DEIM Forum 2014 F8-4

Extraction of Naming Concepts Based on Modifiers in Recipe Titles
Akiho TACHIBANA† , Shoko WAKAMIYA† , Hidetsugu NANBA†† , and Kazutoshi SUMIYA†† School of Human Science and Environment, University of Hyogo
1–1–12 Shinzaike-Honcho, Himeji, Hyogo, 670–0092 Japan†† Graduate School of Information Sciences, Hiroshima City University
3–4–1 Ozuka-higashi, Asaminami-ku, Hiroshima, 731–3194 Japan
E-mail: †nc10x087@stshse.u-hyogo.ac.jp, ††{wakamiya,sumiya}@shse.u-hyogo.ac.jp,†††nanba@hiroshima-cu.ac.jp
Abstract On user-generated recipe-sharing sites such as Rakuten recipe, various modiﬁers such as “Kid-friendly”
and “Simple” are often used in the titles of the recipes to signify thier characteristics. Although a modiﬁer isused in a number of recipes’ titles, the underlying concepts utilized vary. In this paper, we propose a method thatextracts Naming Concepts for recipes based on modiﬁers in their titles. Speciﬁcally, we obtain typical ingredientsand cooking utensils by summarizing the recipes for a dish to extract the diﬀerences between the elements of recipes
and the typical elements in terms of addition, deletion and exchangeability and extract additional information fromprocedures. Then, we identify Naming Concepts for the recipes by extracting feature patterns based on the diﬀerences extracted and grouping them on the basis of the patterns. We also present a system that provides recipes
with granted Naming Concepts for readers.
Key words Modiﬁers, Cooking Recipe, Naming Concepts.

1. Introduction

sidering the features of each recipe. In addition, the same
modiﬁer might be used in diﬀerent ways. Figure 1 shows

Cooking is one of the most important creative activities

Naming Concepts for recipes whose titles include the mod-in daily life. Nowadays, we can obtain large numbers ofiﬁer “Kid-friendly.” In the ﬁgure, there are three types ofrecipes from cooking websites. For example, Rakuten recipe

Naming Concepts: “Kid-friendly” is used in the title of a[1] provides over 740,000 user-generated recipes written inrecipe in the ﬁrst type of Naming Concept because soy milk,

Japanese. COOKPAD [2], another famous cooking website,which is considered to be preferred by many children, is usedprovides more than 1,600,000 recipes. Although these web-as an ingredient in carbonara instead of garlic and milk. In

sites have recipes that meet a wide variety of users’ demands,

the second type of Naming Concept, the same modiﬁer isthey are diﬃcult to ﬁnd because numerous recipes for any

used from a procedure in each recipe because a mixer is ad-

particular dish are available on the sites. For example, when

ditionally used to mince the ingredients and enable children

we searched for recipes on the Rakuten recipe website using

to eat without diﬃculty.

the query “carbonara,” we were presented with more thanIn this paper, we propose a method that extracts Naming

1,300 diﬀerent recipes. Thus, in order to ﬁnd recipes that

Concepts for recipes by identifying the characteristic ingre-

meets users’ demands, invariably, clear distinctions must be

dients, cooking utensils, and procedure in each recipe using

made among recipes. In this paper, we propose a method

the following four steps: 1) extracting the typical ingredients

called to extract “Naming Concept,” which can identify theand cooking utensils for the dish, 2) extracting the diﬀerencesfeatures of each recipe.

between the typical elements of the dish and the elements ofEach recipe on the Rakuten recipe website comprises a ti-

a recipe for the same dish, 3) extracting tips as additionaltle, dish categories, an ingredient list, and a procedure that

information, 4) grouping recipes with the same modiﬁer bygives step-by-step instructions on how to cook the dish. Here,feature patterns of the diﬀerences.

recipe titles are typically represented in the form “modi-

The remainder of this paper is organized as follows: Sec-ﬁer + dish name.” For example, in the two titles, “Simple!

tion 2 discusses related work. Section 3 presents our proce-

carbonara” and “kid-friendly omelette rice,” “Simple!” anddure for extracting Naming Concepts from recipes in detail.

“kid-friendly” are modiﬁers and “carbonara” and “omelette

Section 4 shows the Naming Concepts for some recipes andrice” are dish names. The modiﬁers are assigned after con-discusses experimental results obtained. Finally, we conclude

words in a recipe domain using a data structure. Interestingly, their investigations revealed that people usually write
the main ingredient in the ﬁrst position of the ingredients
list of each recipe and that such an ingredient is strongly
related to the categories to which the recipes belong. Nanba
et al. [9] constructed a recipe ontology based on Chung’s
method [8] and distributional similarity [10] [11], which theyused for multi-recipe summarization. We utilize this ontology to extract Naming Concepts.

