Dosam Hwang's research while affiliated with Yeungnam University and other places

Publications (92)

Article
Full-text available
Currently, determining DNA motifs or consensus plays an indispensable role in bioinformatics. Many postulates have been proposed for finding a consensus. Postulate 2-Optimality is essential for this task. A consensus satisfying postulate 2-Optimality is the best representative of a profile, and its distances to the profile members are uniform. Howe...
Article
Recently, aspect-level sentiment analysis methods using graph convolutional network (GCN)-based structures with fairly good performance have been introduced. However, previous GCN-based methods often experience one of the following limitations. First, GCNs usually use edges with binary weights. However, binary weights are not helpful in many tasks....
Article
With the rapid development of the Internet industry, an increasing number of social media platforms have been developed. These social media platforms have become the main channels for communication among most users. Opinions from social media platforms provide the most updated and inclusive information. Sentiments from opinions are a valuable data...
Chapter
As deep learning (DL) is evolving rapidly, implementing the knowledge of DL into various fields of human life and the effective usage of existing data insights are becoming crucial tasks for a majority of DL models. We are proposing to ensemble maximum prediction probabilities of different epochs and the epoch which achieved the highest accuracy fo...
Chapter
Strings are widely used to describe and store information in bioinformatics, such as DNA and proteins. The determination of a consensus for a string profile plays an important role in bioinformatics. There are several postulates to determine consensus, among which postulate 1-Optimality is the most popular. A consensus that satisfies this postulate...
Chapter
The emergence of word embeddings has created good conditions for natural language processing used in an increasing number of applications related to machine translation and language understanding. Several word-embedding models have been developed and applied, achieving considerably good performance. In addition, several enriching word embedding met...
Chapter
Social networks are increasingly proving to be the core of today’s web. Identifying the influence on social networks is an area of research that presents many open issues. The challenge is finding ways that can effectively calculate and classify users according to criteria that suit them closer to reality. In this paper, we proposed a new method fo...
Article
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Social networks are a very popular channel for people to communicate with, to find, to reference other users before making decisions, especially those concerning purchase. How can users’ opinions within social networks be used in making decisions cost-effective and reliable? In this paper, we propose an approach for supporting decision-making based...
Article
Reviewing is the most important step in the quality accreditation of scientific works, requires the professional expertise of the reviewer as well as there is no conflict of interest in the evaluation process. However, we also acknowledge that reviewers have limited knowledge, experience and opinions about the work of others, so they may misinterpr...
Article
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Nowadays, using the consensus of collectives for solving problems plays an essential role in our lives. The rapid development of information technology has facilitated the collection of distributed knowledge from autonomous sources to find solutions to problems. Consequently, the size of collectives has increased rapidly. Determining consensus for...
Article
Nowadays, to solve a problem, people/systems typically use knowledge from different sources. A binary vector is a useful structure to represent knowledge states, and determining the consensus for a binary vector collective is helpful in many areas. However, determining a consensus that satisfies postulate 2-Optimality is an NP-hard problem; therefo...
Article
Full-text available
Nowadays, to solve a problem, people/systems typically use knowledge from different sources. A binary vector is a useful structure to represent knowledge states, and determining the consensus for a binary vector collective is helpful in many areas. However, determining a consensus that satisfies postulate 2-Optimality is an NP-hard problem; therefo...
Article
Full-text available
Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicio...
Chapter
In recent years, companies have begun using social networks as a useful tool for marketing campaigns and communicating with their customers. Social networks are enormously beneficial for both sellers and buyers. For producers, the analysis of social content can provide immediate insight into people’s reactions regarding products and services. Meanw...
Chapter
The variability in manufacturing process and operating conditions has a significant impact on the operation of memristor devices, since it is usually implemented in nano-scale for higher density. The variability in thickness and area can be regarded as a source of variations in read and write times of memristor when using the device as a memory cel...
Chapter
Collective knowledge or consensus is used widely in our life. Determining the collective knowledge of a collective depends on the knowledge states of collective members. However, in a collective, each member has its knowledge, and knowledge states are often contradictory. Determining consensus satisfying postulate 2-Optimality of a collective is an...
