Name
Abstract | ||
|---|---|---|
Abstract : In this paper we described our efforts for TREC contextual suggestion task. Our goal of this year is to evaluate the effectiveness of: (1) predict user preferences of each scenic spot based on non-negtive matrix factorization, (2) automatic summarization method that leverages the information from multiple resources to generate the description for each candidate scenic spots; and (3) hybrid recommendation method that combing a variety of factors to construct a system of hybrid recommendation system. Finally, we conduct extensive experiments to evaluate the proposed framework on TREC 2015 Contextual Suggestion dataset, and, as would be expected, the results demonstrate its generality and superior performance. |
Year | Venue | Field |
|---|---|---|
2015 | TREC | Recommender system,Information system,Automatic summarization,Data mining,Information retrieval,Computer science,Matrix decomposition,Expert system,Knowledge-based systems,Data management,Generality |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weitong Chen | 1 | 0 | 2.03 |
| Hanchen Li | 2 | 1 | 0.69 |
| Zhen Yang | 3 | 13 | 6.68 |