Incremental C-Rank: An effective and efficient ranking algorithm for dynamic Web environments
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Koo, Jangwan | - |
dc.contributor.author | Chae, Dong-Kyu | - |
dc.contributor.author | Kim, Dong-Jin | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.date.accessioned | 2022-07-09T13:09:31Z | - |
dc.date.available | 2022-07-09T13:09:31Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2019-07 | - |
dc.identifier.issn | 0950-7051 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147495 | - |
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. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.title | Incremental C-Rank: An effective and efficient ranking algorithm for dynamic Web environments | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chae, Dong-Kyu | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.identifier.doi | 10.1016/j.knosys.2019.03.034 | - |
dc.identifier.scopusid | 2-s2.0-85064245760 | - |
dc.identifier.wosid | 000469153200012 | - |
dc.identifier.bibliographicCitation | KNOWLEDGE-BASED SYSTEMS, v.176, pp.147 - 158 | - |
dc.relation.isPartOf | KNOWLEDGE-BASED SYSTEMS | - |
dc.citation.title | KNOWLEDGE-BASED SYSTEMS | - |
dc.citation.volume | 176 | - |
dc.citation.startPage | 147 | - |
dc.citation.endPage | 158 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | INFORMATION | - |
dc.subject.keywordPlus | SIMILARITY | - |
dc.subject.keywordPlus | RETRIEVAL | - |
dc.subject.keywordPlus | SEARCH | - |
dc.subject.keywordPlus | LINKS | - |
dc.subject.keywordAuthor | Information retrieval | - |
dc.subject.keywordAuthor | Ranking algorithm | - |
dc.subject.keywordAuthor | Dynamic ranking | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0950705119301595?via%3Dihub | - |
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