Chapter
The introduction of the online social media system has unquestionably facilitated communication as well as being a prime and cheap source of information. However, despite these numerous advantages, the social media system remains a double-edged sword. Recently, the online social media ecosystem although fast becoming the primary source of informati...
Chapter
Systems and individuals commonly utilize information from multiple sources aim to make a decision. Because knowledge from various sources is often inconsistent, determining the 2-Optimality consensus of a collective, which is an NP-hard problem, is a complicated task, and heuristic algorithms are used to solve this task. The basic algorithm has bee...
Chapter
The recurrent nature of terrorist attacks in recent times has ushered in a new wave of study in the field of terrorism known as social network analysis (SNA). Terrorist groups operate as a social network in a stealthy manner to enhance their survival thereby making sure their activities are unperturbed. Graphical modeling of the terrorist network i...
Chapter
The more societies develop, people have less time for interacting face-to-face with each other. Therefore, more and more users express their opinions on many topics on Twitter. The sentiments contained in these opinions are becoming a valuable source of data for politicians, researchers, producers, and celebrities. Many studies have used this data...
Chapter
Fake news has gained prominence since the 2016 US presidential election as well as the Brexit referendum. Fake news has abused not only the press but also the democratic rules. Therefore, the need to restrict and eliminate it becomes inevitable. The popularity of fake news on social media has made people unwilling to engage in sharing positive news...
Article
Full-text available
The increase in the volume of user-generated content on Twitter has resulted in tweet sentiment analysis becoming an essential tool for the extraction of information about Twitter users’ emotional state. Consequently, there has been a rapid growth of tweet sentiment analysis in the area of natural language processing. Tweet sentiment analysis is in...
Chapter
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The security and welfare of any country are very crucial with states investing heavily to protect their territorial integrity from external aggression. However, the increase in the act of terrorism has given birth to a new form of security challenges. Terrorism has caused untold suffering and damages to civilian lives and properties and hence, find...
Book
This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and sema...
Article
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The dependence between the write time and process variation of a memristor was investigated as a candidate physically unclonable function (PUF). Such write-time-based approach requires exact timing control of the programming pulse to achieve well-balanced results as the source of randomness. However, exact timing control requires precise hardware,...
Chapter
Research conferences are held to share research progress and novel findings among scientists and encourage the growth of academic communities. Assigning papers to reviewers is the most critical and arduous task for conference organizers. Usually, conference committees must distribute hundreds of publications to reviewers in a short time. Moreover,...
Article
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International standards for the exchange of healthcare information, known as Health Level Seven (HL7), were developed for the interoperability of healthcare information systems. Because of HL7’s complex structure and syntax, HL7 messages are processed by computer software. HL7 defines that, when the version is updated, it should be compatible with...
Article
Sentiment analysis has been gaining importance in many applications such as recommendation systems, the decision-making support and prediction models. Sentiment analysis helps to understand and evaluate public opinion regarding social events, product services, and political trends, especially the feelings expressed through comments by users in soci...
Chapter
As more and more users express their opinions on many topics on Twitter, the sentiments contained in these opinions are becoming a valuable source of data for politicians, researchers, producers, and celebrities. These sentiments significantly affect the decision-making process for users when they assess policies, plan events, design products, etc....
Article
Referencing knowledge generated from large collectives is a common approach to solving certain problems. Because determining the consensus of large collectives can be time-consuming, we develop a multi-step consensus approach (MCA) to address this problem. In the MCA, a primary collective is divided into smaller ones and their individual consensuse...
Article
This paper proposes a hybrid collaboration recommendation method that accounts for research similarities and the previous research cooperation network. Research cooperation is measured by combining the collaboration time and the number of co-authors who already collaborated with at least one scientist. Research similarity is based on authors’ previ...
Chapter
Nowadays, the problem of referring knowledge from a large number of autonomous units for solving some problems in the real world has become more and more popular. The need for new techniques to process knowledge in collectives has become urgent because of the rapidly increasing in size of collectives. Many methods for determining the knowledge of c...
Chapter
Twitter is a well-known social network service. Every second, users post a large number of tweets on different topics, which leads to a significant problem-it is time-consuming for users to get useful information for their individual purposes. It is difficult for a user to receive necessary information from all topics with high accuracy. Thus, inte...
