• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.135-141
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• 2013

String matching is one of the key algorithms in network security and many areas could be benefit from a faster string matching algorithm. Based on the most efficient string matching algorithm in sual applications, the Boyer-Moore (BM) algorithm, a novel algorithm called RQS is proposed. RQS utilizes an improved bad character heuristic to achieve bigger shift value area and an enhanced good suffix heuristic to dramatically improve the worst case performance. The two heuristics combined with a novel determinant condition to switch between them enable RQS achieve a higher performance than BM both under normal and worst case situation. The experimental results reveal that RQS appears efficient than BM many times in worst case, and the longer the pattern, the bigger the performance improvement. The performance of RQS is 7.57~36.34% higher than BM in English text searching, 16.26~26.18% higher than BM in uniformly random text searching, and 9.77% higher than BM in the real world Snort pattern set searching.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1986-1992
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• 2009

A user often searches a data by inputting a variant such as the abbreviation or substring of a word, or a misspelled word. The simple approach to the searching for variants is to build a variants dictionary. However, it entails enormous cost and time and can not handle variants by misspelling. Approximate searching, searching by approximate string matching, is a good approach to the searching. A problem in the approach is that it cannot handle variants by abbreviations. This paper propose a method for searching various variants including abbreviations and misspelled words, by using the trie indexing. First, this paper shows a variant matching method with the calculation of path weighted-metric. In addition, it provides variant searching algorithm to reduce the search time.

• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.788-801
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• 2010

Advancing of mobile device is remarkable, so the research on mobile input device is getting more important issue. There are lots of input devices such as keypad, QWERTY keypad, touch and speech recognizer, but they are not as convenient as typical keyboard-based desktop input devices so input strings usually contain many typing errors. These input errors are not trouble with communication among person, but it has very critical problem with searching in database, such as dictionary and address book, we can not obtain correct results. Especially, Hangeul has more than 10,000 different characters because one Hangeul character is made by combination of consonants and vowels, frequency of error is higher than English. Generally, suffix tree is the most widely used data structure to deal with errors of query, but it is not enough for variety errors. In this paper, we propose fast approximate Korean word searching system, which allows variety typing errors. This system includes several algorithms for applying general approximate string searching to Hangeul. And we present profanity filters by using proposed system. This system filters over than 90% of coined profanities.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.60-69
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• 2003

In an Information Retrieval System(IRS) based on an inverted file as a file structure it is possible to retrieve related documents when the searcher know the complete words of searching fields. however, there are many cases in which the searcher may not know the complete words but a partial string of words with which to search. In this case, if the searcher can search indexes that include the known partial string, it is possible to retrieve related documents. Futhermore, when the retrieved documents are few, we need a method to find all documents having indexes which include known the partial string. To satisfy these requests, the searcher should be able to construct a query formulation that uses the term truncation method. Also the IRS should have an electronic dictionary that can support a truncated search term. This paper designs and implements an electronic dictionary(ED) structure to support a truncation search efficiently. The ED guarantees very fast and constant searching time for searching a term entry and the inversely alphabetized entry of it, regardless of the number of inserted words. In order to support a truncation search efficiently, we use the Trie structure and in order to accommodate fast searching time we use a method using array. In the searching process of a truncated term, we can reduce the searching time by minimizing the length of string to be expanded.

• 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.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.8
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• pp.456-462
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• 2002

We are developing searching algorithms for weighted strings such as protein sequences. Let${\sum}$ be an alphabet and for each $a{\in}{\sum}$ its weight ${\mu}(a)$ is given. Given a string $A=a_1a_2…a_n\; with each ai{\in}{\sum}$, a substring<$A(i.j)=a_ia_{i+1}…a_j$ has weight ${\in}(A(i.j))={\in}(a_i)+{\in}(a_i+1)+…+{\in}(a_j)$.The problem we are dealing with is to preprocess A to build a searching structure, and later, given a query weight M, the structure is used to answer the question of whether there is a substring A(i,j) such that$M={\in}(A(i,j))$.In this paper an algorithm that improves over the previous result will be presented. The previously best known algorithm answers a query in $0(\frac{nlog\;logn}{log\; n})$time using a searching structure that requires O(n) amount of memory. Our algorithm reduces the memory requirement to $0(\frac{n}{log\; n})$ while achieving the same query answer time.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.135-139
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• 2009

The problems to compute the distances or similarities of multiple strings have been vigorously studied in such diverse fields as pattern matching, web searching, bioinformatics, computer security, etc. One well-known method to compare multiple strings in the given set is finding a consensus string which is a representative of the given set. There are two objective functions that are frequently used to find a consensus string, one is the radius and the other is the consensus error. The radius of a string x with respect to a set S of strings is the smallest number r such that the distance between the string x and each string in S is at most r. A consensus string based on radius is a string that minimizes the radius with respect to a given set. The consensus error of a string with respect to a given set S is the sum of the distances between x and all the strings in S. A consensus string of S based on consensus error is a string that minimizes the consensus error with respect to S. In this paper, we show that the problem of finding a consensus string based on radius is NP-complete when the distance function is a metric.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.270-275
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• 2007

Motion capture technology is widely used for manufacturing animation since it produces high quality character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. In this paper, we propose a framework to integrate, store and retrieve heterogeneous motion capture data files effectively. We define a standard format for integrating different motion capture file formats. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (eXtensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents. We propose a fuzzy string searching method to retrieve certain MCML documents including strings approximately matched with keywords. The method can be used to retrieve desired series of frames included in MCML documents not entire MCML documents.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.129-132
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• 2003

The metathesaurus(UMLS, 2003AA edition) supports multi language and includes 875, 233 concepts, 2, 146, 897 concept names. It is impossible for PubMed or NLM serve searching of the metatheaurus to retrieval using a query that is not to be text, a fault sentence structure or a part of concept name. That means the user notice correctly suitable medical words in order to get correct answer, otherwise she or he can't find information that they want to find I propose that the method of searching unified medical language system using automatic modified a query for problem that I mentioned. This method use dictionary that is standard for automation of modified query gauge similarity between query and dictionary using string comparison algorithm. And then, the tested term converse the form of metathesaurus for optimized result. For the evaluation of method, I select some query and I contrast NLM method that renewed Aug. 2003.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.6
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• pp.354-367
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• 2010

There are many methods for analyzing patterns in time series data. Although stock data represents a time series, there are few studies on stock pattern analysis and prediction. Since people believe that stock price changes randomly we cannot predict stock prices using a scientific method. In this paper, we measured the degree of the randomness of stock prices using Kolmogorov complexity, and we showed that there is a strong correlation between the degree and the accuracy of stock price prediction using our semi-global alignment method. We transformed the stock price data to quantized string sequences. Then we measured randomness of stock prices using Kolmogorov complexity of the string sequences. We use KOSPI 690 stock data during 28 years for our experiments and to evaluate our methodology. When a high Kolmogorov complexity, the stock price cannot be predicted, when a low complexity, the stock price can be predicted, but the prediction ratio of stock price changes of interest to investors, is 12% prediction ratio for short-term predictions and a 54% prediction ratio for long-term predictions.