Demo Data from SIGIR 2026 / reviewers in the wild / expert
Akiko Sunto
dblp:331/1475
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0001-5956-0262ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval
food computing |
0.6 | 1 | 2022 | Recipe-oriented Food Logging for Nutritional Management · ACM Multimedia 2022 |
Multimedia analysis and retrieval › food computing
recipe analysis |
0.6 | 1 | 2022 | Recipe-oriented Food Logging for Nutritional Management · ACM Multimedia 2022 |
Methods — techniques the papers use, named apart from their topics
graph-based recipe representation · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | JFC-Recipe: A Dataset for Nutrient Estimation from Japanese User-Generated Cooking Recipes
Keisuke Shirai, Yoko Yamakata, Hirotaka Kameko, Akiko Sunto, Jun Harashima, Shinsuke Mori |
LREC | 4 |
| 2022 | Recipe-oriented Food Logging for Nutritional ManagementabstractWe propose a recipe-oriented food logging method that records food by recipe, unlike the ordinary food logging method that records food by name. We also develop an application RecipeLog for this purpose. RecipeLog can create a "skeleton recipe," which is a standardized recipe representation suitable for estimating the nutritional value of a dish. This is represented by a list of ingredients linked to a Nutrition Facts table and a flow graph consisting of cooking actions such as cutting, mixing, baking, simmering, and frying the ingredients. The recipe log allows recipes to be written with fewer operations by editing only the differences from the already registered base recipe. Experiments have confirmed that the recipe log can effectively identify differences in recipes from household to household. The future work is to construct a multimedia recipe dataset consisting of structured recipes and their images using RecipeLog. Yoko Yamakata, Akihisa Ishino, Akiko Sunto, Sosuke Amano, Kiyoharu Aizawa |
ACM Multimedia | 3 |