• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.11-24
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• 2019

The tendency of buyers of web information is changing from the cost-effectiveness to the cost-satisfaction. There is such tendency in the recommendation of multimedia contents, some of which are folksonomy-based recommendation services using mood. However, there is a problem that they does not consider synonyms. In order to solve this problem, some studies have solved the problem by defining 12 moods of Thayer model as AV values (Arousal and Valence), but the recommendation performance is lower than that of a keyword-based method at the recall level 0.1. In this paper, we propose a method based on using mood vector of multimedia contents. The method can solve the synonym problem while maintaining the same performance as the keyword-based method even at the recall level 0.1. Also, for performance analysis, we compare the proposed method with an existing method based on AV value and a keyword-based method. The result shows that the proposed method outperform the existing methods.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.381-400
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• 2009

This study intends to make a comprehensive inquiry into the meaning and limitations of Folksonomy, and to explore how to make full use of Folksonomy in library cataloging. To this end, this study examined as follows : (1) how the philosophical meaning of Folksonomy is different from traditional principles of library cataloging, (2) what the viewpoint of LIS scholars toward Folksonomy are, and how North American libraries have customized Folksonomy for their catalogs. In addition, (3) usefulness of Folksonomy in library catalogs is thoroughly discussed. Based on these, (4) the final discussion includes strategies for Korean LIS scholars and library practitioners to consider when applying Folksonomy to Korea library contexts.

• 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.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.284-295
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• 2019

In the recent times, a personalized travel path recommendation based on both travelogues and community contributed photos and the heterogeneous meta-data (tags, geographical locations, and date taken) which are associated with photos have been studied. The travellers using social media leave their location history, in the form of paths. These paths can be bridged for acquiring information, required, for future recommendation, for the future travellers, who are new to that location, providing all sort of information. In this paper, we propose a personalized travel path recommendation scheme, based on social life log. By taking advantage, of two kinds of social media, such as travelogue and community contributed photos, the proposed scheme, can not only be personalized to user's travel interest, but also be able to recommend, a travel path rather than individual Points of Interest (POIs). The proposed personalized travel route recommendation method consists of two steps, which are: pruning POI pruning step and creating travel path step. In the POI pruning step, candidate paths are created by the POI derived. In the creating travel path step, the proposed scheme creates the paths considering the user's interest, cost, time, season of the topic for more meaningful recommendation.

• Journal of KIISE
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• v.44 no.1
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• pp.71-77
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• 2017

There has been a recent spate in the usage of mobile device equipped GPS sensors, such as smart phones. This trend enables the posting of geo-tagged messages (i.e., multimedia messages with GPS locations) on social media such as Twitter and Facebook, and the volume of such spatial data is rapidly growing. However, the relationships between the location and content of messages are not always explicitly shown in such geo-tagged messages. Thus, the need arises to reorganize search results to find the relationship between keywords and the spatial distribution of messages. We find the smallest minimum bounding rectangle (MBR) that embedding k or more points in order to find the most dense rectangle of data, and it can be usefully used in the location search system. In this paper, we suggest efficient algorithms to discover a group of 2-Dimensional spatial data with a close distance, such as MBR. The efficiency of our proposed algorithms with synthetic and real data sets is confirmed experimentally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.715-721
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• 2018

With the spread of mobile devices, the users of social network services or e-commerce sites have increased dramatically, and the amount of data produced by the users has increased exponentially. E-commerce companies have faced a task regarding how to extract useful information from a vast amount of data produced by the users. To solve this problem, there are various studies applying big data processing technique. In this paper, we propose a collaborative filtering method that applies the tag weight in the Apache Spark platform. In order to elevate the accuracy of recommendation, the proposed method refines the tag data in the preprocessing process and categorizes the items and then applies the information of periods and tag weight to the estimate rating of the items. After generating RDD, we calculate item similarity and prediction values and recommend items to users. The experiment result indicated that the proposed method process large amounts of data quickly and improve the appropriateness of recommendation better.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.493-504
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• 2017

Recently, tremendous amounts of unstructured text data that is distributed through news, blogs, and social media has gained much attention from many researchers and practitioners as this data contains abundant information about various consumers' opinions. However, as the usefulness of text data is increasing, more and more attempts to gain profits by distorting text data maliciously or nonmaliciously are also increasing. This increase in spam text data not only burdens users who want to obtain useful information with a large amount of inappropriate information, but also damages the reliability of information and information providers. Therefore, efforts must be made to improve the reliability of information and the quality of analysis results by detecting and removing spam data in advance. For this purpose, many studies to detect spam have been actively conducted in areas such as opinion spam detection, spam e-mail detection, and web spam detection. In this study, we introduce core concepts and current research trends of spam detection and propose a methodology to detect the spam tag of a blog as one of the challenging attempts to improve the reliability of blog information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.960-966
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• 2012

It is prevalent to gather the location information from GPS, WiFi and etc, and therefore LBSNS (Location-Based SNS) has increased rapidly (such as location-augmented Twitter services). The message created from LBSNS include the specific area of interests which the message is created in or mentions. It is easy to propagate the location-based information of LBSNS by adapting the retweet function which is efficient way to propagate the message in tweeter. In this paper, we have defined the smart retweet as a automatic retweet function for efficient propagating the messages which is geo-tagging the location of interests. We have designed the smart retweet system based on the tweeter system. The user could specify the area of interests and build the social networking among the users which have interested in common area. The smart retweet system have been implemented by mesh-up services based on Open-API of trweeter and google map. It is expected that the smart retweet service proposed in this paper makes easy sharing of the location-based interesting information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.189-206
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• 2011

This paper proposes a conceptual framework to explore the ways in which people work with in accessing, sharing, and navigating Web resources. In order to provide a better frame of a user's interaction with a folksonomy, an information foraging approach was adapted that denotes adaptive information seeking behaviors of users within human information interaction. A conceptual framework that consists of three different components from users' points of view was proposed: tagging, navigation, and knowledge sharing. This understanding will help us to motivate possible future directions of research in folksonomy and lay the groundwork for empirical research which focuses on qualitative analysis of a folksonomic and users' tagging behaviors.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.87-107
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• 2022

This study aims to understand the possibility of small city marketing strategies using B-grade cultural contents. This research focused on the case of Chungju City which applied B-grade cultural contents to city marketing. The process using B-grade cultural contents to small city marketing was investigated and hash-tags and comments on social media were coded and analyzed based on grounded theory. Also, the details were examined through in-depth interviews with the local government official in charge. The result has shown the characteristics of B-grade cultural contents describing the differences from the original B-grade culture as subcuture. First, publicity materials showed the characteristics of general B-grade culture such as retro, puns, and escape, showing the process of communication/participation/empathy. Second, improbability, intertextuality, extensibility, subversiveness, and authenticity were the five main factors for responses and empathy from the audience. Third, the ripple effect was formed through the simple narrative structure of 'intro-conclusion'. Finally B-grade cultural contents of Chungju showed new possibilities for sustainable small city marketing through the formation of new cultural assets.