3. Extraction of Naming Concepts
based on Modifiers in Recipe Titles
3. 1 Our Proposed Approach
In this work, we deﬁne Naming Concepts as features of
Figure 1 A modiﬁer of recipes based on Naming Concepts

recipes that present concepts of modiﬁers. We assume thata Naming Concept can be extracted by considering the dif-

this paper and outline future work in Section 5.

2. Related Work

ferences in the various recipes for a dish and the patterns ofdiﬀerences in the recipes of a modiﬁer. On the right side of
Figure 2, the arrows indicate the diﬀerences between typi-

Ueda et al. [3] proposed a method that recommends per-cal elements of a dish and the elements of each recipe. For

sonalized recipes by measuring each user’s food preference

example, in the analysis focused on the recipe with the ti-

based on ingredients extracted from the user’s recipe brows-

tle “Kid-friendly carbonara!!,” we can extract atypical in-ing and cooking history.

gredients and cooking utensils by analyzing the recipes for

Tsukuda et al. [4] proposed a method that enables users to“carbonara.” Focusing on the modiﬁers of the recipes, we ex-browse from the current recipe to a desired recipe by adding

tract the elements that can possibly signify the features of the

one element into it or deleting one element from it. How-

recipes such as deletion of ingredients or exchange of cooking

ever, they considered only element addition and deletion,utensils. On the left side of Figure. 2, we extract the patternwhereas, we consider both those factors along with elementof diﬀerences between a set of recipes based on a modiﬁer.

exchangeability. Tsukuda et al. [5] also analyzed the typical-

Consequently, our proposed method extracts Naming Con-

ity of an object from two viewpoints: target of analysis andcepts by extracting elements that are typically used in thetype of typicality. By contrast, we extract typical elements

dish from recipes for the same dish, extracting the elements

and identify diﬀerences by comparing the elements of a par-that are diﬀerent from the typical elements in each recipe,

ticular recipe with the typical elements used for the dish.

extracting additional information from the procedures, andYamakata et al. [6] proposed a method that creates a typicalgrouping the recipes using feature patterns.

cooking procedure from multiple recipes by converting each

We extract Naming Concepts as follows:

recipe text into recipe trees and by integrating them. Then,（ 1 ） Extracting elements that are typical in the recipes

they extract features of each recipe by comparing with the（ 2 ） Extracting the diﬀerences of recipes

typical one. Although this work is similar to ours in terms of（ 3 ） Extracting additional information

its attempt to deﬁne typicality and to extract recipe features（ 4 ） Grouping recipes based on feature patternson the basis of typicality, our work diﬀers in that our aim is

The steps used to extract Naming Concepts are described in

to extract recipe features based on modiﬁers.

Sections 3. 2 – 3. 5, respectively.

Approaches focusing on modiﬁers include the method proposed by Takahashi et al. [7] to measure relevancy between

3. 2 Extracting Elements that are Typical in the
Recipesa web text and modiﬁers in its title by extracting suit-

In this work, R is constructed from a set of recipes sep-able words and conﬂicting words. The method determines

arated by dish categories. A recipe rjk belongs to a dishwhether modiﬁers are relevant to the contents or not by mea-

category j consisting of Mjk , Ijk , and Ujk . Mjk is a set ofsuring information credibility. By contrast, our assumption

modiﬁers included in the title of the recipe rjk . Ijk is a set

is that recipes’ Naming Concepts based on modiﬁers in theirof ingredients of the recipe rjk , and Ujk is a set of cooking

titles can be interpreted from multiple perspectives.

utensils in the procedure of the recipe rjk . Then, M , I, andChung [8] proposed an eﬃcient method that ﬁnds related

U are universal sets of modiﬁers, ingredients, and cooking

Udel = tj .U ′ − tk .U
We determine the relation between the diﬀerences of theextracted ingredients and the cooking utensils, because insome cases one diﬀerent element inﬂuences another diﬀerent
element, or diﬀerent elements are independent of each other,making it irrelevant. Next, the element included in a set of
additional elements Iadd and Uadd is represented by +, andthen in a set of deleted elements Idel and Udel is represented
by −. For example, when we compare the ingredients of arecipe with a title such as “healthy sweet and sour pork”
that has typical ingredients “healthy sweet and sour pork,”
Figure 2 Extracting typical elements and Naming Concepts
based on relations between modiﬁer and dishwe extract diﬀerences Iadd = {chicken, bambooshoot}, Idel ={pork, liquor}. Then, we use “chicken” instead of “pork,”
so we consider that these correspond. Conversely, “bamboo

utensils, respectively.

