Name
Abstract | ||
|---|---|---|
We propose a recommendation method that considers region-restrictedness. In this study, we define a spot as an establishment such as a restaurant, amusement facility, or tourist attraction in the real world. A spot with high region-restrictedness indicates that the spot is located in a restricted area but not in a user's home area. We define the region-restrictedness score to extract region-restricted phrases from text data about spots (such as promotional descriptions about spots). Then, spots including these phrases are recommended to the user. In this paper, we present our proposed method and discuss it on the basis of basic experimental results. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14589-6_36 | DASFAA Workshops |
Keywords | Field | DocType |
basic study,restricted area,region-restrictedness score,high region-restrictedness,real world,promotional description,basic experimental result,amusement facility,recommendation method,home area,local search | Data mining,Spots,World Wide Web,Computer science,Tourism,Amusement,Attraction,Local search (optimization) | Conference |
Volume | ISSN | ISBN |
6193 | 0302-9743 | 3-642-14588-4 |
Citations | PageRank | References |
1 | 0.38 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenta Oku | 1 | 84 | 14.81 |
| Fumio Hattori | 2 | 164 | 26.81 |