• Korean Business Review
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• v.15
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• pp.79-97
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• 2002

In this study, an analytical CRM for customer segmentation is exercised by integrating and analyzing the customer profile data and the access data to a particular web site. We believe that effective customer segmentation will be possible with a basis of the understanding of customer characteristics as well as behavior on the web. One of the critical tasks in the web data-mining is concerned with both 'how to collect the data from the web in an efficient manner?' and 'how to integrate the data(mostly in a variety of types) effectively for the analysis?' This study proposes a panel approach as an efficient data collection method in the web. For the customer data analysis, OLAF and a tree-structured algorithm are applied in this study. The results of the analysis with both techniques are compared, confirming the previous work which the two techniques are inter-complementary.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.586-594
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• 2012

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on AP's probabilistic position estimation, we develop an AP distribution map and new pattern matching algorithm for position estimation. The developed approaches can strengthen the advantages of Radio fingerprint based Wi-Fi Positioning System, especiall on the algorithms and data handling. Compared on the existing approaches of fingerprint pattern matching algorithm, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore all fingerprint data have been harvested from the actual measurement of radio fingerprint of Seoul, Kangnam area. This can approve the practical usefulness of proposed methodology.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.219-228
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• 2012

As the wireless Internet become more widely accessible, variety of Internet services can be used without limitation of location. However, existing mobility management methods such as MIP and PMIP of IETF requires the load of heavy protocol stack on the mobile nodes or the addition of components such as LMA and MAG. In this paper, we proposed the location management technique in the PMIPv6 and Fast Handover technique. according to the moving pattern of the node, the location management technique proposed in order to adjust the paging area dynamically. The Fast Handover technique applied MIH technology and it reduced the handover signal processing time between heterogeneous network. The location management cost in the environment which the node moves in order to evaluate this and handover delay time was calculate. The proposal technique was efficiently more evaluated than PMIPv6 with the smallest 29% and maximum 83%.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.499-508
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• 2015

High utility itemset(HUI) mining refers to the discovery of itemsets with high utilities which are not less than a user-specified minimum utility threshold, by considering both the quantities and weight factors of items in a transaction database. Recently the utility-list based HUI mining algorithms have been proposed to avoid numerous candidate itemsets and the algorithms need the costly join operations. In this paper, we propose a new HUI mining algorithm, using the utility-list with additional attributes of transaction utility and common utility of itemsets. The new algorithm decreases the number of join operations and efficiently prunes the search space. Experimental results on both synthetic and real datasets show that the proposed algorithm outperforms other recent algorithms in runtime, especially when datasets are dense or contain many long transactions.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.357-368
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• 2006

This paper discusses the way of processing time-series subsequence matching under time warping. Time warping enables finding sequences with similar patterns even when they are of different lengths. The prefix-querying method is the first index-based approach that performs time-series subsequence matching under time warping without false dismissals. This method employs the $L_{\infty}$ as a base distance function for allowing users to issue queries conveniently. In this paper, we extend the prefix-querying method for absorbing $L_1$, which is the most-widely used as a base distance function in time-series subsequence matching under time warping, instead of $L_{\infty}$. We also formally prove that the proposed method does not incur any false dismissals in the subsequence matching. To show the superiority of our method, we conduct performance evaluation via a variety of experiments. The results reveal that our method achieves significant performance improvement in orders of magnitude compared with previous methods.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.235-242
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• 2005

As the demands in a wireless network are recently increasing, it is necessary to promote the power efficiency of a wireless terminal, and to reduce the overhead of a network. To resolve such problems, we propose the paging technology and the structure of paging area with the joint access point in HPi (High-speed Portable Internet) network, which is being studied as the domestic next-generation IP packet data network. The application of the paging technology to the HPi network possesses the advantage of reducing the registration cost while a terminal in dormant state moves around, and the reporting cost of the terminal's location by the joint access point. The technology suggested in this paper causes the advantages that it promotes the power efficiency in user's point of view while it reduces the network overhead and makes the easy rearrangement of joint APs according to the changes of users' moving pattern in the network manager's point of view.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.447-454
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• 2001

Various caching and prefetching algorithms have been investigated to identify and effective method for improving the performance of I/O devices. A prefetching algorithm decreases the processing time of a system by reducing the number of disk accesses when an I/O is needed. This paper proposes an AMBA prefetching method that is an extended version of the OBA prefetching method. The AMBA prefetching method will prefetching blocks continuously as long as disk bandwidth is enough. In this method, though there were excessive data request rate, we would expect efficient prefetching. And in the AMBA prefetching method, to prevent the cache pollution, it limits the number of data blocks to be prefetched within the cache area. It can be implemented in a user-level File System based on a Linux Operating System. In particular, the proposed prefetching policy improves the system performance by about 30∼40% for large files that are accessed sequentially.

• KIISE Transactions on Computing Practices
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• v.21 no.4
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• pp.290-298
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• 2015

This paper suggests a multi-agent message transport architecture based on the message-oriented middleware ZeroMQ. Compared with the other middlewares such as CORBA, Ice, and Thrift, ZeroMQ receives a good score in the evaluation of performance, QoS (Quality of Service), patterns, user friendliness, and resources. The suggested message transfer architecture borrowed many basic concepts like agent platform, AMS (Agent Management System), and MTS (Message Transfer System) from FIPA (Foundation for Intelligent Physical Agents) standard multi-agent specifications, and the architecture inherited the strength of the architecture from the multi-agent framework SMAF (Smart Multi-Agent Framework). The architecture suggested in this paper is a novel peer-to-peer architecture which is not known to the ZeroMQ community. In the suggested architecture, every MTS agent uses only one ZeroMQ router socket to support peer-to-peer communication among MTS agents. The suggested architecture can support closely collaborating software areas such as intelligent robots as well as the traditional application areas of multi-agent architecture. The suggested architecture has interoperability and scalability with the ZeroMQ devices and patterns.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.17-26
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• 2021

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.