• Title/Summary/Keyword: Issue keyword

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Design and Implementation of Potential Advertisement Keyword Extraction System Using SNS (SNS를 이용한 잠재적 광고 키워드 추출 시스템 설계 및 구현)

  • Seo, Hyun-Gon;Park, Hee-Wan
    • Journal of the Korea Convergence Society
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    • v.9 no.7
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    • pp.17-24
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    • 2018
  • One of the major issues in big data processing is extracting keywords from internet and using them to process the necessary information. Most of the proposed keyword extraction algorithms extract keywords using search function of a large portal site. In addition, these methods extract keywords based on already posted or created documents or fixed contents. In this paper, we propose a KAES(Keyword Advertisement Extraction System) system that helps the potential shopping keyword marketing to extract issue keywords and related keywords based on dynamic instant messages such as various issues, interests, comments posted on SNS. The KAES system makes a list of specific accounts to extract keywords and related keywords that have most frequency in the SNS.

Semantic-based Keyword Search System over Relational Database (관계형 데이터베이스에서의 시맨틱 기반 키워드 탐색 시스템)

  • Yang, Younghyoo
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.12
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    • pp.91-101
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    • 2013
  • One issue with keyword search in general is its ambiguity which can ultimately impact the effectiveness of the search in terms of the quality of the search results. This ambiguity is primarily due to the ambiguity of the contextual meaning of each term in the query. In addition to the query ambiguity itself, the relationships between the keywords in the search results are crucial for the proper interpretation of the search results by the user and should be clearly presented in the search results. We address the keyword search ambiguity issue by adapting some of the existing approaches for keyword mapping from the query terms to the schema terms/instances. The approaches we have adapted for term mapping capture both the syntactic similarity between the query keywords and the schema terms as well as the semantic similarity of the two and give better mappings and ultimately 50% raised accurate results. Finally, to address the last issue of lacking clear relationships among the terms appearing in the search results, our system has leveraged semantic web technologies in order to enrich the knowledgebase and to discover the relationships between the keywords.

Rethinking the US Presidential Election: Feminism and Big Data

  • CHUNG, Sae Won;PARK, Han Woo
    • International Journal of Contents
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    • v.17 no.4
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    • pp.52-61
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    • 2021
  • The 2020 US Presidential Election was a highly-anticipated moment for our global society. During the election period, the most intriguing issue was who would be the winner-Trump or Biden? Among the possible main themes of the 2020 election, from the COVID-19 pandemic to racism, this study focused on feminism ('women') as a main component of Biden's victory. To explore the character of Biden's supporters, this paper focused on internet spaces as a source of public opinion. To guide the data analysis, this study employed four indices from empirical studies on Big Data analytics: issue salience, attention diversity, emotional mentioning, and semantic cohesion. The main finding of this study was that the representative keyword 'women' appeared more prevalently within content related to Biden than Trump, and the keyword pairs indicated that female voters were the main reason for Trump's failure but the root cause of Biden's victory. The results of this study indicated the role of the internet as a forum for public opinion and a fountain of political knowledge, which requires more rigorous investigation by researchers.

Identification of Research Areas and Evolution of 2D Materials by the Keyword Mapping Methodology (키워드 매핑 기반 2차원 물질 연구 영역 탐지와 발전 과정 분석)

  • Ahn, Sejung;Lee, June Young
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.31 no.1
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    • pp.11-18
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    • 2018
  • Two-dimensional (2D) materials such as transition metal dichalcogenides have attracted tremendous scientific interests owing to their potential of solving the zero band-gap issue of graphene. In this work, the research areas and technology evolutionary dynamics of the 2D materials were identified using the scientometric method focusing on keyword mapping and clustering. The time-series analysis showed that the technological progress of 2D material is in the early growth period. The overlay mapping analysis were carried out to investigate the technology evolution of 2D materials with time. The strategic diagram of co-word analysis classifying the topological positions of keyword was derived to support the analysis results. It is conjectured that extensive research will be conducted widely on the application of 2D materials not only in electronic and optoelectronic devices, but also in various other fields such as biomedical applications, and that their development will be more rapid based on accumulated results of extant graphene research.

Concealed Policy and Ciphertext Cryptography of Attributes with Keyword Searching for Searching and Filtering Encrypted Cloud Email

  • Alhumaidi, Hind;Alsuwat, Hatim
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.212-222
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    • 2022
  • There has been a rapid increase in the use of cloud email services. As a result, email encryption has become more commonplace as concerns about cloud privacy and security grow. Nevertheless, this increase in usage is creating the challenge of how to effectively be searching and filtering the encrypted emails. They are popular technologies of solving the issue of the encrypted emails searching through searchable public key encryption. However, the problem of encrypted email filtering remains to be solved. As a new approach to finding and filtering encrypted emails in the cloud, we propose a ciphertext-based encrypted policy attribute-based encryption scheme and keyword search procedure based on hidden policy ciphertext. This feature allows the user of searching using some encrypted emails keywords in the cloud as well as allowing the emails filter-based server toward filter the content of the encrypted emails, similar to the traditional email keyword filtering service. By utilizing composite order bilinear groups, a hidden policy system has been successfully demonstrated to be secure by our dual system encryption process. Proposed system can be used with other scenarios such as searching and filtering files as an applicable method.