shoot” and “liquor” are only added and deleted; therefore,

R = {R1 , ...Rj , ...Rm },they have no relation. Thus, in a scenario where an element

Rj = {rj1 , ...rjk , ...rjn }, rjk = (Mjk , Ijk , Ujk )+ is included in Iadd or Uadd and an element − is included in

Mjk ⊂ M, Ijk ⊂ I, Ujk ⊂ U

Idel or Udel correspond mutually, we consider that they have

M = {m1 , m2 , ...}, I = {i1 , i2 , ...}, U = {u1 , u2 , ...}

an exchangeable relation. Otherwise, we consider that there
is no relation between their diﬀerences.

In this work, we assume that the Naming Concepts of mod-In order to determine relations, we calculate the degree ofiﬁers are detected in the diﬀerences between a recipe and its

co-occurrence between diﬀerent elements. In general, whentypical elements. Therefore, we extract typical elements of

two elements + and − are exchangeable, we consider thata recipe for a dish. One recipe’s data is input, and we ex-they do not co-occur. Therefore, a recipe that contains ele-

tract ingredients tj .I and cooking utensils tj .U . Here, tj isment + does not contain element −, and a recipe that con-a set of recipe Rj of a category that one recipe belongs to.

tains element − does not contain element +. Thus, when the

In this work, we consider ingredients and cooking utensils

frequency of co-occurrence is low, we consider that elementsthat are frequently used as typical ingredients and cooking+ and − are exchangeable. Then, we pair elements + andutensils for a dish. Therefore, we extract ingredients and− and extract the pair as diﬀerences in order to determine

cooking utensils from a set of recipes Rj and calculate recipe

their relations. Consequently, we calculate the degree of co-frequency (RF ) of each element. Thus, a set of typical el-

occurrence of the various pairs of elements. Next, we treat

′

′

′

ements tj consists of a set of ingredients I , which means

element − (which is included as a typical element) and ele-that RF is α and over and a set of cooking utensils U which

ment − (which is included in one recipe) as denominators.

means that RF is β and over, as follows:In cases where only the degree of co-occurrence based on a′tj = (I ′ , U ′ ), tj ∈ T
tj .I ′ = {il |RF (il , Rj ) > α, il ∈ Ij }′tj .U = {uo |RF (uo , Rj ) > β, uo ∈ Uj }3. 3 Extracting the Diﬀerences of Recipes
Next, we extract the diﬀerences between elements of arecipe rjk and the typical elements tj in the category Rj
to which that recipe belongs. First, we extract a set of additional ingredients Iadd , a set of deleted ingredients Idel , a
set of additional cooking utensils Uadd , and a set of deleted
cooking utensils Udel as diﬀerences.

typical element and one recipe are lower than the threshold
amount, we determine that the diﬀerent elements in the pair
have an exchangeable relation. Therefore, a pair comprising diﬀerent elements is added to a set of pairs comprisingexchangeable ingredients Iex or a set of pairs comprising exchangeable cooking utensils Uex , and the elements that fallunder Iadd and Idel , or Uadd and Udel are deleted. Then, theexchangeability relation of the diﬀerent elements are determined and signiﬁed as “–** → +**” using the arrow. For
example, we represent the recipe called “easy carbonara”
that contains “+microwave” and “–pan” in cooking utensils
as “–pan → +microwave.” On the other hand, when the de-

Iadd = rk .I − tj .I ′gree of co-occurrence of diﬀerent elements is higher than the

Idel = tj .I ′ − tk .I

threshold amount, we consider that the diﬀerent elements in

Uadd = rk .U − tj .U ′the pair are independent, and therefore have no relations.

Table 1 Typical elements in recipe categories

Thus, we determine that elements + are additional elements

hamburger steak

carbonara

onion

egg

curry powder

ground meat

pepperonion

bread crumb

salt

water

salt

bacon

rice

pepperspaghetti

carrotegg

cheesecooking oil

analyzing the cooking procedures for the recipes. In order tonutmeg

water

salt

extract them, we use word segmentation on the cooking pro-Worcester saucecooking oil

buttercedures. Next, the cooking procedures are associated withketchup

fresh creammilk

garlicand elements − are deleted elements.
3. 4 Extracting Additional Information
We consider that recipes’ features of modiﬁers can be extracted from cooking procedures. For example, recipes for“Kid-friendly” may have features such as “small cut” and“easy-to-eat size.” Therefore, we extract these features byIword classes. We then extract additional information by de-curry

cooking oil

pendency parsing.

