• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.55-62
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• 2009

This study is concerned with predicting human search performance using a visual lobe. The most previous studies on human performance in visual search have been limited to a single-target search. This study extended the visual search research to multiple-target search including targets of different types as well as targets of same types. A model for predicting visual search performance was proposed and the model was validated by human search data. Additionally, this study found that human subjects always did not use a constant ratio of the whole visual lobe size for each type of targets in visual search process. The more conspicuous the target is, the more ratio of the whole visual lobe size human subjects use. The model that can predict human performance in multiple-target search may facilitate visual inspection plan in manufacturing.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.255-265
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• 2017

Objective: This study aims to survey visual search performance models to assess and predict individual's visual tasks in everyday life and industrial sites. Background: Visual search is one of the most frequently performed and critical activities in everyday life and works. Visual search performance models are needed when designing or assessing the visual tasks. Method: This study was mainly based on survey of literatures related to ergonomics relevant journals and web surfing. In the survey, the keywords of visual search, visual search performance, visual search model, etc. were used. Results: On the basis of the purposes, developing methods and results of the models, this study categorized visual search performance models into six groups: probability-based models, SATO models, visual lobe-based models, computer vision models, neutral network-based models and detection time models. Major models by the categories were presented with their advantages and disadvantages. More models adopted the accuracy among two factors of accuracy and speed characterizing visual tasks as dependent variables. Conclusion: This study reviewed and summarized various visual search performance models. Application: The results would be used as a reference or tool when assessing the visual tasks.

• Asia pacific journal of information systems
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• v.1 no.1
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• pp.87-101
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• 1991

The primary purpose of this study was to investigate a robust search methodology that could be used in full-text information retrieval systems. A robust search methodology is one that can be easily used by a variety of users (particularly naive users) and it will give them comparable search performance regardless of their different expertise or interests In order to develop a possibly robust search methodology, a fully functional prototype of a fuzzy knowledge based information retrieval system was developed. Also, an experiment that used this prototype information retreival system was designed to investigate the performance of that search methodology over a small exploratory sample of user queries To probe the relatonships between the possibly robust search performance and the query organization using fuzzy inference logic, the search performance of a shallow query structure was analyzes. Consequently the following several noteworthy findings were obtained: 1) the hierachical(tree type) query structure might be a better query organization than the linear type query structure 2) comparing with the complex tree query structure, the simple tree query structure that has at most three levels of query might provide better search performance 3) the fuzzy search methodology that employs a proper levels of cut-off value might provide more efficient search performance than the boolean search methodology. Even though findings could not be statistically verified because the experiments were done using a single replication, it is worth noting however, that the research findings provided valuable information for developing a possibly robust search methodology in full-text information retrieval.

• Korean small business review
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• v.41 no.2
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• pp.1-24
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• 2019

This paper seeks to explore the effects of search strategies on innovation performance in the context of small and medium enterprises. The empirical results of 3,398 Korean SMEs demonstrate that there is a substitutive relationship between search depth and search width, and this substitutive relationship is weakened when a firm possesses collaboration experience. Furthermore, although these two types of search enhance innovation performance, the impact of search depth is greater than that of search width. The positive effect of search width on innovation performance is weakened when the firm adopts formal information protection mechanisms.

• Knowledge Management Research
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• v.21 no.4
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• pp.109-127
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• 2020

This study empirically investigates the effects of information search on new product development (NPD) process and performance with a sample of 82 NPD projects in 5 firms. The information search is consisted of general sources, internal sources, and external sources. The performance is consisted of technological and market performance. Findings show that information search from internal sources increases the technological knowledge of the NPD team, and information search from external sources increases the market knowledge of the NPD team. The technological and market knowledge of the NPD team increases its technical performance respectively. Only the market knowledge of the NPD team increases its market performance. Overall, the technological knowledge of the NPD team fully mediates the relationship between the information search from internal sources and its technical performance. The market knowledge of the NPD team fully mediates the relationship between the information search from external sources and its technical performance, and the relationship between the information search from external sources and its market performance. There is no other significant mediation relationships between the information searches and the performances. Implications of the research findings are discussed, and recommendation for future research are provided.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.57-68
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• 2011

This paper examines how multiple performance feedbacks influence firm's technological search, using two types of indicators : accounting-based performance and market-based performance. Also we investigate how CEO's attention shift depends on firm specific factors such as firm size and outsider ownership. For empirical analysis, we utilized financial data on 675 manufacturing firms in Korea during the period between 1998 and 2009. The results show that technological search based on accounting-based performance feedback is moderated by focal firm's size. However, as outsider ownership increases, technological search increases in response to market-based performance feedback.

