• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.31-43
• /
• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.3
• /
• pp.292-297
• /
• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• The KIPS Transactions:PartD
• /
• v.19D no.1
• /
• pp.105-112
• /
• 2012

Most methods for detecting PVC and APC require the measurement of accurate QRS complex, P wave and T wave. In this study, we propose new algorithm for detecting PVC and APC without using complex parameter and algorithms. Proposed algorithm have wide applicability to abnormal waveform by personal distinction and difference as well as all sorts of normal waveform on ECG. To achieve this, we separate ECG signal into each unit patterns and made a standard unit pattern by just using unit patterns which have normal R-R internal. After that, we detect PVC and APC by using similarity analysis for pattern matching between standard unit pattern and each unit patterns.

• Journal of the Korea Convergence Society
• /
• v.8 no.4
• /
• pp.25-36
• /
• 2017

As smartphone users have increased in recent years, various applications have been developed and used especially for Android-based mobile devices. However, malicious applications developed by attackers for malicious purposes are also distributed through 3rd party open markets, and damage such as leakage of personal information or financial information of users in mobile terminals is continuously increasing. Therefore, to prevent this, a method is needed to distinguish malicious apps from normal apps for Android-based mobile terminal users. In this paper, we analyze the existing researches that detect malicious apps by extracting the system call events that occur when the app is executed. Based on this, we propose a technique to identify malicious apps by analyzing the sequence similarity of kernel layer events occurring in the process of running an app on commercial Android mobile devices.

• Journal of Information Science Theory and Practice
• /
• v.7 no.1
• /
• pp.29-38
• /
• 2019

Information retrieval is the challenge of the Web 2.0 world. The experiment of knowledge organisation in the context of abundant information available from various sources proves a major hurdle in obtaining information retrieval with greater precision and recall. The fast-changing landscape of information organisation through social networking sites at a personal level creates a world of opportunities for data scientists and also library professionals to assimilate the social data with expert created data. Thus, folksonomies or social tags play a vital role in information organisation and retrieval. The comparison of these user-created tags with expert-created index terms, author keywords and title words, will throw light on the differentiation between these sets of data. Such comparative studies show revelation of a new set of terms to enhance subject access and reflect the extent of similarity between user-generated tags and other set of terms. The CiteULike tags extracted from 5,150 scholarly journal articles in marine science were compared with corresponding Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title terms. The Jaccard similarity coefficient method was employed to compare the social tags with the above mentioned wordsets, and results proved the presence of user-generated keywords in Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title words. While using information retrieval techniques like stemmer and lemmatization, the results were found to enhance keywords to subject access.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.645-654
• /
• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Lingua Humanitatis
• /
• v.2 no.2
• /
• pp.321-347
• /
• 2002

The Russian language uses more words that imply collectivism than Western Indo-European languages. In Korean, the first-person plural pronouns are used more often than in Western languages. In this respect, Russian seems to stand closer to the latter, although typologically it belongs to the Indo-European family. The predominance of 'we' over 'I,' which took place in the history of the Russian language, had something to do with the Russian commune and the ecclesiastical and spiritual concept of 'sobornost' (equation omitted). A similarity between the Russian and the Korean nations lies in a collective way of life as compared to Western nations. The Russian concepts of (equation omitted) and (equation omitted) ('commune') have direct analogues in the Korean language. In all societies a commune involves a certain sense of collectivity, or spiritual unity of the people - 'sobornost' (equation omitted). Korean collectivity is more familial and moral in character, whereas Russian 'sobornost' is more spiritual. This has its direct reflection in Korean and Russian languages. One can say that a sort of a family version of Russian 'sobornost' takes place in Korean society.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.2
• /
• pp.119-124
• /
• 2016

According to the expansion of smartphone penetration and development of wearable device, personal context information can be easily collected. To use this information, the context aware recommender system has been actively studied. The key issue in this field is how to deal with the context information, as users are influenced by different contexts while rating items. But measuring the similarity among contexts is not a trivial task. To solve this problem, we propose context aware post-filtering to apply the context compensation. To be specific, we calculate the compensation for different context information by measuring their average. After reflecting the compensation of the rating data, the mechanism recommends the items to the user. Based on the item recommendation list, we recover the rating score considering the context information. To verify the effectiveness of the proposed method, we use the real movie rating dataset. Experimental evaluation shows that our proposed method outperforms several state-of-the-art approaches.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.6 no.1
• /
• pp.143-149
• /
• 2010

In ubiquitous environment, information retrieval using collaborative filtering is a popular technique for reducing information overload. Collaborative filtering systems can produce personal recommendations by computing the similarity between your preference and the one of other people. We integrate the collaboration filtering method and context-aware information retrieval method. The proposed method enables to find some relevant information to specific user's contexts. It aims to makes more effective information retrieval to the users. The proposed method is conceptually comprised of two main tasks. The first task is to tag context tags by automatic tagging technique. The second task is to recommend items for each user's contexts integrating collaborative filtering and information retrieval. We describe a new integration method algorithm and then present a u-commerce application prototype.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.628-631
• /
• 2009

In this paper, we proposed a new authentication method using video that was taken during moving a hand-held camera in front of the face. The proposed method extracted individuality from the obtained image sequences using the parametric eigenspace scheme. Changes of facial appearance through authentication trials draw continuous tracks in the low dimensional igenspace. The similarity between their continuous tracks are calculated by DP-matching to verify their identities. Experimental results confirmed that different motions and persons change the shapes of continuous tracks, so the proposed method could identify the person.