Query Expansion using an Automatically Constructed Thesaurus
Hidetsugu anba
Hiroshima City University
3-4-1 Ozukahigashi, Hiroshima 731-3194
Phone & FAX: +81-82-830-1584
nanba@hiroshima-cu.ac.jp

Abstract
Our group participated in the Japanese and English Retrieval Subtasks of TCIR-6. Our goal was toevaluate the effectiveness of a thesaurus constructedfrom patents for invalidity search. To confirm the effectiveness of our thesaurus-based query expansion,
we conducted experiments and found that our method
can improve upon traditional document retrieval systems.

Keywords: Invalidity Search, Thesaurus,
Query Expansion
1

Introduction

We are studying the automatic construction of athesaurus from patent documents. Our goal in
NTCIR-6 [Fujii et al. 2007] is to evaluate the effectiveness of the thesaurus for invalidity search.
Invalidity search aims to find patent that can invalidate the assertions in an existing claim. However,
it is often difficult to retrieve such patents using traditional document retrieval systems, because the terms
used in a claim are often abstract or creative, to expand the range of the claim. As a result, different patents tend to contain different terms, even though theseterms refer to the same things. To solve this problem,
we apply a thesaurus-based query expansion.
This paper is organized as follows. Section 2 describes some related works. Section 3 explains theconstruction of a thesaurus for query expansion. Section 4 contains a system description. To investigate
the effectiveness of our method, we conducted experiments, as reported in Section 5. We present ourconclusions in Section 6.

2

Related Works

Several methods for thesaurus construction havebeen proposed, and they are divided into two categories: (1) extraction of hypernym/hyponym relations[Hearst 1992, Morin and Jacquemin 2004, Oishi et al.
2006], and (2) collection of related terms [Lee 1999,
Lin 1998, Mase et al. 2005, Sato and Sasaki 2003]. In
the following, we summarize these methods, and describe their relationship to our work.

2.1

Hypernym/Hyponym Extraction

Hearst [Hearst 1992] proposed a method for extracting hyponyms from text corpora using a set ofpatterns. For example, “magnetic tape” and “floppy
disc” are extracted as hyponyms of “magnetic recording media” from the following sentence, using apattern “P0 such as {P1, P2, (and/or)} Pn”.
Methods for manufacturing magnetic recording
media such as magnetic tapes and floppy discs
are well known in the art …
As there are many sentences containing “such as”
or “等の” (such as) expressions in patent applications,
we use this pattern for hypernym/hyponym extraction.

2.2

Collection of Related Terms

Lin [1998] and Lee [1999] proposed methods forcalculating the similarity between terms. They focused on the contexts in which terms are used, anddefine the similarity between two terms as the amountof information contained in the commonality between
the terms, divided by the amount of information in thecontexts of the terms. Although the effectiveness of
their method was confirmed in their experiments, themethod did also collect several dissimilar term pairs.
In patent applications, inventors may explicitly describe related terms by using parentheses, as in“floppy disc (magnetic recording medium)”. The term
preceding the parentheses and the term in parentheses
have a broader/narrower relationship. Mase et al.
[2005] extracted related terms from the text in a “Description of Symbols” of Japanese patents. Though
there are fewer term pairs collected by Mase’s methodthan by Lin’s and Lee’s methods, the results are morereliable.
When using related term collection for query expansion, the more reliable data is preferable despite
being less extensive, because incorrect query expansion directly affects precision. We therefore use
Mase’s method for our task.

3

Construction of a Thesaurus forQuery Expansion

To construct English-language and Japaneselanguage thesauri, we extracted four types of relation
between terms: “Hypernym/Hyponym”, “Abbreviation”, “Synonym”, and “Related Term”.

