Demo Data from SIGIR 2026 / reviewers in the wild / expert
Akihisa Ishino
dblp:299/9536
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 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.
| Human-computer interaction and pervasive computing
2 papers |
Health and well-being technologies · 68% Interaction techniques and input · 32% | |
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% |
Topics — the 4 heaviest of 5, 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 |
Health and well-being technologies › personal informatics › self-tracking
food tracking |
0.5 | 1 | 2021 | RecipeLog: Recipe Authoring App for Accurate Food Recording · ACM Multimedia 2021 |
Interaction techniques and input
mobile interaction |
0.5 | 1 | 2021 | RecipeLog: Recipe Authoring App for Accurate Food Recording · ACM Multimedia 2021 |
Methods — techniques the papers use, named apart from their topics
graph-based recipe representation · 1.1user study · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 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 | 2 |
| 2021 | RecipeLog: Recipe Authoring App for Accurate Food RecordingabstractDiet management is usually conducted by recording the name of foods eaten, but in fact, the nutritional value of food in the same name varies greatly from recipe to recipe. To know accurate nutritional values of the foods, recording personal recipes is effective but time-consuming. Therefore, we are developing a mobile application "RecipeLog", that assists users to write their own recipes by modifying prepared ones. In our experiments, we show that with RecipeLog users create personal recipes with 45% less edit distance compared to writing from scratch. Akihisa Ishino, Yoko Yamakata, Hiroaki Karasawa, Kiyoharu Aizawa |
ACM Multimedia | 1 |