Development of the Dictionary of Poetic Japanese Description
Hilofumi Yamamoto

Bor Hodošček

Tokyo Institute of Technology

Osaka UniversityIntroduction• This paper proposes to further the development of a dictionary of classical Japanese poetry using pairwise term information(Yamamoto et al., 2014).
• Information on pairwise terms between an index and related term such as “flower–spring” is not included within traditionalmodern and classical Japanese dictionaries, even though this information connects terms with their contexts in a transparent
way and thus oﬀers an unbiased method for inferring the meaning of old Japanese terms.
• An R package for the analysis of linked communities in networks, linkcomm (Kalinka and Tomancak, 2011), is used to extract
subordinate terms. Average, McQuitty, and single linkage methods are evaluated for the quality of their extraction of subordinate
clauses of terms representing the ‘cherry’, ‘plum’, and ‘orange’ flowers. All methods extracted similar subordinate terms, whichwere quite natural in the context of classical Japanese poetry.

Problem
1. Many scholars of Japanese poetry have tried to explain poetic vocabulary based on their intuition and experience.
2. As scholars can only describe constructions that they can consciously point out, those that they are unconsciousof will NEVER be uncovered. ⇒ In order to conduct more exact and unbiased descriptions:1) using computer-assisted descriptions;2) using co-occurrence weighting methods on corpora of Japanese poetry; and
3) using linkcomm R package, extract the lists of words grouping sub communites.
⇒ allows one to BETTER GRASP the construction of poetic words.

Methodsa.

Calculation: Linkcomm (Kalinka and Tomancak, 2011) for sub communities of three flowers:
ume (plum), sakura (cherry), and tachibana (mandarin orange).
Material: Hachidaishū (ca. 905–1205) from Kokkataikan (Shin-pen KokkataikanHenshū Committee, 1996), Nijūichidaishū database published by NIJIL (Nakamura et al., 1999),
Shin-Nihon Koten Bungaku Taikei (Kojima and Arai, 1989), and Shin-kokinshū (Kubota, 1979).

Result聞ゆ
鳴く馴らすLink Communities Dendrogram

名残変ふ
何れ

千代b.

1

夕声
郭公

0.8

借る
未だ置く

今朝

夕風

末

0.2

小島 崎 彼

然

其れ

庭

誰
汝噪く

五月雨

吹く

匂ふ

枕

尋ぬ

待つ辺

昔

忍草掛く

軒香

妻有処
染む

如何で空

夜半短かし

止む
恋し

後露

闇

涼し

五月

夏

標

Partition Density

人す
枯る
何故
宿る
兼ぬ曳く

足

Fig. 1: Network of Words; mandarin orange.

average
(.43)

掘る

伝つ

初む
うたた寝

嗅ぐ

零る

nodes

0.43

Table 1: Sub-clusters of orange.

手枕

袖

今年

出づ

# edges =267 ,# nodes =112# clusters =44 ,Largest cluster =15
Hclust method:
average

0.215

覚ゆ

夢折0

風

夜

思ひ寝

香る

軒端

山郭公

0

雨

雲里

懐かし

Fig. 2: Link Community Dendrogram.

過ぐ

一木

今澄む

古里c.

0.4

宿山吹 咲く著し 追風
浮雲
いさよふ 村雨
宵有り

0.6

忍ぶHeight

旅近し植う

No. node
1 mukashi (old days)
2 nihofu (smell)
3 kaze (wind)
4 yume (dream)
5 kotoshi (this year)
6 atari (aroud)
7 matsu (to wait)
8 kaoru (fragrance)
9 samidare (summer rain)
10 somu (to dye)mcquitty
single(.43)(.38)
edge nodeedge node
edge
7
65
54
44
3
3
3

mukashinihofukotoshiatarimatsu
kaze
yume
somu
kaoriyami

7
64
4
4
44
3
3
3

mukashinihofuyume
kaoru
kotoshisomu
samidareori
makuraomohine

544
3333333Conclusion• Pairwise term information generated by the community centrality procedure works well.
• R package “linked communities” could extract proper sub cluster terms which contribute to the description ofclassical Japanese poetry.

Reference• Kalinka, A. T. and Tomancak, P. 2011. linkcomm: an R package for the generation, visualization, and analysis of link communities innetworks of arbitrary size and type. Bioinformatics. 2011–2. 27 (14).
• Yamamoto, H., Hajime Murai, Bor Hodošček. 2014. Development of an Asymptotic Word Correspondence System between ClassicalJapanese Poems and their Modern Translations. Symposium for Computer and Humanities, 2014. The information processing societyof Japan. Vol. 2014, No. 3, 157–62.