• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2082-2102
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• 2018

In recent years, social network related applications such as WeChat, Facebook, Twitter and so on, have attracted hundreds of millions of people to share their experience, plan or organize, and attend social events with friends. In these operations, plenty of valuable information is accumulated, which makes an innovative approach to explore users' preference and overcome challenges in traditional recommender systems. Based on the study of the existing social network recommendation methods, we find there is an abundant information that can be incorporated into probability matrix factorization (PMF) model to handle challenges such as data sparsity in many recommender systems. Therefore, the research put forward a unified social network recommendation framework that combine tags, trust between users, ratings with PMF. The uniformed method is based on three existing recommendation models (SoRecUser, SoRecItem and SoRec), and the complexity analysis indicates that our approach has good effectiveness and can be applied to large-scale datasets. Furthermore, experimental results on publicly available Last.fm dataset show that our method outperforms the existing state-of-art social network recommendation approaches, measured by MAE and MRSE in different data sparse conditions.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.45-56
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• 2007

Recently, much research has been actively conducted for a new kind of network environment ubiquitous computing. This paper will define the smart-tag technology required by a ubiquitous environment. We will describe how to apply smart-tag-related Radio Frequency Identification(RFID) research for GIS in underground social infrastructure, a local-area wireless-communication technology. Application development is important that will be able to materialize a network environment. This research promotes various application developments, such reason currently it establishes the IT 839 from domestic. The geographic information system construction is a part of IT 839. The research which is various becomes accomplished for the ubiquitous of social base facility from domestic. Consequently, in this paper analyzes the geographic information system of existing, researches based RFID underground social infrastructure management system development. The Proposed method is complements the method of existing, and is efficient for underground social infrastructure. This system is new management system for underground social infrastructure, and provides safe administrator function using authentication of active RFID tag. It provides real processing and autonomy of administrator.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.181-195
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• 2010

The participation and share between personal users are the driving force of Web 2.0, and easily found in blog, social network, collective intelligence, social bookmarking and tagging. Among those applications, the social bookmarking lets Internet users to store bookmarks online and share them, and provides various services based on shared bookmarks which people think important.Delicious.com is the representative site of social bookmarking services, and provides a bookmark search service by using tags which users attach to the bookmarks. Our paper suggests a method re-ranking the ranks from Delicious.com based on user tags in order to provide personalized bookmark recommendations. Moreover, a method to consider bookmarks which have tags not directly related to the user query keywords is suggested by using tag network based on Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare the ranks by Delicious.com with new ranks of our system.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.133-140
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• 2012

In this paper, we propose a music recommendation method considering users' tags by collaborative tagging in a social music site. Since collaborative tagging allows a user to add keywords chosen by himself to web resources, it provides users' preference about the web resources concretely. In particular, emotional tags which represent human's emotion contain users' musical preference more directly than factual tags which represent facts such as musical genre and artists. Therefore, to classify the tags into the emotional tags and the factual tags and to assign weighted values to the emotional tags, a tag ontology called UniTag is developed. After preprocessing the tags, the weighted tags are used to create user profiles, and the music recommendation algorithm is executed based on the profiles. To evaluate the proposed method, a conventional playcount-based recommendation, an unweighted tag-based recommendation, and an weighted tag-based recommendation are executed. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.

• Journal of the Korean Society for information Management
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• v.27 no.1
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• pp.41-60
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• 2010

This study aims to analyze the properties of the tags used in the fiction genre, the structural aspect of the patterns and the contents of the tags by utilizing LibraryThing, where the tags are assigned in work units of FRBR. A comparative analysis was conducted in terms of the level of association between the descriptive terms in bibliography and LCSH terms. The study also examined the sources of the tags not included in the bibliographic descriptions or LCSHs, what aspects of work they represented, and the terms used as tags in relation to the work. By restricting the study to a single genre, a number of tags that reflected the characteristics of fiction (three elements of the fiction which are theme, plot, style and three elements of the fiction composition which are character, event, setting) were extracted. This study finds out the role of the tag making up the taxonomy and proposes a new direction for the tagging system by demonstrating the possibility of using tags as facets in information organization and retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1460-1478
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• 2020

This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.211-227
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• 2022

Illegal gambling through online gambling sites has become a significant social problem. The development of Internet technology and the spread of smartphones have led to the proliferation of illegal gambling sites, so now illegal online gambling has become accessible to anyone. In order to mitigate its negative effect, the Korean government is trying to detect illegal gambling sites by using self-monitoring agents or reporting systems such as 'Nuricops.' However, it is difficult to detect all illegal sites due to limitations such as a lack of staffing. Accordingly, several scholars have proposed intelligent illegal gambling site detection techniques. Xu et al. (2019) found that fake or illegal websites generally have unique features in the HTML tag structure. It implies that the HTML tag structure can be important for detecting illegal sites. However, prior studies to improve the model's performance by utilizing the HTML tag structure in the illegal site detection model are rare. Against this background, our study aimed to improve the model's performance by utilizing the HTML tag structure and proposes Tag2Vec, a modified version of Doc2Vec, as a methodology to vectorize the HTML tag structure properly. To validate the proposed model, we perform the empirical analysis using a data set consisting of the list of harmful sites from 'The Cheat' and normal sites through Google search. As a result, it was confirmed that the Tag2Vec-based detection model proposed in this study showed better classification accuracy, recall, and F1_Score than the URL-based detection model-a comparative model. The proposed model of this study is expected to be effectively utilized to improve the health of our society through intelligent technology.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• KIISE Transactions on Computing Practices
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• v.23 no.9
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• pp.550-556
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• 2017

Due to the rapid growth and development of Internet of Things (IoT), various devices are now accessible and controllable anytime from anywhere. However, the current IoT system requires a series of complex steps (e.g., launch an application, choose a space and thing, control the thing, etc.) to control the IoT devices; therefore, IoT suffers from a lack of efficient and intuitive methods of interacting with users. To address this problem, we propose a novel IoT control framework based on IoT tags and social messages. The proposed system provides an intuitive and efficient way to control the device based on the device ownership: 1) users can easily control the device by IoT tagging, or 2) users can send an IoT social message to the device owner to request control of the tagged device. Through the development of the prototype system, we show that the proposed system provides an efficient and intuitive way to control devices in the IoT environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1068-1072
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• 2014

We propose a collaborative social tagging for eBook using external DSL approach. The goal of this paper is (1) to provide DSL by which authors can write HTML5 rich contents ebook and tag resources, (2) to make users enhance book by tagging resources easily, (3) to make readers read rich book easily regardless of their devices types, (4) to provide ebook resources of RESTful address style by which other system can identify self-descriptive resources of book. To achieve the goal, we provide Bukle DSL language by which author and users can author and enhance ebook with ease. As a domainspecific language Bukle provides a simple yet expressive language for authoring and tagging books that would otherwise be more difficult to express with a general purpose language. Further work includes visual DSL approach and tools by using that the unskilled users could tag book easily. In order that future work also includes text-to-visual DSL transform engine. UX research is also required to tag and to author book. To tackle the above questions we are looking at using visual notation focusing visual syntax.