• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.7
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• pp.433-439
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• 2014

This paper proposes an architecture of two-stage string matching engine with content-addressable memory(CAM) and parallel bit-split string matchers for deep packet inspection(DPI). Each long signature is divided into subpatterns with the same length, where subpatterns are mapped onto the CAM in the first stage. The long pattern is matched in the second stage using the sequence of the matching indexes from the CAM. By adopting CAM and bit-split string matchers, the memory requirements can be greatly reduced in the heterogeneous string matching environments.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.33-40
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• 2008

In various manners, string pattern matching algorithm has been proven for prominence in speed of searching particular queries and keywords. Whereas, the existing algorithms are limited in terms of various pattern. In this paper, regular expression has been utilized to improve efficiency of pattern matching through efficient execution towards various pattern of queries including particular keywords. Such as this research would enable to search various harmful string pattern more efficiently, rather than matching simple keywords, which also implies excellent speed of string pattern matching compared to that of those existing algorism. In this research, the proposed string search engine generated from the LEX are more efficient than BM & AC algorithm for a string patterns search speed in cases of 1000 with more than patterns, but we have got similar results for the keywords pattern matching.

• ETRI Journal
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• v.35 no.1
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• pp.154-157
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• 2013

This letter proposes a memory-based parallel string matching engine using the compressed state transitions. In the finite-state machines of each string matcher, the pointers for representing the existence of state transitions are compressed. In addition, the bit fields for storing state transitions can be shared. Therefore, the total memory requirement can be minimized by reducing the memory size for storing state transitions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.100-106
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• 2017

In this paper, we propose a parallel optimization method of Aho-Corasick (AC) algorithm and Parallel Failureless Aho-Corasick (PFAC) algorithm using Open Computing Language (OpenCL) on Field Programmable Gate Array (FPGA). The low throughput of string matching engine causes the performance degradation of network process. Recently, many researchers have studied the string matching engine using parallel computing. FPGA's vendors offer a parallel computing platform using OpenCL. In this paper, we apply the AC and PFAC algorithm on DE1-SoC board with Cyclone V FPGA, where the optimization that considers FPGA architecture is performed. Experiments are performed considering global id, local id, local memory, and loop unrolling optimizations using PFAC algorithm. The performance improvement using loop unrolling is 129 times greater than AC algorithm that not adopt loop unrolling. The performance improvements using loop unrolling are 1.1, 0.2, and 1.5 times greater than those using global id, local id, and local memory optimizations mentioned above.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.41-48
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• 2008

This study focuses on the modeling file search engine and suggesting modified file search schema based on weight value using file contents in order to improve the performance in terms of search accuracy and matching time. Most of the file search engines have used string matching algorithms like KMP(Knuth.Morris.Pratt), which may limit portability and fast searching time. However, this kind of algorithms don't find exactly the files what you want. Hence, the file search engine based on weight value using file contents is proposed here in order to optimize the performance for mobile environments. The Comparison with previous research shows that the proposed schema provides better.

• International Journal of Contents
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• v.8 no.3
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• pp.83-93
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• 2012

In this paper, we propose a novel method that automatically generates real character images to familiarize existing OCR systems with new fonts. At first, we generate synthetic character images using a simple degradation model. The synthetic data is used to train an OCR engine, and the trained OCR is used to recognize and label real character images that are segmented from ideal document images. Since the OCR engine is unable to recognize accurately all real character images, a substring matching method is employed to fix wrongly labeled characters by comparing two strings; one is the string grouped by recognized characters in an ideal document image, and the other is the ordered string of characters which we are considering to train and recognize. Based on our method, we build a system that automatically generates 2350 most common Korean and 117 alphanumeric characters from new fonts. The ideal document images used in the system are postal envelope images with characters printed in ascending order of their codes. The proposed system achieved a labeling accuracy of 99%. Therefore, we believe that our system is effective in facilitating the generation of numerous character samples to enhance the recognition rate of existing OCR systems for fonts that have never been trained.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.229-236
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• 2005

The Semantic Web enables machines to achieve an effective retrieval, integration, and reuse of web resources. The keyword search method currently used has a limit to accurate search results because of a simple string matching method in web environment. This paper proposes an Ontology-Based Information Retrieval which can solve the problems and retrieve better search results through semantic relations. In this system, we implemented the Cultural Assets Ontology based on OWL with RDQL and Jena API. we also suggest a method to handle properties stored in a database.