Chapter
Question-and-answer (Q&A) sites can be understood as information systems where users generate and answer questions. Also, they can determine the top answers using the number of positive and negative votes from crowd knowledge and experts. Knowledge sharing sites have been rapidly growing in recent years. It is difficult for a user to find experts w...
Article
Twitter has become a popular microblogging service that allows millions of active users share news, emergent social events, personal opinions, etc. That leads to a large amount of data producing every day and the problem of managing tweets becomes extremely difficult. To categorize the tweets and make easily in searching, the users can use the hash...
Conference Paper
The number of events generated on social networks has been growing quickly in recent years. It is difficult for users to find events that most suitably match their favorites. As a solution, the recommender system appears to solve this problem. However, event recommendation is significantly different from traditional recommendations, such as product...
Conference Paper
In recently, the smart tourism applications are raising the scale of data to an unprecedented level. A new emerging trend in social media namely to collect and introduce cultural heritage by geotagged resources were being focused on. The paper aims to deliver a way to collect geotagged cultural heritage resources from social networking services by...
Chapter
In this decade, the number of movies is increasing rapidly. Many studies have been proposed to assist users in movie understanding. In which, these methods are taken into account movie content analysis using social network for discovering relationships among characters and so on. However, these methods have shown some unsatisfactorily in dynamic ch...
Article
In recent years, many applications in natural language processing (NLP) have been developed using the machine learning approach. Annotating data is an important task in applying machine learning to NLP applications. A common approach to improve the system performance is to train on a large and high-quality set of training data that is annotated by...
Article
The scientific community is growing very quickly. Every year a huge number of academic events (conferences, workshops, symposiums, etc.) are organized over the world. Therefore, it is difficult for researchers to find related information about the events in which they may be interested. In this study, we present an improvement to existing academic...
Article
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Movie summarization focuses on providing as much information as possible for shorter movie clips while still keeping the content of the original movie and presenting a faster way for the audience to understand the movie. In this paper, we propose a novel method to summarize a movie based on character network analysis and the appearance of protagoni...
Conference Paper
Information extraction from microblogs has recently attracted researchers in the fields of knowledge discovery and data mining owing to its short nature. Annotating data is one of the significant issues in applying machine learning approaches to these sources. Active learning (AL) and semi-supervised learning (SSL) are two distinct approaches to re...
Conference Paper
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With the development of scientific societies, research problems are increasingly complex, requiring scientists to collaborate to solve them. The quality of collaboration between researchers is a major factor in determining their achievements. This study proposes a collaboration recommendation method that takes into account previous research collabo...
Chapter
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The named entity recognition (NER) problem has an important role in many natural language processing (NLP) applications and is one of the fundamental tasks for building NLP systems. Supervised learning methods can achieve high performance but they require a large amount of training data that is time-consuming and expensive to obtain. Active learnin...
Article
The imbalanced data problem occurs when the number of representative instances for classes of interest is much lower than for other classes. The influence of imbalanced data on classification performance has been discussed in some previous research as a challenge to be studied. In this paper, we propose a method to solve the imbalanced data problem...
Article
In recent years, information extraction from tweets has been challenging for researchers in the fields of knowledge discovery and data mining. Unlike formal text, such as news articles and pieces of longer content, tweets are of a specific nature: short, noisy, and with dynamic content. Thus, it is difficult to apply the traditional natural languag...
Conference Paper
In this decade, the number of movies is increasing rapidly. Many studies have been proposed to assist users in movie understanding. In which, these methods are taken into account movie content analysis using social network for discovering relationships among characters and so on. However, these methods have shown some unsatisfactorily in dynamic ch...
Conference Paper
In this study, a new academic event recommendation method is proposed. This method analyzes author interactions, academic event attendance records, research related, and textual descriptions from attended academic events to measure interaction strength between authors. Experiments on the DBLP dataset and Wiki Calls for Papers (WikiCFP) showed that...
Conference Paper
Generally the knowledge of a collective, which is considered as a representative of the knowledge states in a collective, is often determined based on a single-stage approach. For big data, however, a collective is often very large, a multi-stage approach can be used. In this paper we present an improvement of the two-stage consensus-based approach...
