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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Renyuan Wang Yan Chen Taoying Li Yingying Yu |
| Copyright Year | 2013 |
| Description | Author affiliation: Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China (Renyuan Wang; Yan Chen; Taoying Li; Yingying Yu) |
| Abstract | With the emergence of search engines, people's life becomes more and more convenient. However, the problem that search engines are faced is how to make the concern or important pages in the top-ranking after searching. Nowadays, the search ranking algorithms are lacking factors in the consideration of which pages are concerned by common users, such as Alexa algorithm, PageRank algorithm, HillTop algorithm and so on. This article presents a new sorting method which adds a new parameter factor to the original PageRank sorting algorithm. The new parameter factor is called grey factor. We can optimize the algorithm through applying the knowledge of grey forecasting model to PageRank algorithm, and enhance the factor in the consideration of which pages are concerned recently by users. |
| Sponsorship | Hubei Univ. Automot. Technol. |
| Starting Page | 1698 |
| Ending Page | 1700 |
| File Size | 499774 |
| Page Count | 3 |
| File Format | |
| ISBN | 9780769550046 |
| DOI | 10.1109/ICCIS.2013.443 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Heuristic algorithms Grey forecasting model PageRank sorting algorithm Predictive models Search engines Educational institutions Grey factor Forecasting Sorting |
| Content Type | Text |
| Resource Type | Article |
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