• Journal of the Korean Society for Library and Information Science
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• v.19
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• pp.189-241
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• 1990

This study identified cognitive styles of online searchers in terms of Field Dependence (FD) and Field Independence (FI) dimension and determined whether searching performance was affected by FD / FI cognitive differences between online searchers and the extent to which searching performance was affected by the FD / FI dimension of cognitive style. This study used a quasi experimental design with 41 student subjects using the Lockheed DIALOG system and ERIC ONT AP database. Cognitive styles of student subjects were measured by using GEFT (Group Embedded Figure Test) and the subjects were divided into two cognitive groups- FD and FI based on the GEFT scores. Each subject was assigned two predetermined searches which had different search goals-a 'high precision search' and a 'high recall search.' Search performance of the two cognitive groups on the two problems was compared in order to see how these two groups responded to achieving different search goals in terms of search strategy, search inputs, and resulting search outputs. The major findings of this study were: 1. The pattern of approaching a search problem regardless of whether it was a high precision search or a high recall search was not significantly different between the two cognitive groups. 2. The FI group tended to use significantly more terms for the high recall search than the FD group but slightly less time than the FD group. However, significant differences in connect time between the two groups were not revealed. 3. For both search problems the FI group achieved a significantly higher success rate than the FD group. The FI group were significantly more successful searchers than the FD group. As for unit / cost, although the FI group were more cost effective than those of the FD group for both searches, these differences were too small to be statistically significant. 4. Mean differences of the search performance variables between the FD / FI groups were consistent across the two types of search questions. The FI group seemed to be equally effective for both types of search questions. In conclusion, the differences found in number of terms used and success rate between the two cognitive groups apparently resulted from different cognitive styles.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.165-171
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• 2003

Visual search in an unstructured search field is a fruitful research area for computational modeling. Search models that describe relationship between search time and probability of target detection have been used for prediction of human search performance and provision of ideal goals for search training. Until recently, however, most of models were focused on detecting a single target in a search field, although, in practice, a search field includes multiple targets and search models for multiple targets may differ from search models for a single target. This study proposed a random search model for multiple targets, generalizing a random search model for a single target which is the most typical search model. To test this model, human search data were collected and compared with the model. This model well predicted human performance in visual search for multiple targets. This paper also proposed how to determine optimal stopping time in multiple-target search.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1103-1111
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• 2008

Internet routers forward an incoming packet to an output port toward its final destination through IP address lookup. Since each incoming packet should be forwarded in wire-speed, it is essential to provide the high-speed search performance. In this paper, IP address lookup algorithms using binary search are studied. Most of the binary search algorithms do not provide a balanced search, and hence the required number of memory access is excessive so that the search performance is poor. On the other hand, binary-search-on-range algorithm provides high-speed search performance, but it requires a large amount of memory. This paper shows an optimized binary-search-on-range structure which reduces the memory requirement by deleting unnecessary entries and an entry field. By this optimization, it is shown that the binary-search-on-range can be performed in a routing table with a similar or lesser number of entries than the number of prefixes. Using real backbone routing data, the optimized structure is compared with the original binary-search-on-range algorithm in terms of search performance. The performance comparison with various binary search algorithms is also provided.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.31-38
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• 2018

As the use of open source databases grows, so does need to evaluate, the performance of search queries for these databases. This paper compares the search query performance of SQL-based open source databases with commercial databases through experiments. The targets are MySql, MariaDB, and MS-SQL Server. In this study, the execution time of various types of search queries are measured. Also, search query performance was experimented according to change of index and number of tuples. Experimental results show that SQL-based open source databases have the potential to replace commercial databases when indexes are used and the number of tuples is not very large.