U

3. 5 Grouping Recipes based on Feature Patterns

frying pan

frying pan

pan

bowl

We deﬁne the feature patterns of recipes Prjk based on
Table 2 Example of recipes

viewpoints grouped by the relations between diﬀerent elements in Section 3. 2. More speciﬁcally, we deﬁne themKid-friendly, excellent

Kid-friendly

based on a set of six viewpoints: additional ingredients Iadd ,and simple cheese incarbonara of

can eathamburger steaktuna and cornwith children

deleted ingredients Idel , exchangeable ingredients Iex , additional cooking utensils Uadd , deleted cooking utensils Udel ,Beans curryground meat

spaghetti

onion

onion

cheesegarlicand exchangeable cooking utensils Uex . Then, to simplify,

butteregg

tomatowe represent patterns using binary vectors: when the ele-bread crumbmilk

soy beanment count is one or more, we present “1”; when the element

soy milk

non-dairy creamer ground meategg

peppercurry powder

saltcooking oil

soy milk

peppergarlic

water

wine

tuna

cooking oil

sauce

corn

We group recipes that use the same modiﬁer by the featureketchupwater

patterns of viewpoints that have up to 64 (= 26 ) patterns as

cheeseI

count is zero, we present “0.”Prk = [bi(|Iadd |), bi(|Idel |), bi(|Iex |),bi(|Uadd |), bi(|Udel |), bi(|Uex |)]tomatoNaming Concepts of modiﬁers.
U

4. Experiment

bowl

bowl

mixer

frying pan

frying pan

frying pan

4. 1 Dataset
We conducted an experiment using a recipe dataset pro-

amples of the recipes used to extract Naming Concepts are

vided by Rakuten Data Release from Rakuten Institute ofshown in Table 2, and examples of the elements that diﬀer

Technology. From the dataset, we selected 500 recipes whosefrom typical elements are shown in Table 3. In order to de-titles included the modiﬁer “kid-friendly.”

We then ex-termine the relations between diﬀerent elements, we made all

tracted ingredients and cooking utensils as recipe elements bypossible pairs of elements of + and − from the set of diﬀerent

considering inconsistent spelling using a recipe ontology [9]elements.

that we constructed by integrating methods for extracting

Next, we calculated the ratio of co-occurrence of each pairrelated words of a given word based on the data struc-+ and − in all the recipes for a dish. In the experiment, weture of user-generated recipes [8] and summarizing multi-

set the value of the threshold at 0.10. Then, when the degree

documents. In order to extract the typical ingredients andof co-occurrence was lower than the threshold, we determinedcooking utensils for a dish, we calculated RF (Recipe Fre-the relation of the pair to be exchangeable. Conversely, whenquency) of all the recipes used in ten recipes for the dish.

the degree of co-occurrence was higher than the threshold,In the experiment, we set the values of thresholds α and β

we determined that no relation existed between the pair.

at 0.15. Table 1 presents the typical elements extracted forTable 4 presents the results of the determination of the ex-three dishes: hamburger steak, carbonara, and curry.

changeability relation using the typical elements in Table 1

4. 2 Result: Naming Concept Extraction

and target recipes in Table 2 and calculating the degree ofWe extracted diﬀerent elements by comparing the elementsco-occurrence. We calculated the number of recipes contain-

in a recipe with the typical elements for that recipe. Ex-

ing elements + and − as the denominator, and determinedTable 3 Elements that diﬀer from typical elements

Table 5 Results of extracted diﬀerence elements and features inthe three recipes

Kid-friendly,

Kid-friendly

Beans curry

excellent and simple

carbonara of

can eatcheese intuna and cornwith children

hamburger steak

Iadd

diﬀerent elements+cheeseKid-friendly, excellent+lettuce

Iadd

and simple cheese+tomatoIdel

in hamburger steak–cooking oil

Iex

+milk

+soy milk+Non-dairy creamer +tomato

+wine

+tuna

+soy bean–nutmeg+cheese+corn+ground meat→ +butter+soy milk–milk+tomatoIdel→ +soy milk

