• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1263-1265
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• 1996

IEC1131-3 Specification of Programming Controller is established in 1994 and consists of 3 graphical languages and 2 textual languages. It is used in PLC and small scale controller because of its uniformity and extensibility. This paper describes Soft Logic Designer which is a graphical and textual programming editor for IEC1131-3 programming languages. Soft Logic Designer is developed with Object Orient Language, C++ under Microsoft Windows 95. It has two graphic editors for Sequential Function Chart and Function Block Diagram and one textual editor for Structured Text. Users can efficiently write high-level programs with mouse and menu buttons.

• The Journal of Industrial Distribution & Business
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• v.12 no.3
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• pp.21-29
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• 2021

Purpose: The cosmetic industry is one of the significant sectors of the economy that has attracted a wide range of players due to the fast growth rate. The purpose of this research is to identify the effect of container design in influencing consumer purchase intention, pulling together collected textual data regarding two factors. No other research conduct to measure this relationship. Research design, data and methodology: Using web data searching tools, the present researcher coded the data obtained. The web content analysis platform is useful because it allows a researcher to examine themes in texts and, in a way, allows an ideal way to understand links within categories of data. Results: Different components of container design have different impacts on the purchase behavior of different consumers. The most crucial container design components include; shape, color, material and textual, and artistic features. These components are used by designers for different purposes and have different levels of appeal to the consumer. Conclusions: Manufacturers in the cosmetic industry must invest in designing packaging products that are more appealing in shape and color while using high-quality materials to packaging these products. The packaging containers should also be designed to incorporate textual and artistic features that provide more information regarding the products.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• Journal of Information Management
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• v.34 no.2
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• pp.67-88
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• 2003

There have been increased interests in information visualization. Information visualization has been considered as a way to summarize textual data so that the users can access large amount of data more efficiently and effectively. However, many information visualization techniques stem from scientific visualization techniques, which might be difficult for the regular users to understand. More importantly, the system models used by most of the information visualization techniques do not have real world counterpart. For example, most of the users do not represent or process the textual data in terms of fisheye view or a topological map. This means that there is no affordance on the current information visualization systems from the users point of view. In this paper, we analyzed this problem by using the user interface design principles to point out what lacks in the current information visualization systems. More specifically, we have applied Nielson's Heuristic Evaluation technique to review four representative information visualization techniques. The analysis results confirmed our original hypothesis on why the current information visualization systems are not part of the mainstream information systems. Finally, we suggested to invest more efforts in improving the currently prevalent and familiar bullet list type textual information presentation method based on the usability studies and the intelligent content analysis.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.3-3
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• 2003

With biomedical literature expanding so rapidly, there is an urgent need to discover and organize knowledge extracted from texts. Although factual databases contain crucial information the overwhelming amount of new knowledge remains in textual form (e.g. MEDLINE). In addition, new terms are constantly coined as the relationships linking new genes, drugs, proteins etc. As the size of biomedical literature is expanding, more systems are applying a variety of methods to automate the process of knowledge acquisition and management. In my talk, I focus on the project, GENIA, of our group at the University of Tokyo, the objective of which is to construct an information extraction system of protein - protein interaction from abstracts of MEDLINE. The talk includes (1) Techniques we use fDr named entity recognition (1-a) SOHMM (Self-organized HMM) (1-b) Maximum Entropy Model (1-c) Lexicon-based Recognizer (2) Treatment of term variants and acronym finders (3) Event extraction using a full parser (4) Linguistic resources for text mining (GENIA corpus) (4-a) Semantic Tags (4-b) Structural Annotations (4-c) Co-reference tags (4-d) GENIA ontology I will also talk about possible extension of our work that links the findings of molecular biology with clinical findings, and claim that textual based or conceptual based biology would be a viable alternative to system biology that tends to emphasize the role of simulation models in bioinformatics.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.623-640
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• 2013

