• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.387-399
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• 2021

This study mainly aims to examine the effect of intangible assets on the value relevance of the Gulf Cooperation Council (GCC)-listed non-financial firms. This study tested three types of models by using a large sample of non-financial firms listed in GCC countries as emerging markets from 2008 to 2016. The types of models are accounting information (earnings per share and book value of share) without intangible assets model, intangible assets model, and accounting information (earnings per share and book value of share) with intangible assets model. Ordinary least square (OLS) shows mixed results as intangible assets improve the value relevance of accounting information positively in UAE and negatively in Kuwait but not in other countries. The study documents a robust positive relationship between intangible assets and earnings quality in terms of value relevance in KSA and Qatar. The findings provide implications for policymakers, investors, and managers. The results suggest that intangible assets can improve the value relevance in emerging markets, such as GCC, as the need to organize the requirements of information disclosures on intangible assets and provide great transparency and additional disclosure of information about intangible assets and their components.

• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.189-206
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• 2014

The purposes of this study are to analyze relevance judgement of college students' problem solving process and suggest improvements for information literacy education in higher education. The in-depth interviews were conducted with 9 subjects to identify relevance judgement processes and problems. As a result, the main problems during relevance judgement processes were judgement about content of document aligned with subject's opinion, judgement about reliability of newspaper articles, shortage of relevance judgement time due to deadline of an assignment and judgement of relationship of documents and evaluation result. The recommendations for information literacy education are as follows: objective relevance judgement education, guidance of reliable information source;showing guideline of using reference information by professor and emphasis of engaging in information (4.1 stage of Big 6).

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.101-108
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• 2010

In this paper, how fast and accurate the companies provides exponentially increasing information to the users is the most important in the corporate competitiveness. The enhancement of the retrieval relevance became the important element in enhancing company competitiveness and it is required to provide the services that are beyond simple retrieval service for good quality search service. This paper proposes the effective scheme that enhances retrieval relevance by utilizing registered tag information. By proposed scheme, we can overcome the limitations of retrieval relevance that usual search engines provide. And we compare the proposed scheme with existing web retrieval service on retrieval relevance evaluation and related search keyword.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3149-3165
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• 2013

Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2728-2739
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• 1999

This paper proposes an effective fusion algorithm for retrieval results from heterogeneous information sources in federated digital libraries. The algorithm determines the population of documents retrieved from involved information sources for a given query and evaluates the degree of relevance between the query and the population. The evaluated results are used as relevance distribution information for collection fusion. The main informations used for the fusion are relevance distribution among collections, the population size N, and ranking information of relevant documents in their origin. We also present th performance evaluation of the algorithm by developing the prototype of a meta-searcher.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.55-70
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• 2014

Although a significant number of studies have been conducted in user-based relevance criteria, a need for further research still remains. The rational is associated with the following inadequacies: (1) research on young user groups, (2) research on the Web environment with multimedia resources, (3) research on the irrelevance criteria and implications to improve related systems and services. Accordingly, this study identified user - based relevance and irrelevance criteria, examining 40 middle school third grader students who use KERIS Edunet site. The results identified 16 relevance criteria and 8 irrelevance criteria. Major implications related to information system and service improvements.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.417-435
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• 2016

Relevance judgment is important in terms of improving the effectiveness of information retrieval systems, and it has been dominant for users to search and use images utilizing internet and digital technologies. However, in the field of image retrieval, there have been only a few studies in terms of identifying relevance criteria. The purpose of this study aims to identify and characterize the non-relevance criteria from the failed image searches. In order to achieve the purpose of this study, a total of 135 participants were recruited and a total of 1,452 criteria items were collected for this study. Analyses and identification on the data set found thirteen criteria such as 'topicality', 'visual content', 'accuracy', 'visual feature', 'completeness', 'appeal to user', 'focal point', 'bibliographic information', 'impression', 'posture', 'face feature', 'novelty', and 'time frame'. Among these criteria, 'visual content' and 'focal point' were introduced in this current study, while 'action' criterion identified in previous studies was not shown in this current study. When image needs and image uses are analyzed with these criteria, there are distinctive differences depending on different image needs and uses.

• Science of Emotion and Sensibility
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• v.15 no.3
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• pp.367-380
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• 2012

The purpose of this research was to implement and verify an information retrieval(IR) system based on users' relevance criteria for information search tasks. For this purpose, we implemented an IR system with a dynamic ranking model using users' relevance criteria varying with the types of information search task and evaluated this system through user experiment. 45 participants performed three information search tasks on both IR systems with a static and a dynamic ranking model. Three Information search tasks are fact finding search task, problem solving search task and decision making search task. Participants evaluated top five search results on 7 likert scales of relevance. We observed that the IR system with a dynamic ranking model provided more relevant search results compared to the system with a static ranking model. This research has significance in designing IR system for information search tasks, in testing the validity of user-oriented relevance judgement model by implementing an IR system for actual information search tasks and in relating user research to the improvement of an IR system.

• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.123-136
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• 2020

Purpose - This study is to verify the impact of the documentation of key audit matters on the value relevance of accounting information in accordance with the revised accounting audit standards in 2017. Investors will be able to identify the company's significant financial risks through key audit matters and use them to make investment decisions. Design/methodology/approach - From 2011 to 2019, the final sample is 290, based on the December settlement of accounts listed on the securities market. Ohlson (1995) was used to verify the incremental link between net income and the book value as a determinant of corporate value. Findings - First, the key audit matters in the financial industry was found to have a negative (-) effect that was significant to the value relevance of accounting Information. In addition, the value of the interaction between the key audit matters and the net income is a significant (+) relationship with the share price and the value of the interaction between the key audit matters and the book value is a significant (-) relationship with the share price. This means that the key audit matters is the determining factor of corporate value, positively reflects the accounting information in net income and negatively reflects the accounting information in book value. Second, among the key audit matters, the fair value assessment of financial instruments and the adequacy of premiums reserve have a significant impact on the value relevance of accounting information. Research implications or Originality - The results of this study suggest that investors recognize key audit matters as information about the company's major financial risks and reflect them differently in the value relevance of accounting information.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.89-96
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• 2000

Relevance feedback is a technique to learn the user's subjective perception of similarity between images, and has recently gained attention in Content Based Image Retrieval. Most relevance feedback methods assume that the individual features that are used in similarity judgments do not interact with each other. However, this assumption severely limits the types of similarity judgments that can be modeled In this paper, we explore a more sophisticated model for similarity judgments based on fuzzy measures and the Choquet Integral, and propose a suitable algorithm for relevance feedback, Experimental results show that the proposed method is preferable to traditional weighted- average techniques.