• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.189-195
• /
• 2024

The issue "Exploring Social Media and Other Crucial Success Elements of Attitude towards Politics and Intention for Voting in Pakistan" is a huge study embracing more issues. The politics of Pakistan is basically the politics of semantic groups. Pakistan is a multilingual state more than six languages. There are 245 religious parties in Pakistan, as elaborated by the Daily Times research. The use of social media sites in Pakistan peaked to its maximum after announcement of election schedule by the Election Commission of Pakistan in March 22, 2013. Most of the political parties used it for the recent elections in Pakistan to promote their agenda and attract country's 80 million registered electors. This study was aiming to investigate the role of social media and other critical variables in the attitude towards politics and intention for voting.

• The Journal of the Korea Contents Association
• /
• v.10 no.6
• /
• pp.43-48
• /
• 2010

Useful emails influence on consumers' purchase behavior and activate them to visit retail stores. Regular contact with consumers by e-mail has positive effects on brand loyalty. However, email marketing has a limitation. Spam now accounts for over half of all e-mail traffic. The increase of email users has resulted in the dramatic increase of spam emails during the past few years. In this paper, we proposed an ontology-based system offering personalized email services to overcome such limitation. Our method is not the ontology-driven spam filtering, but a personalized content service considering personal interests and relations among people by using FOAF and domain ontologies. Our system was successfully tested in email marketing domain.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.21 no.3
• /
• pp.151-163
• /
• 2010

It is necessary, due to changes in the information environment, to investigate problems in existing information retrieval systems. Ontologies and social tagging, which are a relatively new means of information organization, enable exploratory discovery of information. These two connect a thought of a user with the thoughts of numerous other people on the Internet. With these connection chains through the interactions, users are foraging information actively and exploratively. Thus, the purpose of this study is, through qualitative research methods, to identify numerous discovery facilitators provided by ontologies and social tagging, and to create an exploratory discovery model based on them. The results show that there are three uppermost categories in which 5, 4 and 4 subcategories are enumerated respectively. The first category, 'Browsing and Monitoring,' has 5 sub categories: Noticing the Needs, Being Aware, Perceiving, Stopping, and Examining a Resource. The second category, Actively Participating, has 4 categories: Constructing Meaning, Social Bookmarking and Tagging, Sharing on Social Networking, Specifying the Original Needs. The third category, Actively Extends Thinking, also has 4 categories: Social Learning, Emerging Fortuitous Discovery, Creative Thinking, Enhancing Problem Solving Abilities. This model could contribute to the design of information systems, which enhance the ability of exploratory discovery.

• Culinary science and hospitality research
• /
• v.24 no.3
• /
• pp.167-176
• /
• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.

• Journal of Internet Computing and Services
• /
• v.13 no.5
• /
• pp.33-43
• /
• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.5
• /
• pp.390-394
• /
• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• Journal of Intelligence and Information Systems
• /
• v.19 no.1
• /
• pp.19-33
• /
• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• Journal of Internet Computing and Services
• /
• v.13 no.2
• /
• pp.99-108
• /
• 2012

Many methods had been developed to improve the accuracy of extracting information from a vast amount of data. This paper combined a number of natural language processing methods such as NER (named entity recognition), sentence extraction, and part of speech tagging to carry out text analysis. The data source is comprised of texts obtained from the web using a domain-specific data extraction agent. A framework for the extraction of information from unstructured data was developed using the aforementioned natural language processing methods. We simulated the performance of our work in the extraction and analysis of texts for the detection of organizational structures. Simulation shows that our study outperformed other NER classifiers such as MUC and CoNLL on information extraction.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.190-193
• /
• 2008

사용자의 '참여'를 지향하는 웹2.0 서비스들은 사람간이나 정보간의 '관계'에 대한 문제에 주목하고 있다. 대표적인 서비스인 블로그는 엮인글을 통해 사용자들의 참여를 이끌고 문서를 연결하고 있으나 이를 악용하는 사례들이 발생하고 있어 이에 대한 해결을 위해 연결에 대한 분석이 요구되고 있다. 사람의 개인 정보와 친구 관계 및 주변 사물과의 관계를 모델링하는 방식인 FOAF(Friend of a Friend)는 이러한 사회연결망 분석을 가능케 하는 수단으로써 연구되고 있다. FOAF는 단순화되고 이해하기 쉬운 용어를 사용하여, 복잡하고 이해하기 어려운 시맨틱 웹의 단점을 극복하기 위한 발판으로서 또한 주목 받고 있다. 본 연구에서는 여러 웹 사이트를 하나의 ID로 이용하기 위한 OpenID를 통해 FOAF에 정보 관리 능력을 부여하여 개인정보 유출 문제를 해결하기 위한 방안을 제시한다. 또한 실제 운영되는 관리 능력을 부여하여 개인정보 유출 문제를 해결하기 위한 방안을 제시한다. 또한 실제 운영되는 사회연결망 서비스의 분석을 통해 OpenID의 정보에 따라 자동으로 사회연결망 정보를 수집하는 성장형 FOAF 프레임워크를 설계하였으며, 쉬운 FOAF를 보급하기 위한 발판을 마련하였다.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.66-71
• /
• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.