–nutmeg

–salt

–rice

–milk

–bacon–carrot–cooking oil–fresh cream–salt–butter

Uadd
Udel

viewpoints+wine+butter+lettuce+garlic

recipe titles

+bowl

+milk
–salt

Iadd

Kid-friendly carbonara –fresh cream

Idel→ +Non-dairy creamIex+mixer–baconUdel+frying pan→ +tuna

–pan

–bowl

of tuna and corn+garlic+tomatothe exchangeability relation when the degree of co-occurrence
was lower than the threshold. We present the results for the
extracted diﬀering elements and features in the three recipes.
Then, we present the diﬀerent elements and viewpoints in+ground meat

Iadd+soy milk

Idel

Beans curry can

–rice

Iex

eat with children

–salt

Uadd

–butter

Uex

Table 5–carrot

We grouped 500 recipes into feature patterns of diﬀerences
extracted from the experimental recipes, and extracted Nam-

→ +soy bean

ing Concepts for the modiﬁer “kid-friendly.” The recipes+mixer–panwere grouped into 38 patterns from the 64 patterns in Sec-

→ +frying pantion 3. 5. In Table 6, we present the feature patterns grouped
as more than three percent. As a result, seven patterns included the feature Iex and ﬁve patterns included the feature
Uadd or Udel .

Table 6 Naming Concepts for “Kid-friendly”
appearance
Iadd Idel Iex Uadd Udel Uex
ratio
pattern1

1

1

1

0

1

0

30 %

Table 7 presents recipe titles grouped into the top-threepattern2

1

1

1

1

0

0

14 %

patterns. The recipes grouped by feature patterns do notpattern3

1

1

1

1

1

0

12 %

become unbalanced because of the dishes. Therefore, recipes

pattern4

1

1

0

0

1

0

5%

for the same dish are grouped by various patterns.

pattern5

0

1

1

0

0

0

4%

pattern6

0

0

1

0

0

0

3%

pattern7

1

1

1

0

0

0

3%

pattern8

1

1

0

1

1

0

3%

4. 3 Discussion
In our extractions, typical cooking utensils that are normally included in typical elements were not included. For
example, when cooking carbonara, a pan is typically used toboil spaghetti. However, in the experiment, it was not included in the typical elements because there were few recipesthat had “pan” expressly written. When we extracted difference elements, cooking utensils were included in the difference elements that were normally included in typical elements because cooking utensils were used in pictures, but
not included in the procedures. In the future, we need to improve the extraction of typical elements and determine theexchangeability relations. Therefore, we consider that we
can make up for cooking utensils by inferring the cooking
utensils used from the actions in the procedures. For exam-

ple, we can infer that “boil” means “pan” and “fry” means“frying pan,” and so on.
When we determined the exchangeability relation andcompared our results with the correct data, we found that a
number of pairs had appropriately determined the relation.
However, with regard to cooking utensils, there are many
recipes in which only actions are written (e.g. “boil” and“fry”). Therefore, cooking utensils that would not normallydetermine the relation of exchangeability here, do so becauseof the lowness of their degree of co-occurrence, resulting fromthem not being cooking utensils are not expressly written inTable 4 Results of calculation of conﬁdence for judging the relation
recipe titles

pairs to determine relations

degree of co-occurrence exchangeable+

Kid-friendly, excellent–+butter, –nutmeg

0.12

0.16

and simple cheese+butter, –cooking oil

0.06

0.05

○

in hamburger steak+soy milk, –milk

0.00

0.00

○

+wine, –milk

0.00

0.18

+milk, –fresh cream

0.24

0.17

Kid-friendly carbonara +Non-dairy cream, –fresh cream 0.00

0.00

○
○

of tuna and corn+tuna, –bacon

0.00

0.00

+corn, –bacon

0.00

0.25

+garlic, –salt

0.13

0.23

+garlic, –butter

0.10

0.06

Beans curry can+tomato, –carrot

0.04

0.13

eat with children+soy bean, –carrot

0.00

0.09

+ground meat, –carrot

0.00

0.15

+mixer, –pan

0.70

0.00

+frying pan, –pan

0.00

0.00

Table 7 Recipe titles grouped into the top-three patterns
Kid-friendly ☆ carbonara
Kid-friendly Anpanman hamburger steak○○

However, we extracted Naming Concepts, which were notassumed as concepts of “kid-friendly.” The reason is that we
failed to make pairs. We made pairs of seasonings and ma-

Kid-friendly ★ creamy curry

terials (e.g. “–salt → +chocolate”). We assume that it has

Kid-friendry milk pudding

not exchangeable relation between seasonings and materials.