3.1

Hypernym/Hyponym Extraction

Using the same pattern as Hearst [Hearst 1992]
proposed, we obtained 3,898,060 hypernym/hyponym
relations from United States Patent Office (USPTO)
patents over an eight-year period. Some examples ofEnglish hypernym/hyponym relations are shown in
Table 1.
In the same way, we obtained 7,031,159 hypernym/hyponym relations from Japanese patentdocuments over a ten-year period, using the pattern“P0 (,|と|や) P2 (等の|などの)Pn”. Some examples of Japanese hypernym/hyponym relations areshown in Table 2.
Table 1 Examples of English Hypernym/Hyponym
Relations
Freq.
23
20
11
8
6

Hypernym

magnetic storage medium

Hyponymmagnetic diskmagnetic tapemagnetic disccomputer disk
floppy disk

Table 2 Examples of Japanese Hypernym/Hyponym Relations
Freq.
101

Hypernym

39
26
25
22

3.2

磁気記憶装置(magnetic storage medium)

Hyponymハードディスク(hard disc)
磁気ディスク装置(magnetic disc system)
ハードディスク装置(hard disc system)
ＨＤＤ
ハードディスクドライ
ブ (hard disc drive)

Abbreviation Extraction

We extracted abbreviations for terms when parentheses were used. In some sentences, which were used
for extracting hypernym/hyponym relations in Section
3.1, terms are shown with their abbreviation in parentheses. The following is an example containing anabbreviation.
この外管３１の内部には例えばＰＴＦＥ(ポリテトラフルオロエチレン)等の合成樹脂材料によって形成された可撓性内管２１を挿通し、Table 3 Examples of Japanese Terms and theirAbbreviations
Freq.
Term 1
Term 2935 ポリエチレンテレフタレー ＰＥＴト(polyethylene terephthalate)
658 コンパクトディスク
ＣＤ(compact disc)586 アルミニウム(aluminium)
Ａｌ
545 ポリプロピレンＰＰ(polypropylene)
498 タングステン(tungsten)Ｗ
490 銅(copper)Ｃｕ
449 発光ダイオードＬＥＤ(light emitting diode)
Table 4 Examples of English Terms and their Abbreviations
Freq.
Term 1
Term 2160 polyvinyl chloride
PVC
130 biscyclopentadienyl
124 polytetrafluoroethylene
PTFE
123 chemical vapour deposi- CVDtion
122 central processing unitCPU
115 aluminiumAL
109 tungsten
W

3.3

Synonym Extraction

In Japanese patent documents, the same concept isoften expressed in different terms. For example, “フロッピーディスク” (floppy disc) may be expressedas “磁気記録装置” (magnetic recording system) or“ 磁 気 記 憶 装 置 ” (magnetic storage medium). To
search patents exhaustively, the use of a synonym
dictionary is inevitable. However, it is difficult toautomatically construct such a dictionary by traditional term co-occurrence methods, because synonyms such as “magnetic recording system” and“magnetic storage medium” rarely appear in the same
patent. To extract synonyms, we focus on citation
relations between patents. Generally, two patents thathave a citation relationship are topically related.
Therefore, we collect synonyms for a given term X in
the following three steps;(Step 1) Search all patents related to the term X,(Step 2) Collect patents that have citation relationships with patents collected in Step 1,(A flexible inner tube 21 containing synthetic resin,such as PTFE (poly tetra fluoro ethylene), is inserted through an outer tube.)(Step 3) Extract terms from patents collected in
Step 2.

In this sentence, “ＰＴＦＥ” is an abbreviation of “ポリテトラフルオロエチレン” (poly tetra fluoro ethylene). We extracted 50,161 Japanese terms and theirabbreviations (Table 3). In the same way, we extracted 17,792 English terms and their abbreviations(Table 4).

