Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김상욱 | - |
dc.date.accessioned | 2020-08-18T08:01:26Z | - |
dc.date.available | 2020-08-18T08:01:26Z | - |
dc.date.issued | 2019-07 | - |
dc.identifier.citation | KNOWLEDGE-BASED SYSTEMS, v. 176, Page. 147-158 | en_US |
dc.identifier.issn | 0950-7051 | - |
dc.identifier.issn | 1872-7409 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0950705119301595?via%3Dihub | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/152325 | - |
dc.description.abstract | Web page ranking is one of the core components of search engines. Given a user query, ranking aims to provide a ranked list of Web pages that the user is likely to prefer the most. By and large, the ranking algorithms can be categorized into content-based approaches, link-based approaches, and hybrid approaches. Hybrid ranking algorithms, which exploit both the content and link information, are the most popular and extensively studied techniques. Among the hybrid algorithms, C-Rank combines content and link information in a very effective way using the concept of contribution. This algorithm is known to provide high performance in terms of both accurate and prompt responses to user queries. However, C-Rank suffers from very high costs to reflect the highly dynamic and extremely frequent changes in the World Wide Web, because it re-computes all of the C-Rank scores used for ranking from scratch to reflect the changes. As a result, C-Rank may be considered inappropriate to provide users with accurate and up-to-date search results. This paper aims to remedy this limitation of C-Rank. We propose incremental C-Rank, which is designed to update the C-Rank scores of only a carefully chosen portion of the Web pages rather than those of all of the Web pages without any accuracy loss. Our experimental results on a real-world dataset confirm both the effectiveness and efficiency of our proposed method. (C) 2019 Elsevier B.V. All rights reserved. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP; Ministry of Science and ICT) (No. NRF-2017R1A2B3004581). | en_US |
dc.language.iso | en | en_US |
dc.publisher | ELSEVIER SCIENCE BV | en_US |
dc.subject | Information retrieval | en_US |
dc.subject | Ranking algorithm | en_US |
dc.subject | Dynamic ranking | en_US |
dc.title | Incremental C-Rank: An effective and efficient ranking algorithm for dynamic Web environments | en_US |
dc.type | Article | en_US |
dc.relation.volume | 176 | - |
dc.identifier.doi | 10.1016/j.knosys.2019.03.034 | - |
dc.relation.page | 147-158 | - |
dc.relation.journal | KNOWLEDGE-BASED SYSTEMS | - |
dc.contributor.googleauthor | Koo, Jangwan | - |
dc.contributor.googleauthor | Chae, Dong-Kyu | - |
dc.contributor.googleauthor | Kim, Dong-Jin | - |
dc.contributor.googleauthor | Kim, Sang-Wook | - |
dc.relation.code | 2019000171 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF COMPUTER SCIENCE | - |
dc.identifier.pid | wook | - |
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