• Journal of the Korean Society for information Management
• /
• v.36 no.4
• /
• pp.183-205
• /
• 2019

Among the various methods for identifying users's information needs, Log analysis methods can realistically reflect the users' actual search behavior and analyze the overall usage of most users. Based on the large quantity of query log big data obtained through the portal service of the National Archives of Korea, this study conducted an analysis by the information type and search result type in order to identify the users' information needs. The Query log used in analysis were based on 1,571,547 query data collected over a total of 141 months from 2007 to December 2018, when the National Archives of Korea provided search services via the web. Furthermore, based on the analysis results, improvement methods were proposed to improve user search satisfaction. The results of this study could actually be used to improve and upgrade the National Archives of Korea search service.

• Journal of Korean Library and Information Science Society
• /
• v.39 no.1
• /
• pp.265-278
• /
• 2008

This study aims to perform an evaluation of unified search services provided by major Korean search portals, Naver, Daum, Yahoo-Korea, and Empas. These unified search services are evaluated in terms of the relevance of search results. In conducting this study, real queries that real users submitted were used. This study also utilized click logs that consist of documents users clicked and viewed. The results of this study can be implemented to the development and improvement of portal's unified search services. Users can refer to the results of this study in choosing unified search services from search portals.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.2
• /
• pp.382-389
• /
• 2018

Recently cyber attacks can cause serious damage on various information systems. Log data analysis would be able to resolve this problem. Security log analysis system allows to cope with security risk properly by collecting, storing, and analyzing log data information. In this paper, a security log analysis system is designed and implemented in order to analyze security log data using the Logstash in the Elasticsearch, a distributed search engine which enables to collect and process various types of log data. The Kibana, an open source data visualization plugin for Elasticsearch, is used to generate log statistics and search report, and visualize the results. The performance of Elasticsearch-based security log analysis system is compared to the existing log analysis system which uses the Flume log collector, Flume HDFS sink and HBase. The experimental results show that the proposed system tremendously reduces both database query processing time and log data analysis time compared to the existing Hadoop-based log analysis system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37A no.10
• /
• pp.841-849
• /
• 2012

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a $4{\times}4$ system, the proposed algorithm shows a performance degradation of less than 0.1dB.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.15 no.4
• /
• pp.477-483
• /
• 2015

The k-Winners-Take-All (kWTA) is an operation to find the largest k (>1) inputs among N inputs. Parallel search algorithm of kWTA for digital inputs is not invented yet, so most of digital kWTA architectures have O(N) time complexity. A parallel search algorithm for digital kWTA operation and the circuits for its VLSI implementation are presented in this paper. The proposed kWTA architecture can compare all inputs simultaneously in parallel. The time complexity of the new architecture is O(logN), so that it is scalable to a large number of digital data. The high-speed kWTA operation and its O(logN) dependency of the new architecture are verified by simulations. It takes 290 ns in searching for 5 winners among 1024 of 32 bit data, which is more than thousands of times faster than existing digital kWTA circuits, as well as existing analog kWTA circuits.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.3
• /
• pp.144-149
• /
• 1998

This paper presents a fast motion estimation algorithm, 5DS, useful for video coding. We first try block matching to 4 directions(N, E, W, S) to estimate motions in this algorith, since most of motions in video are oriented to those direction, and then try one additional diagonal matching between the matching ponts having small MADs. It makesthis algorithm possible for searching through a diagonal direction which is not adequate to logarithmic (LOG) search algorithm. This proposed algorithm has almost same PSNR but, 1.9, 1.2 times faster than classical block matching methods such as three steps search(TSS) and LOG search algorithms.

• Journal of the Korean Society for information Management
• /
• v.20 no.2
• /
• pp.27-41
• /
• 2003

Query logs are online records that capture user interactions with information retrieval systems and all the search processes. Query log analysis offers ad advantage of providing reasonable and unobtrusive means of collecting search information from a large number of users. In this paper, query logs of NAVER, a major Korean Internet search service, were analyzed to investigate the information seeking behabior of NAVER users. The query logs were collected over one week from various collecions such as comprehensive search, directory search and web ducument searc. It is expected that this study could contribute to the development and implementation of more effective web search systems and services.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.269-274
• /
• 2005

There are lots of medicine information on the internet recently. But there is no specific research result about search patterns or acquisition methods of medicine information on web pages for lay people until now. In this paper, 1 analyzed the web log files of a certain company providing medicine information using the WiseLog tool. I analyzed three kinds of statistic result of the web log files such as the status of web page usage by types of users, the status of web page menu usage, and the status of search menu usage. As results, I proposed methods of supplement and improvement for companies providing medicine information on the internet.

• Journal of the Korean Society for Library and Information Science
• /
• v.45 no.2
• /
• pp.209-228
• /
• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

• The KIPS Transactions:PartD
• /
• v.13D no.2 s.105
• /
• pp.147-156
• /
• 2006

Event logging plays increasingly an important role in system and network management, and syslog is a de-facto standard for logging system events. However, due to the semi-structured features of Common Log Format data most studies on log analysis focus on the frequent patterns. The extensible Markup Language can provide a nice representation scheme for structure and search of formatted data found in syslog messages. However, previous XML-formatted schemes and applications for system logging are not suitable for semantic approach such as ranking based search or similarity measurement for log data. In this paper, based on ranked keyword search techniques over XML document, we propose an XML tree structure through a new data modeling approach for syslog data. Finally, we show suitability of proposed structure for semantic retrieval.