Conference Paper
The nature characteristics of data in Social Network Services (SNS) are usually short, contain insufficient information, and often are influenced by noise data, thus popular Named Entity Recognition (NER) methods applied for these data could provide wrong results even if they perform well on well-format documents. Most of NER methods are based on s...
Conference Paper
Full-text available
Exploring social events from Social Network Services (SNSs) (known as detecting events) has been studied in many researches because of its challenges. Most of researches focus on detecting events based on textual context. In this paper, we propose a novel framework using media data for not only systematically identifying events but also ranking the...
Article
Although collaborative filtering is widely applied in recommendation systems, it still suffers from several major limitations, including data sparsity and scalability. Sparse data affects the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure a...
Conference Paper
Full-text available
In this paper, we propose a new statistical method for sentiment analysis of figurative language within short texts collected from Twitter (called tweets) as a part of SemEval-2015 Task 11. Particularly, the proposed model focuses on classifying the tweets into three categories (i.e., sarcastic, ironic, and metaphorical tweet) by extracting two mai...
Article
As communities of researchers continue to become quite large and to grow incessantly, collaboration among researchers can be conducive to greater research productivity. Nevertheless, it is difficult for a researcher to find suitable collaborators from all researchers around the world. In this paper, we have used bibliographic DBLP data to extract i...
Conference Paper
Discovering the research communities to bring techniques to the world is an interesting topic. In this paper we use the DBLP data to investigate the co-author relationship in a real bibliographic network and predict the interactions between co-authors. We analysis the research trend of authors and conferences based on extracted keywords from paper...
Article
Several key applications like recommender systems need to determine the similarities between users or items. These similarities play an important role in many tasks, such as discovering users with common interests or items with common properties. Most of the traditional methods are symmetric which means that they always assign equal similarity to e...
Chapter
Movie summarization focuses to obtain as much as possible of information as a shorter movie clip does, that but it keeps the content of the original and presents to the audience the faster way for understanding the movie. In this paper, we propose a co-occurrence characters network analysis for movie summarization based on discovery and analysis mo...
Article
Social Network Services (SNS) have been the most popular channel where users can generate and disseminate a large amount of information (so-called ‘social big data’) among other users efficiently. Discovering meaningful patterns from these SNS (e.g., clustering relevant messages, detecting events, and understanding trends of social communities) is...
Article
Similarity-based algorithms, often referred to as memory-based collaborative filtering techniques, are one of the most successful methods in recommendation systems. When explicit ratings are available, similarity is usually defined using similarity functions, such as the Pearson correlation coefficient, cosine similarity or mean square difference....
Conference Paper
Social data have been emerged as a special big data resource of rich information, which is raw materials for diverse research to analyse a complex relationship network of users and huge amount of daily exchanged data packages on Social Network Services (SNS). The popularity of current SNS in human life opens a good challenge to discover meaningful...
Conference Paper
The paper focuses on using geotagged resources from the social network service (SNS) for searching the famous places from keyword. We extend the HITS[9] algorithm in order to rank locations which are collected from geotagged resources on SNS. Our approach not only uses the similarity measurement between locations’tags for computing the value of loc...
Article
Full-text available
Nowadays, there are many ongoing researches to construct knowledge bases from unstructured data. This process requires an ontology that includes enough properties to cover the various attributes of knowledge elements. As a huge encyclopedia, Wikipedia is a typical unstructured corpora of knowledge. DBpedia, a structured knowledge base constructed f...
Conference Paper
Social networking services (SNS) have been an important sources of geotagged resources. This paper proposes Naive Bayes method-based framework to predict the locations of non-geotagged resources on SNS. By computing TF-ICF weights (Term Frequency and Inverse Class Frequency) of tags, we discover meaningful associations between the tags and the clas...
Article
Full-text available
The introduction of semantic web and Linked Data helps facilitate sharing of data on the Internet more easily. Subsequently, the resource description framework (RDF) is the standard in publishing structured data resources on the Internet and is used in interconnecting with other data resources. To remedy the data integration issues of the tradition...
Conference Paper
User-based collaborative filtering (CF) is a widely used technique to generate recommendations. Lacking sufficient ratings will prevent CF from modeling user preference effectively and finding trustworthy similar users. To alleviate this problems, item-based CF was introduced. However, when number of co-rated items is not enough or new item is adde...