A Hotel Recommendation System Based on Collaborative Filtering and Rankboost Algorithm
A hotel recommendation system based on collaborative filtering method of clustering and Rankboost algorithm proposed in this paper, which can avoid the cold-start and scalability problems existing in traditional collaborative filtering. One can find a hotel quickly and efficiently when he uses this...
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| creator | Gao Huming Li Weili |
| description | A hotel recommendation system based on collaborative filtering method of clustering and Rankboost algorithm proposed in this paper, which can avoid the cold-start and scalability problems existing in traditional collaborative filtering. One can find a hotel quickly and efficiently when he uses this hotel recommendation system. |
| doi_str_mv | 10.1109/MMIT.2010.14 |
| format | Conference Proceeding |
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One can find a hotel quickly and efficiently when he uses this hotel recommendation system.</abstract><pub>IEEE</pub><doi>10.1109/MMIT.2010.14</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2010 Second International Conference on Multimedia and Information Technology, 2010, Vol.1, p.317-320 |
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| language | eng |
| recordid | cdi_ieee_primary_5474286 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Clustering algorithms Filtering algorithms Finance Information filtering Information filters Information management Information technology International collaboration Multimedia systems Scalability |
| title | A Hotel Recommendation System Based on Collaborative Filtering and Rankboost Algorithm |
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