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

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.12
• /
• pp.3762-3774
• /
• 2000

The advances of computer hardware and information processing technologies raise the needs of multimedia information retrieval systems. Up to date. multimedia information systems have been developed for text information and image information. Nowadays. the multimedia information systems for video and audio information. especially for musical information have been grown up more and more. In recent music information retrieval systems. not only the information retrieval based on meta-information such like composer and title but also the content-based information retrieval is supported. The content-based information retrieval in music information retrieval systems utilize the similarity value between the user query and the music information stored in music database. In tbis paper. hence. we developed a similarity computation algorithm in which the pitches and lengths of each corresponding pair of notes are used as the fundamental factors for similarity computation between musical information. We also make an experiment of the proposed algorithm to validate its appropriateness. From the experimental results. the proposed similarity computation algorithm is shown to be able to correctly check whether two music files are analogous to each other or not based on melodies.

• KIISE Transactions on Computing Practices
• /
• v.20 no.12
• /
• pp.711-716
• /
• 2014

With the gradual increase of interest in plagiarism and intelligent file content search, the demand for similarity measuring between two sentences is increasing. There is a lot of researches for sentence similarity measurement methods in various directions such as n-gram, edit-distance and LSA. However, these methods have their own advantages and disadvantages. In this paper, we propose a new sentence similarity measurement method approaching from another direction. The proposed method uses the set-based POI data search that improves search performance compared to the existing hard matching method when data includes the inverse, omission, insertion and revision of characters. Using this method, we are able to measure the similarity between two sentences more accurately and more quickly. We modified the data loading and text search algorithm of the set-based POI data search. We also added a word operation algorithm and a similarity measure between two sentences expressed as a percentage. From the experimental results, we observe that our sentence similarity measurement method shows better performance than n-gram and the set-based POI data search.

• Journal of Korea Multimedia Society
• /
• v.11 no.11
• /
• pp.1566-1574
• /
• 2008

Researches of current information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aims at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among data. The current searching occasionally presents too much redundant information or offers no matching results from large volumes of data. To lessen this disadvantages in the information searching, we propose an inference algorithm that supports associated and inferred searching through the Jess engine based on the OWL ontology constraints and knowledge expressed by SWRL with association rules. After constructing the personalized preference ontology for domains such as restaurants, gas stations, bakeries, and so on, it shows that new knowledge information generated from the ontology and the rules is provided with an example of the domain of gas stations.

• KIISE Transactions on Computing Practices
• /
• v.20 no.9
• /
• pp.498-506
• /
• 2014

With the development of smart transportation, people are likely to find their paths by using navigation and map application. However, the existing retrieval system cannot output the correct retrieval result due to the inaccurate query. In order to remedy this problem, set-based POI search algorithm was proposed. Subsequently, additionally a method for measuring POI name similarity and POI search algorithm supporting classifying duplicate characters were proposed. These algorithms tried to compensate the insufficient part of the compensate set-based POI search algorithm. In this paper, accuracy improvement methods for measuring string similarity in POI data retrieval system are proposed. By formulization, similarity measurement scheme is systematized and generalized with the development of transportation. As a result, it improves the accuracy of the retrieval result. From the experimental results, we can observe that our accuracy improvement methods show better performance than the previous algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.26 no.8A
• /
• pp.1388-1397
• /
• 2001

무선 ATM에서 핸드오프 시의 경로 재설정 과정에서 필요한 COS 선택 알고리즘에 관하여 기존의 알고리즘과는 다른 새로운 알고리즘을 제안한다. 제안하는 Short search COS 선택 알고리즘은 매 핸드오프 시마다 COS를 검색하지 않고 이전에 검색된 COS 노드를 최대한 활용하여 핸드오프 지연 성능을 저하시키지 않으면서 전체적인 망 이용 효율성은 향상시키는 결과를 나타낸다. 알고리즘의 개선된 성능을 시뮬레이션을 통해 검증되고 그래프 및 결과 테이블을 통해 보여진다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.131-134
• /
• 1997

