• The Korean Journal of Archival Studies
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• no.48
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• pp.93-139
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• 2016

Aside from serving as a body that monitors and criticizes the government through reviews and comments on public issues, newspapers can also form and spread public opinion. Metadata contains certain picture records and, in the case of local newspapers, the former is an important means of obtaining locality. Furthermore, advertising in newspapers and the way of editing in newspapers can be viewed as a representation of the times. For the value of archiving in newspapers when a documentation strategy is established, the newspaper is considered as a top priority that should be collected. A newspaper archive that will handle preservation and management carries huge significance in many ways. Journalists use them to write articles while scholars can use a newspaper archive for academic purposes. Also, the NIE is a type of a practical usage of such an archive. In the digital age, the newspaper archive has an important position because it is located in the core of MAM, which integrates and manages the media asset. With this, there are prospects that an online archive will perform a new role in the production of newspapers and the management of publishing companies. Korea Integrated News Database System (KINDS), an integrated article database, began its service in 1991, whereas Naver operates an online newspaper archive called "News Library." Initially, KINDS received an enthusiastic response, but nowadays, the utilization ratio continues to decrease because of the omission of some major newspapers, such as Chosun Ilbo and JoongAng Ilbo, and the numerous user interface problems it poses. Despite these, however, the system still presents several advantages. For example, it is easy to access freely because there is a set budget for the public, and accessibility to local papers is simple. A national library consistently carries out the digitalization of time-honored newspapers. In addition, individual newspaper companies have also started the service, but it is not enough for such to be labeled an archive. In the United States (US), "Chronicling America"-led by the Library of Congress with funding from the National Endowment for the Humanities-is in the process of digitalizing historic newspapers. The universities of each state and historical association provide funds to their public library for the digitalization of local papers. In the United Kingdom, the British Library is constructing an online newspaper archive called "The British Newspaper Archive," but unlike the one in the US, this service charges a usage fee. The Joint Information Systems Committee has also invested in "The British Newspaper Archive," and its construction is still ongoing. ProQuest Archiver and Gale NewsVault are the representative platforms because of their efficiency and how they have established the standardization of newspapers. Now, it is time to change the way we understand things, and a drastic investment is required to improve the domestic and international online newspaper archive.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.35-57
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• 2021

This paper is to grasp the current trends of national bibliographies through analyzing representative national bibliographies using literature review, analysis of national bibliographies' web pages and survey. First, in order to conform to the definition of a national bibliography as a record of a national publication, it attempts to include a variety of materials from print to electronic resources, but in reality it cannot contain all the materials, so there are exceptions. It is impossible to create a general selection guide for national bibliography coverage, and a plan that reflects the national characteristics and prepares a valid and comprehensive coverage based on analysis is needed. Second, cooperation with publishers and libraries is being made to efficiently generate national bibliography. For the efficiency of national bibliography generation, changes should be sought such as the standardization and consistency, the collection level metadata description for digital resources, and the creation of national bibliography using linked data. Third, national bibliography is published through the national bibliographic online search system, linked data search, MARC download using PDF, OAI-PMH, SRU, Z39.50, and mass download in RDF/XML format, and is integrated with the online public access catalog or also built separately. Above all, national bibliographies and online public access catalogs need to be built in a way of data reuse through an integrated library system. Fourth, as a differentiated function for national bibliography, various services such as user tagging and national bibliographic statistics are provided along with various browsing functions. In addition, services of analysis of national bibliographic big data, links to electronic publications, and mass download of linked data should be provided, and it is necessary to identify users' needs and provide open services that reflect them in order to develop differentiated services. Through the current trends and considerations of the national bibliographies analyzed in this study, it will be possible to explore changes in national and international national bibliography.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• The Korean Journal of Archival Studies
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• no.78
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• pp.153-195
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• 2023