Pattern1 Kid-friendly pumpkin gratin
Kid-friendly ☆ beancurd Sichuan style ☆

Therefore we need to make pairs of seasoning and materials
separately.

Kid-friendly omelette rice

Thus, there are also many recipes that include cooking

Kid-friendly pretty croquettutensils as Naming Concepts. However, there are some ex-

Kid-friendly chow mein
Kid-friendly ☆ carbonara with tuna and corn ♪
Kid-friendly! Japanese hamburger steak with tohu

tracted cooking utensil elements for which it is diﬃcult toconsider that the elements are Naming Concepts. For ex-

Kid-friendly ★ curry with celery

ample, in the recipe for curry in Table 5, we extracted and

The dish for children ♪ Very easy! Rice croquetts

used “frying pan” instead of “pan.” However, it is diﬃcult toPattern2 For children ♪ Steamed breadconsider these elements as Naming Concepts. Therefore, we

Kid-friendly ♪ Star breadneed to consider whether extracted elements really present

Fried chicken children like!

the concepts of modiﬁers or noise.

Kid-friendly! Fried chicken
Healty and kid-friendly okonomiyaki
Kid-friendly hamburger steak with chub mackerel

In the results of grouped recipes based on feature patterns
and extracted Naming Concepts, we found that recipes in-

For children’s snack ☆ Banana pudding

cluded in the same category have various Naming Concepts

Kid-friendly gratin with breadsuch as those listed in Table 7. In this paper, we extracted

Mild beancurd Sichuan style for eating with children

Naming Concepts for “kid-friendly.” However, we need toPattern3 Kid-friendly omelette rice
Kid-friendly! Corn croquetts
Kid-friendly ♪ Small bread ♪
Curry and cheese croquetts for children
For children ★ How to make okonomiyaki

extract more Naming Concepts for various modiﬁers. By
comparing the diﬀerence between modiﬁers, we could analyze the relations between modiﬁers. For example, when thetrends for Naming Concepts are similar between modiﬁers,
they have similar relations.
Figure. 3 depicts a system that presents the Naming Con-

recipes.
In Table 5, we consider that the Naming Concepts for “kidfriendly” are addition, deletion, and exchange of ingredients.
For example, in the recipe for carbonara in Table 5, we could
extract the exchangeability relation in which “tuna” is usedinstead of “bacon” as the feature.

cepts of recipes based on our method. In this system, whena user searches for recipes containing modiﬁers such as “Kidfriendly” and “Simple”, it is diﬃcult to understand the features of the recipes because a list of search results often show
only titles and pictures for the recipes. Therefore, if users

the procedures of recipes. For instance, although we generally use a “frying pan” when “frying” something, it is often
omitted because users/readers can easily associate the action“fry” with the cooking utensil “frying pan” in the recipes.
Therefore, we plan to infer cooking utensils from proceduresby considering actions in procedures.

Acknowledgment
This research was supported in part by the Grant-in-Aid
for JSPS Fellows 24.9154 from the Ministry of Education,
Culture, Sports, Science, and Technology of Japan. The experimental Rakuten recipe dataset was provided by Rakuten
Data Release from the Rakuten, Inc.

Figure 3 System for retrieving and presenting recipes with Naming Concepts
Table 8 Well-used modiﬁers in Rakuten recipe
rank

modiﬁers

number of recipes

1

Simple7795

2

Handmade1332

3

For a lunch box

1184

4

Kid-friendly

995

5

Healthy660

want to know the features of the recipes, they look into thedetails of each recipe. However, it is a really daunting task
and determining its features is a time-consuming process.
Therefore, our system enables users to comprehend the features of the recipes solely by checking the list of search results.
Table 8 shows main modiﬁers used in user-generated
recipe-sharing sites. In this paper, we focused on the modiﬁer “Kid-friendly”, but we need to examine how to extract
Naming Concepts of other modiﬁers.

5. Conclusion
In this work, we proposed a method that extracts Naming
Concepts for recipes, which are deﬁned as characteristic elements summarized by modiﬁers in the recipes’ titles. We extracted diﬀerent elements of ingredients and cooking utensils,
determined the relations between them by calculating theirdegree of co-occurrence and extracted Naming Concepts bygrouping the recipes based on feature patterns. Further, we
experimented with a real recipe dataset to extract the Naming Concepts of given recipes.
In future work, we plan to enable the inferring of cooking
utensils that are not written expressly in procedures because
we found that typical cooking utensils tend to be omitted in

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