기존의 유전자 알고리즘과는 달리 대화형 유전자 알고리즘은 평가치를 인간이 제시할 수있기 때문에 인간의 직관이나 감성을 효과적으로 표현할 수 있다는 장점이 있다. 대화형 유전자 알고리즘을 기반으로 내용 기반 영상 검색 시스템을 구축한 바 있는데, 이 시스템은 웨이블렛 변환을 통하여 기술된 영상을 내용에 기반하여 검색할 수 있도록 한다. 본 논문에서는 이러한 웨이블렛 변환으로 얻어진 계수가 유전자 알고리즘의 염색체 표현으로 효과적인지를 실험적으로 평가하고자 한다. 소규모의 영상 데이터베이스에 대하여 실험한 결과 체이블렛 변환으로 기술된 염색테들이 유전자 알고리즘의 교차 연산에 대하여 의미있는 후보를 찾아낸다는 사실을 확인할 수 있다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06a
• /
• pp.488-490
• /
• 2011

본 논문에서는 문서 영상에서 글자 분할 및 인식이 필요 없는 단어 검색 알고리즘을 제안한다. 글자 분할을 하지 않고 검색하기 위해 영상 검색에 사용되는 SIFT특징을 이용하였다. 제안하는 알고리즘은 사용자가 입력한 질의어를 질의 영상으로 변환하고, 질의 영상에서 SIFT특징을 추출한다. 추출된 특징은 문서영상에서 추출한 특징과 매칭을 통해 매칭점 쌍을 생성한다. 생성된 매칭점 쌍들을 군집화 조건에 따라 군집화 한다. 군집화는 질의 영상과 지리적 분포가 유사하게 군집화 되도록 설계되었다. 생성된 군집은 군집에 포함된 특징점의 개수가 많을수록 질의 영상과 유사하다. 따라서 N개 이상의 원소를 가지는 군집을 결과로 출력한다. 실험한 결과 제안하는 알고리즘의 가능성을 확인할 수 있었다.

• Journal of the Korean Society for information Management
• /
• v.17 no.4
• /
• pp.47-65
• /
• 2000

This study aims lo enhance the perfor~nance 01 concept-based information retr~eval through the use of the lraditional thesaurus which, clearly delmes relalions among terms. To achwe lhls, thc study purports to construcl relation-value-based, relalion-bad, and inlegated kumwledge bases tluough the use ol ihc lhcsau~ub. To cornpale and a~alyze retrieval perlor~nance among knowledge bases, two methods weue al~plied. Sequential bnb algorithm is ap~lied to the I-clation-ualue-based and intzgralcd knowledge base while heuristic bnb algorithm is applied to the relal~on-based knowlcdgc base.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.75-78
• /
• 2010

웹 검색에는 기존의 정보검색(Information Retrieval) 시스템에서와 다르게 문서 간 하이퍼링크 정보를 바탕으로 각 웹 문서의 고유 중요도를 추정하는 방식이 자주 이용된다. 링크 분석에 기반한 알고리즘 중 PageRank 알고리즘은 구글의 웹 검색 서비스에 적용된 것으로 알려져 있다. 이런 PageRank 알고리즘에 따라 중요도를 계산하는 경우 색인된 웹 문서수가 증가함에 따라 계산에 필요한 CPU 자원의 사용도 함께 증가하며, 문서 수가 수 억 페이지에 달하면 하나의 서버에서는 계산을 수행할 수 없다는 문제가 있다. 본 논문에서는 이런 문제점을 해소하기 위해 여러 대의 서버를 PageRank 계산 용 클러스터로 사용할 수 있는 방법을 제시한다. 제시된 방법은 고속의 LAN을 이용하여 여러 대의 서버를 연결하고 반복적인 행렬 계산을 병렬로 수행할 수 있어 계산 시간을 단축시킬 수 있다. 이런 서버 클러스터 구현을 위해 멀티 쓰레딩 프로그램이 작성되었으며, PageRank 계산에 사용되는 행렬 데이터를 적은 양의 메모리만으로 표현 가능하도록 하였다.