RDBMS is a widely used database system worldwide, and the term dataset refers to the vast amount of data produced in administrative information systems using RDBMS. Unlike business systems that mainly produce administrative documents, administrative information systems generate records centered around the unique tasks of organizations. These records differ from traditional approval documents and metadata, making it challenging to seamlessly transfer them to standard record management systems. With the 2022 revision of the 'Public Records Act Enforcement Decree,' dataset was included in the types of records for which only management authority is transferred. The core aspect of this revision is the need to manage the lifecycle of records within administrative information systems. However, there has been little exploration into how to manage dataset within administrative information systems. As a result, this research aims to design a database for a record management module that needs to be integrated into administrative information systems to manage the lifecycle of records. By modifying and supplementing ISO 16175-1:2020, we are designing an "human resource management system" and identifying and evaluating personnel management dataset. Through this, we aim to provide a concrete example of record management within administrative information systems. It's worth noting that the prototype system designed in this research has limitations in terms of data volume compared to systems currently in use within organizations, and it has not yet been validated by record researchers and IT developers in the field. However, this endeavor has allowed us to understand the nature of dataset and how they should be managed within administrative information systems. It has also affirmed the need for a record management module's database within administrative information systems. In the future, once a complete record management module is developed and standards are established by the National Archives, it is expected to become a necessary module for organizations to manage dataset effectively.

• The Korean Journal of Archival Studies
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• no.78
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• pp.197-249
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• 2023

This paper focus on the demand for broadcast and video archive contents by users outside broadcasters as the archive openness and sharing projects of terrestrial broadcasters have become more active in recent years. In the process of creating works using broadcasters' released video footage, the study examined the criteria by which video footage is selected and the methods and processes utilized for editing. To this end, the study analyzed the the case of the 5.18 footage video sharing project 〈May Story(Owol-Iyagi)〉 contest organized by KBS in 2022, in which KBS released its footage about the May 18 Democratic Uprising and invited external users to create new content using them. Analyzing the works that were selected as the winners of the contest, the research conducts in-depth interviews with the creators of each work. As a result, the following points are identified. Among the submitted works, many works deal with the direct or indirect experience of the May 18 Democratic Uprising and focus on the impact of this historical event on individuals and our current society. The study also examined the ways in which broadcasters' footage is used in secondary works. We found ways to use video as a means to share historical events, or to present video as evidence or metaphor. It is found that the need for broadcasters to provide a wider range of public video materials such as the May 18 Democratic Uprising, describing more metadata including copyright information before releasing selected footage, ensuring high-definition and high-fidelity videos that can be used for editing, and strengthening streaming or downloading functions for user friendliness. Through this, the study explores the future direction of broadcasters' video data openness and sharing business, and confirms that broadcasters' archival projects can be an alternative to fulfill public responsibilities such as strengthening social integration between regions, generations, and classes through moving images.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Korean Society of Archives and Records Management
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• v.2 no.2
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• pp.1-38
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• 2002

This study examines the status quo of Korean archives and records management from the Governmental as well as professional activities for the development of the field in relation to the new legislation on records management. Among many concerns, this study primarily explores the following four perspectives: 1) the Government Archives and Records Services; 2) the Korean Association of Archives; 3) the Korean Society of Archives and Records Management; 4) the Journal of Korean Society of Archives and Records Management. One of the primary tasks of the is to build the special depository within which the Presidential Library should be located. As a result, the position of the GARS can be elevated and directed by an official at the level of vice-minister right under a president as a governmental representative of managing the public records. In this manner, GARS can sustain its independency and take custody of public records across government agencies. made efforts in regard to the preservation of paper records, the preservation of digital resources in new media formats, facilities and equipments, education of archivists and continuing, training of practitioners, and policy-making of records preservation. For further development, academia and corporate should cooperate continuously to face with the current problems. has held three international conferences to date. The topics of conferences include respectively: 1) records management and archival education of Korea, Japan, and China; 2) knowledge management and metadata for the fulfillment of archives and information science; and 3) electronic records management and preservation with the understanding of ongoing archival research in the States, Europe, and Asia. The Society continues to play a leading role in both of theory and practice for the development of archival science in Korea. It should also suggest an educational model of archival curricula that fits into the Korean context. The Journals of Records Management & Archives Society of Korea have been published on the six major topics to date. Findings suggest that "Special Archives" on regional or topical collections are desirable because it can house subject holdings on specialty or particular figures in that region. In addition, archival education at the undergraduate level is more desirable for Korean situations where practitioners are strongly needed and professionals with master degrees go to manager positions. Departments of Library and Information Science in universities, therefore, are needed to open archival science major or track at the undergraduate level in order to meet current market demands. The qualification of professional archivists should be moderate as well.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.