Soil organic carbon (SOC) of soil series is necessary to calculate soil C sequestration due to IPCC default categorized by climate regions and by soil types. The 3,400 thousand data were downloaded from agricultural soil information system and analyzed to get averages of soil order, soil series, and textual family for the three different soil management practices in Korea. The SOC content was $13.3{\pm}5.38g\;kg^{-1}$ in paddy field, $13.7{\pm}7.19g\;kg^{-1}$ in upland field, and $15.2{\pm}8.22g\;kg^{-1}$ in orchard soil, respectively. As SOC in orchard was 10% greater than that in upland, orchard must be managed with applying compost. The SOCs of inceptisols, which was largely distributed in Korea, were $13.6{\pm}5.48g\;kg^{-1}$ in paddy field, $14.1{\pm}7.38g\;kg^{-1}$ in upland field, and $15.3{\pm}8.20g\;kg^{-1}$ in orchard soil, respectively. The SOCs of alfisols were $13.6{\pm}4.96g\;kg^{-1}$ in paddy field, $13.7{\pm}6.99g\;kg^{-1}$ in upland field, and $15.6{\pm}8.59g\;kg^{-1}$ in orchard soil, respectively. The SOCs of entisols were $11.7{\pm}5.16g\;kg^{-1}$ in paddy field, $12.8{\pm}7.05g\;kg^{-1}$ in upland field, and $13.7{\pm}7.81g\;kg^{-1}$ in orchard soil, respectively. The SOCs of ultisols were $12.7{\pm}4.79g\;kg^{-1}$ in paddy field, $12.7{\pm}6.22g\;kg^{-1}$ in upland field, and $16.3{\pm}8.49g\;kg^{-1}$ in orchard soil, respectively. The fact that soils containing greater clay content in textual family had also more SOC content revealed that SOC could be also dependent on some soil properties as well as soil order. Because SOC differences among soil series representing same textual family were greater than those among textual family, SOC differences should be mainly affected by management practices such as compost application.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.202-208
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• 2001

One of the most frequent uses of Internet is data gathering. Data can be about many themes but perhaps one of the most demanded fields is the tourist information. Normally, databases that support these systems are maintained manually. However, there is other approach, that is, to extract data automatically, for instance, from textual public information existing in the Web. This approach consists of extracting data from textual sources(public or not) and to serve them totally or partially to the user in the form that he/she wants. The obtained data can maintain automatically databases that support different systems as WAP mobile telephones, or commercial systems accessed by Natural Language Interfaces and others. This process has three main actors. The first is the information itself that is present in a particular context. The second is the information supplier (extracting data from the existing information) and the third is the user or information searcher. This added value chain reuse and give value to existing data even in the case that these data were not tough for the last use by the use of the described technology. The main advantage of this approach is that it makes independent the information source from the information user. This means that the original information belongs to a particular context, not necessarily the context of the user. This paper will describe the application based on this approach developed by the authors in the FLEX EXPRIT IV n$^{\circ}$EP29158 in the Work-package "Knowledge Extraction & Data mining"where the information captured from digital newspapers is extracted and reused in tourist information context.

• Language and Information
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• v.17 no.2
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• pp.93-121
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• 2013

Identifying the speakers of individual utterances mentioned in textual stories is an important step towards developing applications that involve the use of unique characteristics of speakers in stories, such as robot storytelling and story-to-scene generation. Despite the usefulness, it is a challenging task because not only human entities but also animals and even inanimate objects can become speakers especially in fairytales so that the number of candidates is much more than that in other types of text. In addition, since the action of speaking is not always mentioned explicitly, it is necessary to infer the speaker from the implicitly mentioned speaking behaviors such as appearances or emotional expressions. In this paper, we investigate a method to exploit linguistic clues to identify the speakers of utterances from textual fairytale stories in Korean, especially in order to handle such challenging issues. Compared with the previous work, the present work takes into account additional linguistic features such as vocative roles and pairs of conversation participants, and proposes the use of discourse-level turn-taking behaviors between speakers to further reduce the number of possible candidate speakers. We describe a simple rule-based method to choose a speaker from candidates based on such linguistic features and turn-taking behaviors.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.1-14
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• 2000

Visual information retrieval and image databases are very important applications of spatial access methods. The quaries for these applications are visual and based not on exact match but on dubjective similarity. The individual aperations of spatial access methods are much more expensive than those of conventional one-dimensional access methods. Also, because the visual queries are much more complex than textual queries, an efficient processing technique for visual queries is one of the critical requirements in the development of large and scalable image databases. Therefore, efficient translation and execution for the complex visual queries are not less important than those of textual databases. In this paper, we introduce our cognitive and topological studies that are required to process subjective visual queries effectively. Then, we propose an efficient translation and execution techniques for similarity based visual queries by conducting these related studies.