• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.433-438
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• 2003

Recently, some studies of a web-based information recommendation technique which provides users with the most necessary information through websites like a web-based shopping mall have been conducted vigorously. In most cases of web information recommendation techniques which rely on a user profile and a specific feedback from users, they require accurate and diverse profile information of users. However, in reality, it is quite difficult to acquire this related information. This paper is aimed to suggest an information prediction technique for a web information service without depending on the users'specific feedback and profile. To achieve this goal, this study is to design and implement a Dynamic Web Information Prediction System which can recommend the most useful and necessary information to users from a large volume of web data by designing and embodying Ensemble Support Vector Machine and hybrid SOM algorithm and eliminating the scarcity problem of web log data.

• Journal of Computing Science and Engineering
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• v.11 no.3
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• pp.92-99
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• 2017

Memcached, commonly used to speed up the data access in big-data and Internet-web applications, is a system software of the distributed-cache mechanism. But it is subject to the severe challenge of the loss of recently uncommitted updates in the case where the Memcached servers crash due to some reason. Although the replica scheme and the disk-log-based replay mechanism have been proposed to overcome this problem, they generate either the overhead of the replica synchronization or the persistent-storage overhead that is caused by flushing related logs. This paper proposes a scheme of backing up the write requests (i.e., set and add) on the Memcached client side, to reduce the overhead resulting from the making of disk-log records or performing the replica consistency. If the Memcached server fails, a timestamp-based recovery mechanism is then introduced to replay the write requests (buffered by relevant clients), for regaining the lost-data updates on the rebooted Memcached server, thereby meeting the data-consistency requirement. More importantly, compared with the mechanism of logging the write requests to the persistent storage of the master server and the server-replication scheme, the newly proposed approach of backing up the logs on the client side can greatly decrease the time overhead by up to 116.8% when processing the write workloads.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.341-346
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• 2012

This paper reports the findings of research into the effect of flow experience and internet addiction on e-learning participation. The total number of access, playing time of contents and lag time (time between content upload and first access) were investigated as e-learning participation by analyzing web log data. The paper also examines the relationship between academic achievement and e-learning participation. The results suggest that the flow experience significantly correlates with all variables related with e-learning participation and internet addiction significantly correlates with lag time. It is found that female students significantly access more, longer and have shorter lag time than their male counterparts. It also suggest total number of access, lag time and gender difference have significant effect on academic achievement.

• Genomics & Informatics
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• v.13 no.3
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• pp.86-89
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• 2015

Because there are clear molecular differences entailing different treatment effectiveness between Korean and non-Korean cancer patients, identifying distinct molecular characteristics of Korean cancers is profoundly important. Here, we report a web-based data repository, namely Korean Cancer Genome Database (KCGD), for searching gene signatures associated with Korean cancer patients. Currently, a total of 1,403 cancer genomics data were collected, processed and stored in our repository, an ever-growing database. We incorporated most widely used statistical survival analysis methods including the Cox proportional hazard model, log-rank test and Kaplan-Meier plot to provide instant significance estimation for searched molecules. As an initial repository with the aim of Korean-specific marker detection, KCGD would be a promising web application for users without bioinformatics expertise to identify significant factors associated with cancer in Korean.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.423-432
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• 2009

Advances in information and communication technologies are changing our society greatly. In knowledge-based society, information can be obtained easily via communication tools such as web and e-mail. However, obtaining right and up-to-date information is difficult in spite of overflowing information. The concept of adaptive web site has been initiated recently. The purpose of the site is to provide information only users want out of tons of data gathered. In this paper, an algorithm is developed for adaptive web site construction. The proposed algorithm is based on association rules that are major principle in adaptive web site construction. The algorithm is constructed by analysing log data in web server and extracting meaning documents through finding behavior patterns of users. The proposed algorithm has the following characteristics. First, it is superior to existing algorithms using association rules in time complexity. Its superiority is proved theoretically. Second, the proposed algorithm is effective in space complexity. This is due to that it does not need any intermediate products except a linked list that is essential for finding frequent item sets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.349-352
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• 2000

As a lot of people have used electronic commerce, many shopping malls have appeared on the Interne and the shopping information in them has been enormous. So, the need for a system to recommend product to customers is on the increase so as to reduce time and efforts for shopping. In this paper, we suppose a Product Recommender System which is constructed by applying data mining techniques to web for files and analyzing customer's action pattern, customer's profile and product purchase data. This system offers convenience that customers can get their desired information easily, by sending e-mail or mail and recommending web pages when they visit a shopping mall.

• Journal of Digital Contents Society
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• v.12 no.2
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• pp.241-252
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• 2011

During the last decades, other parts of operating systems, storage devices, and media are changed steadily, whereas filesystem is changed little. As data is grown bigger, the number of files to be managed also increases in geometrically. Researches about new filesystem schemes are being done widely to support these files efficiently. In web document search area, there are many researches about finding meaningful documents using semantic search. Many researches tried to apply these schemes, which is been proven in web document search previously, to filesystems. But they've focused only on higher layer of filesystem, that is not related seriously to storage media. Therefore they're not well tuned to physical characteristics of new flash memory based SSD which has different features against traditional HDD. We enhance log structured filesystem, that is already well known to work better in SSD, by putting semantic search scheme to and with multi logging point.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.43-48
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• 2016

This study is to examine how big data collects user's information and is used; the status quo of exposures of user's information, and various measures of self-control by the user. This study is also to look their ethical issues and discuss problems of privacy concerning big data. As a way for users to self-control their information, they need to check the log-in state of web portal sites and set up their account so that customized advertisement and location information cannot be tracked. When posting a blog, the value of posting should be controlled. When becoming a member of a web site, users must check the access terms before agreement and beware of chained agreements and/or membership joins in order to control the exposure of their personal information. To prevent information abuse through big data through which user's information is collected and analyzed, all users must have the right to control, block or allow personal information. For an individual to have the right to control over his information, users must understand the concept of user's information and practice ethics accompanied by newly given roles in the Internet space, which will lead to the establishment of the sound and mature information society on the Internet.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.58-60
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• 2001

하루에도 수십 수백 메가 바이트까지 증가하는 웹 로그 데이터를 이용하여 실시간에 다차원분석을 가능하게 하기 위해서는 OLAP의 적용이 필요하다. 하지만 OLAP을 적용하는데 있어서 빠른 응답시간을 얻기 위해 사전처리(Precomputation)를 수행 할 시 심각한 데이터의 희박성으로 인해 데이터 폭발 현상이 발생된다. 본 논문에서는 실제 웹 로그 데이터를 사용하여 OLAP적용 시 희박성을 일으키는 원인들을 밝히고, 2, 3 차원에서의 희박성 형태를 분석함으로써 웹 로그 데이터의 희박성 처리 방식 및 성능평가에 기반이 되게 한다.