Name
Abstract | ||
|---|---|---|
In recent years, there have been plenty of cooking recipes on the internet. Because it has caused difficulty in searching for a cooking recipe that suites one's needs, many studies have researched on how to make these recipes easily accessible. Existing studies have focused on the components of cooking recipes, such as ingredients, nutrients, and condiments. However, if the recipe contains difficult cooking activities for the user, the user may not be able to cook the dish according to the recipe. Consequently, it is necessary to match the searched recipe's cooking skills. Therefore, in this work, we define four-levels of difficulty of cooking activities, and we propose a method for calculating a cooking recipe's difficulty level when searching for one that matches a user's cooking skills. Then, our approach was evaluated using a questionnaire survey on a crowdsourcing site. The results of our experiment showed that our approach can reduce the burden on users when searching for appropriate cooking recipes. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3106668.3106673 | CEA@IJCAI |
Field | DocType | ISBN |
World Wide Web,Crowdsourcing,Computer science,Recipe,Artificial intelligence,Questionnaire,Machine learning,The Internet | Conference | 978-1-4503-5267-3 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuma Kusu | 1 | 1 | 2.06 |
| Nozomi Makino | 2 | 0 | 0.34 |
| Takamitsu Shioi | 3 | 2 | 2.45 |
| Kenji Hatano | 4 | 30 | 10.41 |