• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.100-104
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• 2010

In the past decade, various search engines have been developed to retrieve web pages that web surfers want to find from world wide web. In search engines, one of the most important functions is to evaluate and rank web pages for a given web surfer query. The prior algorithms using hyperlink information like PageRank incur the problem of 'topic drift'. To solve the problem, relevance propagation models have been proposed. However, these models suffer from serious performance degradation, and thus cannot be employed in real search engines. In this paper, we propose a new ranking algorithm that alleviates the topic drift problem and also provides efficient performance. Through a variety of experiments, we verify the superiority of the proposed algorithm over prior ones.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.268-274
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• 2005

Since introduction of the PageRank technique, it is known that it ranks web pages effectively In spite of its usefulness, we found a computational drawback, which we call norm-leak, that PageRank values become smaller than they should be in some cases. We present an improved PageRank algorithm that computes the PageRank values of the web pages correctly as well as its efficient implementation. Experimental results, in which over 67 million real web pages are used, are also presented.

• Journal of KIISE:Databases
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• v.36 no.1
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• pp.22-29
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• 2009

The World Wide Web has emerged as largest media which provides even a single user to market their products and publish desired information; on the other hand the user can access what kind of information abundantly enough as well. As a result web holds large amount of related information distributed over multiple web pages. The current search engines search for all the entered keywords in a single webpage and rank the resulting set of web pages as an answer to the user query. But this approach fails to retrieve the pair of web pages which contains more relevant information for users search. We introduce a new search paradigm which gives different weights to the query keywords according to their order of appearance. We propose a new arc weight measure that assigns more relevance to the pair of web pages with alternate keywords present so that the pair of web pages which contains related but distributed information can be presented to the user. Our measure proved to be effective on the similarity search in which the experimentation represented the e~arc ranking measure outperforming the conventional ones.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.473-476
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• 2009

본 논문에서는 다중 쓰레드 환경에서 동작하는 웹 크롤러를 구현하고 성능을 분석한다. 이 웹 크롤러의 특징은 검색시간을 단축하기 위하여 크롤링, 파싱 및 페이지랭킹, DB 저장 모듈을 서로 독립적으로 다른 작업을 수행하도록 구현한 것이다. 크롤링 모듈은 웹상의 데이터를 수집하는 기능을 제공한다. 그리고 파싱 및 페이지랭크 모듈은 수집한 데이터를 파싱하고, 웹 페이지의 상대적인 중요도를 수치로 계산하여 페이지랭크를 지정한다. DB 연동 모듈은 페이지랭크 모듈에서 구한 페이지랭크를 데이터베이스에 저장한다. 성능평가에서는 다중 쓰레드 환경에서 쓰레드 수와 웹 페이지의 수에 따른 검색 시간을 측정하여 그 결과를 비교 평가한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.76-78
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• 2010

최근 몇 년간 정보 검색 분야에서 문맥 광고에 관한 연구가 활발히 연구되고 있다. 하지만 기존의 관련된 연구들은 대부분 웹페이지 내용만을 활용하여 유사한 광고를 찾고자 하였다. 그럼으로써 동일한 웹페이지를 접속하는 다양한 의도를 가진 사용자들이 동일한 광고를 보게 된다는 한계가 존재하였다. 본 논문에서는 웹페이지의 내용뿐만 아니라 각각의 사용자들의 웹페이지 방문 의도를 웹 페이지 방문 히스토리로부터 추출하여 이를 활용한 기법을 제안하고자 한다. 또한 실험을 통하여 본 논문에서 제안된 기법이 사용자 방문 의도를 반영함으로써 기존 기법에 비해 성능이 향상되었음을 보여준다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.35-40
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• 2007

역파일을 사용한 색인 기법은 정보 검색 분야에서 널리 사용되었으며, 최근 대용량 검색 시스템으로 사용되고 있는 웹 검색 엔진에서도 적응되고 있다. 본 논문에서는 웹 검색 엔진의 특성에 완친 구현된 역파일 기법 기반의 웹 문서 색인 파일의 구조와 디스크에 저장된 대용량의 역파일 색인을 기반으로 웹 페이지의 검색 적합도를 계산하는 랭킹 시스템을 설명한다. 이를 통하여 상용 웹 검색 엔진의 랭킹 시스템과 디스크 자원 사용의 최소화 기법을 제시한다.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.567-581
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• 2008

As the size of the web is growing explosively, search engines are becoming increasingly important as the primary means to retrieve information from the Internet. A search engine periodically downloads web pages and stores them in the database to provide readers with up-to-date search results. The web crawler is a program that downloads and stores web pages for this purpose. A large-scale search engines uses a parallel web crawler to retrieve the collection of web pages maximizing the download rate. However, the service architecture or experimental analysis of parallel web crawlers has not been fully discussed in the literature. In this paper, we propose an architecture of the parallel web crawler and discuss implementation issues in detail. The proposed parallel web crawler is based on the coordinator/agent model using multiple machines to download web pages in parallel. The coordinator/agent model consists of multiple agent machines to collect web pages and a single coordinator machine to manage them. The parallel web crawler consists of three components: a crawling module for collecting web pages, a converting module for transforming the web pages into a database-friendly format, a ranking module for rating web pages based on their relative importance. We explain each component of the parallel web crawler and implementation methods in detail. Finally, we conduct extensive experiments to analyze the effectiveness of the parallel web crawler. The experimental results clarify the merit of our architecture in that the proposed parallel web crawler is scalable to the number of web pages to crawl and the number of machines used.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.547-550
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• 2009

블로그는 누구나 쉽게 이용할 수 있는 도구이며, 블로그를 통한 콘텐츠의 생산과 소비는 빠른 속도로 증가하고 있다. 이런 블로그의 글은 단순히 정보를 전달하는 웹 페이지 이상의 사회적 관계를 포함하고 있다. 하지만 지금까지 웹 페이지 및 블로그에 대한 검색은 이러한 사회적 관계를 고려하지 않고 있다. 따라서 본 논문에서는 사용자 행동과 사회적 관계에 기반한 블로그 랭크 모델을 제안한다. 이를 기반으로 국내의 서로 다른 서비스에서 제공한 블로그 랭킹을 새롭게 제안한 블로그 모델과 비교하였고, 이를 통해 제안하는 블로그 모델의 타당성을 제시하였다.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.580-589
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• 2009

Today, most web pages are being created in the blogspace or evolving into the blogspace. A blog entry (blog page) includes non-traditional features of Web pages, such as trackback links, bloggers' authority, tags, and comments. Thus, the traditional rank algorithms are not proper to evaluate blog entries because those algorithms do not consider the blog specific features. In this paper, a new algorithm called "Blog-Rank" is proposed. This algorithm ranks blog entries by calculating bloggers' reputation scores, trackback scores, and comment scores based on the features of the blog entries. This algorithm is also applied to searching for information related to the users' queries in the blogspace. The experiment shows that it finds the much more relevant information than the traditional ranking algorithms.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.