In order to extract topic terms from patents in Step3, we focus on patent claims. In most claims, nounphrases before “において” (concerning) and after “を特徴とする” (characterized by) indicate topic terms.
Figure 1 is an example of a Japanese claim, together
with its English translation. In this figure, the boldface terms “シフトレバー装置” (shift lever device),

“シフトレバー” (shift lever), and “シフトロック装置” (shift lock unit) are extracted as topic terms.
車体に固定する筐体内に前後揺動体を車体前後方向へ回動可能に軸支し、該前後揺動体に揺動基部を車体左右方向へ回動可能に軸支し、該揺動基部に植設したシフトレバーを車体前後及び左右方向へ揺動させることにより筐体上面に形成したゲート部を移動し所望のレンジを選択して自動変速機を切替操作するシフトレバー装置
シフトレバー装置
において、前記揺動基部に一対の上下に離間した突起部を設け、一方の突起部に当接可能なＰ
係止部と、他方の突起部に当接可能なＮ係止部を有する回転ロック体を前記筐体に回動可能に軸支するとともに、シフトレバーがＰレンジ又はＮレンジに移動したとき該回転ロック体を回動させるアクチュエータを前記筐体に固定したことを特徴とするシフトレバー
シフトレバーのシフトロック
シフトレバー シフトロック装置。
装置(A shift lock unit for a shift lever device for use in
an automatic transmission having parking and neutral
ranges, comprising: a casing; a base rotatably supported in said casing, said base including first andsecond protrusions separate d from each other in alongitudinal direction thereof; a lock member rotatably supported in said casing, said lock member including first and second engagements which can abuton said first and second protrusions, respectively; ashift lever arranged with said base, said shift leverserving to select a desired range of the transmission;and an actuator fixed to said casing, said actuator rotating said lock member when said shift lever is
moved to one of the parking and neutral ranges.)
Figure 1 A Claim Extracted from a Japanese Patent (Publication umber = 10-184868)
We extracted 522,810 different topic terms fromJapanese patents over a 10-year period. For each term,
we applied Steps 1 to 3, and obtained Japanese synonyms (257,459 pairs of terms). Some examples areshown in Table 5.

3.4

Related Term Extraction

As described in Section 2, we use Mase et al.’s
method [2005] for related term extraction. We applied
this method to Japanese patents, and obtained 22,952
pairs of related terms. Some examples are shown in
Table 6.

Table 5 Examples of Japanese Synonyms
Freq.
75

Term 1

Term 2磁気記録媒体(magnetic
recordingsystem)
磁気ディスク装置(magnetic disc system)
磁気ヘッド(magnetic head)
磁気記録装置(magnetic
recordingmedium)
金属薄膜型磁気記録(metallic thin film
magnetic recording)37
磁気記憶装置(magnetic storage
medium)18
13

11

Table 6 Examples of Japanese Related Terms
Freq.
4420

Term 1
ＣＰＵ

2158

制御手段
(control method)
像担持体(image carrier)
制御手段(control method)
制御手段(control method)

1800
1573
1544

4

Term 2
中央処理装置(central processing unit)
ＣＰＵ
感光ドラム
(photosensitive dram)
制御装置(control device)
制御部 (control unit)

System Description

Our system comprises the following four steps:(Step 1) Morphological analysis
We introduce the Vector Space Model as a retrieval
model and SMART [Salton 1971] for term weighting.
We use GETA1 as a retrieval engine. We use ChaSen2
and TreeTagger 3 as Japanese and English morphological analysis tools, respectively.
(Step 2) Stopword deletion
Our system uses nouns, verbs, adjectives, and unknown words to retrieve relevant patents. In thismethod, unimportant words are stripped from thoseterms that are any of the above parts of speech and are
extracted from the query.
(Step 3) Topic term extraction from a claim
Our system extracts topic terms from a claim using
a claim analyser [Shinmori et al. 2002] that we described in Section 3.3. The extracted terms are expanded in the next step.

1

GETA: http://geta.ex.nii.ac.jp/
ChaSen: http://chasen.naist.jp/hiki/ChaSen/
3
TreeTagger:
http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html
2

(Step 4) Thesaurus-based query expansion
We use the following procedure for query expansion using the thesaurus shown in Table 7.
Table 7 Thesaurus for Query Expansion
Hyponyms
Abbreviations
Synonyms
Related terms

Japanese○○○○

English○○－－(1) Expand queries (topic terms) using “Hyponyms” (Section 3.1) with a term weight Wh,(2) Expand queries using “Abbreviations” (Section 3.2) with a term weight Wa,(3) Expand queries using “Synonyms” (Section3.3) with a term weight Ws, (Japanese taskonly),(4) Expand queries using “Related terms” (Section
3.4) with a term weight Wr (Japanese taskonly).

