• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.111-127
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• 2003

The purpose of this study is to ascertain whether event tracking is more effective in event retrieval than information filtering. This study examined the two techniques for event retrieval to suggest the more effective one. The event-retrieval performances of the event tracking technique based on a kNN classifier and the query-based information filtering technique were compared. Two event tracking experiments, one with the static training set and the other with the dynamic training set , were carried out. Two information filtering experiments, one with initial queries and the other with refined queries, were also carried out to evaluate the event-retrieval effectiveness. We found that the event tracking technique with the static training set performed better than on with the dynamic training set. It was also found that the information fitering technique using intial queries performed better than one using the refined queries. In conclusion, the comparison of the best cases of event tracking and information filtering revealed that the information filtering technique outperformed the event tracking technique in event retrieval.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.549-554
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• 2002

This paper proposes a UQoSM (User Qualify of Service Middleware) framework for multimedia application systems. UQoSM system is extended the existing event service model added to the event monitoring, reflective event filtering and event dispatcher for supporting multimedia application systems. Especially, this paper is concentrated on providing suitable reflective event filtering function for multimedia application service system in order to meet various user requirements under inter-based environment. It means this system provides high QoS to users. In addition, it results in decreasing network traffic as unnecessary event information is filtered from network.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.141-145
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• 2008

Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5S
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• pp.1666-1675
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• 2000

This paper proposes a RTWM (Real-Time Web Middleware) framework for real-time EC(Electronic Commerce) systems. RTWM system is extended the existing COS( CORBA Object Service) model added to the event monitoring, real-time scheduler, real-time event filtering for supporting real-time concept of EC systems. Especially, this paper is concentrated on providing suitable event filtering function for EC system in order to meed various user time requirements under distributed system environment. It stores time constraint requirements an interesting event information input from users into QoS repository, then processes the data through appropriate RTFA(Real-Time Filtering Agent) module when real-time events occur. From this method, users can get the filtered event result reflected their requirements about real-time filtering. It means this system provides thigh QoS to users. In addition, it results in decreasing network traffic as unnecessary event information is filtered from network.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.335-345
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• 2017

Recently, location systems using RFID technology have been studied in indoor environments. However, the existing techniques require high computational cost to compute the location of a moving object because they compare the location proximity of all reference tags and objects. In this paper, we propose an RFID based location positioning scheme using event filtering, which reduces the computation cost of calculating the locations of moving objects while maintaining the accuracy of location estimation. In addition, we propose an incremental location update policy to reduce the location update cost for moving objects. We also compare the proposed scheme with one of the localization schemes, LANDMARC using a performance evaluation. As a result, the proposed scheme outperforms LANDMARC in terms of the computational cost of location estimation. The proposed scheme also reduces the cost of location update by using the RFID-based update policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.683-690
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• 2011

The conventional sensor tag data filtering algorithm uses time window based data filtering for each tag data. However, this approach shows many performance problems such as low error and event detection rate and larger storage size requirement. In this paper, we propose a collaborative sensor tag data filtering algorithm to improve sensor data processing performance. simulation study shows that the proposed sensor tag filtering algorithm outperforms the conventional filtering algorithm in terms of the processing time, the size of required data storage memory and accuracy of error and event detection rate.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.504-512
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• 2016

In this paper, we propose a personalized event recommendation scheme using user's activity analysis and collaborative filtering in social network environments. The proposed scheme predicts un-evaluated attribute values through analysis of user activities, relationships, and collaborative filtering. The proposed scheme also incorporates a user's recent preferences by considering the recent history for the user or context-aware information to precisely grasp the user's preferences. As a result, the proposed scheme can recommend events to users with a high possibility to participate in new events, preventing indiscriminate recommendations. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluation.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.482-489
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• 2006

How to process event message traffic efficiently is important to collaboration among multiple distributed users, and it is a key research issue in the virtual environment fields. AOI model is one of solutions for this problem; which reduces message traffic by restricting event propagation region into an area in which a user is interested. However, in previous systems, it is difficult to adapt to dynamic environment where changes in the number and movement of participants are frequent. This paper proposes a new event management model, called extended AOI model, which is helpful to improve flexibility and efficiency of traditional models, and is able to extend its functions by introducing multi-layered regions. The proposed model can be applied to DVE and MMORPG as an event filtering model.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.345-350
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• 2016

This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.