Exploring Future Signals for Mobile Payment Services - A Case of Chinese Market - (모바일 결제 서비스에 대한 미래신호 예측 - 중국시장을 대상으로 -)

  • Bin Xuan;Seung Ik Baek
    • Journal of Service Research and Studies
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    • v.13 no.1
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    • pp.96-107
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    • 2023
  • The objective of this study is to explore future issues that Chinese users, who have the highest mobile payment service usage rate in the world, will be most interested in. For this purpose, after collecting text data from a Chinese SNS site, it classifies major keywords into 4 types of future signals by using Keyword Emergence Map (KEM) and Keyword Issue Map (KIM). Furthermore, to understand the four types of signals in detail, it performs the qualitative analysis on text related to each signal keyword. As a result, it finds that the strong signal, which is rapidly growing in keyword appearance frequency during this research period, includes the keywords related to the daily life of Chinese people, such as buses, subways, and household account books. Additionally, it find that the signal that appears frequently now, but with a low increase rate, includes various services that can replace cash payment, such as hongbao (cash payment) and bank cards. The weak signal and latent signal, which appear less often than other two signals, includes the keywords related to promotion events or changes in service regulations. Its result shows that the mobile payment services greatly have changed user's daily life beyond providing convenience. Furthermore, it shows that, in the Chinese market, in which card payment is not common, the mobile payment services have the great potential to completely replace cash payment.

Analysis of News Big Data for Deriving Social Issues in Korea (한국의 사회적 이슈 도출을 위한 뉴스 빅데이터 분석 연구)

  • Lee, Hong Joo
    • The Journal of Society for e-Business Studies
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    • v.24 no.3
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    • pp.163-182
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    • 2019
  • Analyzing the frequency and correlation of the news keywords in the modern society that are becoming complicated according to the time flow is a very important research to discuss the response and solution to issues. This paper analyzed the relationship between the flow of social keyword and major issues through the analysis of news big data for 10 years (2009~2018). In this study, political issues, education and social culture, gender conflicts and social problems were presented as major issues. And, to study the change and flow of issues, it analyzed the change of the issue by dividing it into five years. Through this, the changes and countermeasures of social issues were studied. As a result, the keywords (economy, police) that are closely related to the people's life were analyzed as keywords that are very important in our society regardless of the flow of time. In addition, keyword such as 'safety' have decreased in increasing rate compared to frequency in recent years. Through this, it can be inferred that it is necessary to improve the awareness of safety in our society.

Analysis of Trends in Science and Technology using Keyword Network Analysis (키워드 네트워크 분석을 활용한 과학기술동향 분석)

  • Park, Ju Seop;Kim, Na Rang;Han, Eun Jung
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.2
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    • pp.63-73
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    • 2018
  • Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

Interactive Morphological Analysis to Improve Accuracy of Keyword Extraction Based on Cohesion Scoring

  • Yu, Yang Woo;Kim, Hyeon Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.145-153
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    • 2020
  • Recently, keyword extraction from social big data has been widely used for the purpose of extracting opinions or complaints from the user's perspective. Regarding this, our previous work suggested a method to improve accuracy of keyword extraction based on the notion of cohesion scoring, but its accuracy can be degraded when the number of input reviews is relatively small. This paper presents a method to resolve this issue by applying simplified morphological analysis as a postprocessing step to extracted keywords generated from the algorithm discussed in the previous work. The proposed method enables to add analysis rules necessary to process input data incrementally whenever new data arrives, which leads to reduction of a dictionary size and improvement of analysis efficiency. In addition, an interactive rule adder is provided to minimize efforts to add new rules. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that error ratio was reduced from 10% to 1% by applying our method and it took 450 milliseconds to process 5,000 reviews, which means that keyword extraction can be performed in a timely manner in the proposed method.

Public Key Encryption with Keyword Search in Multi-Receiver Setting (다중 수신자 환경에서 키워드 검색 가능한 공개키 암호시스템)

  • Rhee, Hyun-Sook;Park, Jong-Hwan;Rhee, Dong-Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.19 no.2
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    • pp.31-38
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    • 2009
  • To provide the privacy of a keyword, a public key encryption with keyword search(PEKS) firstly was propsed by Boneh et al. The PEKS scheme enables that an email sender sends an encrypted email with receiver's public key to an email server and a server can obtain the relation between the given encrypted email and an encrypted query generated by a receiver. In this email system, we easily consider the situation that a user sends the one identical encrypted email to multi-receiver like as group e-mail. Hwang and Lee proposed a searchable public key encryption considering multi-receivers. To reduce the size of transmission data and the server's computation is important issue in multi-receiver setting. In this paper, we propose an efficient searchable public key encryption for multi-receiver (mPEKS) which is more efficient and reduces the server's pairing computation.