
pp. 528-554 ◽  
Author(s):  
Rose Attu ◽  
Melissa Terras
Keyword(s):  
Social Media ◽  
Research Papers ◽  
Content Type ◽  
Long Form ◽  
Media Research ◽  
Access To Data ◽  
Social Networking Website ◽  
Conference Papers ◽  
Published Research ◽  
Practical Implications

Purpose Since its launch in 2007, research has been carried out on the popular social networking website Tumblr. The purpose of this paper is to identify published Tumblr-based research, classify it to understand approaches and methods, and provide methodological recommendations for others. Design/methodology/approach Research regarding Tumblr was identified. Following a review of the literature, a classification scheme was adapted and applied, to understand research focus. Papers were quantitatively classified using open coded content analysis of method, subject, approach, and topic. Findings The majority of published work relating to Tumblr concentrates on conceptual issues, followed by aspects of the messages sent. This has evolved over time. Perceived benefits are the platform’s long-form text posts, ability to track tags, and the multimodal nature of the platform. Severe research limitations are caused by the lack of demographic, geo-spatial, and temporal metadata attached to individual posts, the limited Advanced Programming Interface, restricted access to data, and the large amounts of ephemeral posts on the site. Research limitations/implications This study focusses on Tumblr: the applicability of the approach to other media is not considered. The authors focus on published research and conference papers: there will be book content which was not found using the method. Tumblr as a platform has falling user numbers which may be of concern to researchers. Practical implications The authors identify practical barriers to research on the Tumblr platform including lack of metadata and access to big data, explaining why Tumblr is not as popular as Twitter in academic studies. Social implications This paper highlights the breadth of topics covered by social media researchers, which allows us to understand popular online platforms. Originality/value There has not yet been an overarching study to look at the methods and purpose of those who study Tumblr. The authors identify Tumblr-related research papers from the first appearing in 2011 July until 2015 July. The classification derived here provides a framework that can be used to analyse social media research, and in which to position Tumblr-related work, with recommendations on benefits and limitations of the platform for researchers.

Private ethical fund investors across countries and time: a survey-based review

2015 ◽  
Vol 7 (4) ◽  
pp. 379-411 ◽  
Author(s):  
Anett Wins ◽  
Bernhard Zwergel
Keyword(s):  
Keyword Search ◽  
Relevant Literature ◽  
Future Research ◽  
Socially Responsible ◽  
Screening Criteria ◽  
Content Type ◽  
Responsible Investment ◽  
Private Investors ◽  
Ethical Funds ◽  
Fund Portfolio

Purpose – This paper aims to provide an overview of the literature to point out similarities and differences among private ethical investors across countries and time. Over the past three decades, many surveys have been conducted to advance the understanding of the demographic characteristics, motivation and morals of private ethical investors across countries and time. To date, the survey-based evidence on private investors into ethical funds is geographically rather segmented, and the research questions are fairly diverse. This permits only very temporally or regionally selective conclusions. Thereby, the authors identify interesting topics for future research. Design/methodology/approach – To identify the relevant literature for our review, the authors carried out a structured Boolean keyword search using major library services and databases. Findings – When questions about negative screening criteria are presented in a direct investment context, the consensus of private ethical investors “worldwide” (on average) is that social screening issues are most important, followed by ecological and moral topics. The percentage of ethical funds in the fund portfolio of the average private ethical investor in Europe seems to increase when the investor exhibits high degrees of pro-social attitudes and perceived consumer effectiveness. European private ethical investors are of the opinion that ethical funds perform worse but are less risky than conventional funds. Practical implications – The authors make suggestions on how investment companies should design their funds so that they can attract more socially responsible investors. Originality/value – The paper is of particular value because it focuses on private investors in the fast growing retail market of socially responsible investment funds.

Reconfigurable manufacturing system: a systematic review, meta-analysis and future research directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Pansare ◽  
Gunjan Yadav ◽  
Madhukar R. Nagare
Keyword(s):  
Manufacturing System ◽  
Meta Analysis ◽  
Future Research ◽  
Future Trends ◽  
Reconfigurable Manufacturing ◽  
Research Papers ◽  
Reconfigurable Manufacturing System ◽  
Content Type ◽  
Related Research ◽  
And Performance

Purpose Uncertainties in manufacturing and changing customer demands force manufacturing industries to adopt new strategies, such as the reconfigurable manufacturing system (RMS). To improve the implementation and performance of RMS, it is necessary to review the available literature and identify future trends in this field. This paper aims to analyze existing literature and to see trends in RMS-related research. Design/methodology/approach The systematic literature review and analysis of RMS-related research papers from 1999 to 2020 is carried out in this literature. The selected studies are analyzed based on the year of publication, journals, publishers, active authors, research design, countries, enablers, barriers, performance evaluation parameters and universities. Findings After the analysis of selected RMS-related research papers, the top countries, universities, journals, publishers and authors are identified in this domain. Research themes and trends in research are identified in this study. Besides, it has been noted that there is a need for further research in this domain and for the creation of a generalized framework that can guide researchers and practitioners to increase RMS adoption. Practical implications Research insights, guidance and observations from this paper are provided to RMS-related researchers and practitioners. Important research gaps are identified in this study, which can provide direction for future research and trends in RMS research. Originality/value The study presented focuses mainly on the method of collecting, organizing, capturing, interpreting and analyzing data to provide more insight into RMS to identify future trends in research.

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