5

Evaluation

5.1

Data and Evaluation

We used 1,685 Japanese topics and 2,221 English
topics to evaluate our patent retrieval method [Fujii etal. 2007]. All the systems were evaluated by mean
average precision (MAP).

5.2

Systems

Japanese Retrieval Subtask

tems “hcu1” and “hcu2”. The difference between
these systems is in the term weights used for the four
query expansion methods. The weights for each system are shown in Table 8, and were determined using
dry run data. Here, Wt and Ww indicate the weight for
topic terms and for other terms in claims, respectively.
For comparison with “hcu1” and “hcu2”, we prepareda baseline system that omitted the query expansion.
Table 8 Term Weights for Each System(Japanese Retrieval Subtask)
hcu1
hcu2
baseline

Ww
2
2
2

Wt

Wa
2
1
0

5
5
5

Ws
2
2
0

Wr
2
2
0

Wh
0
1
0

English Retrieval Subtask
For the formal run of the English Retrieval Subtask,
we submitted the two results provided by systems“hcu1” and “hcu2”. Table 9 gives the term weights
for “hcu1” and “hcu2”. These weights were determined using sample data that was distributed, insteadof dry run data. In the same way as for the Japanese
Retrieval Subtask, we prepared a baseline system thatomitted the query expansion.
Table 9 Term Weights for Each System(English Retrieval Subtask)
Ww
hcu1
hcu2
baseline

Wa
1
1
1

Wh
1
0
0

0
1
0

For the formal run of the Japanese Retrieval Subtask, we submitted the two results provided by sys-

def0
hcu1
hcu2
baseline
def1
hcu1
hcu2
baseline

Table 10 Evaluation Results for Japanese Patent Retrieval (%)
all
NTC4
NTC5
NTC6
a
b
a
b
a
b
a
b
9.78
6.49
20.52
15.67
9.69
8.22
4.88
9.62
6.37
19.38
15.30
9.54
8.06
4.77
6.49
3.77
10.26
9.73
6.88
5.43
2.36
all
NTC4
NTC5
NTC6
a
b
a
b
a
b
a
b
7.01
5.33
6.49
10.77
15.67
8.22
4.16
4.88
5.26
6.37
10.35
15.30
8.06
4.06
4.77
7.03
2.86
3.77
6.52
9.73
4.23
5.43
2.05
2.36
Table 11 Evaluation Results for English Patent Retrieval (%)
a
b
hcu1
3.37
6.94
hcu2
3.23
6.65
baseline
3.23
6.93

SR
a
7.39
7.47
3.45
SR
a
6.58
6.44
3.06

b
7.52
7.47
4.30
b
7.52
7.47
4.30

5.3

percent of cases in both sets a and b, but on the whole,
the system impaired the baseline system.

Results

Japanese Retrieval Subtask
The results are shown in Table 10. For comparison
with “hcu1” and “hcu2”, we also show the results forthe baseline system that omits the query expansion.
As can be seen from Table 10, “hcu1” is superior to
the baseline system.
This indicates that “Abbreviations”, “Synonyms”,
and “Related Terms” can improve the mean average
precision (MAP). “Hcu2” is superior to “hcu1” inSR.a and in NTC5.a, which means that “Hyponym”
can also contribute to MAP improvement.

Table 13 The umber of Topics that “hcu1”
and “hcu2” could Improve the MAP(English Retrieval Subtask)abEnglish Retrieval Subtask
The results are shown in Table 11. For comparison
with “hcu1” and “hcu2”, we also show the results forthe baseline system that omits the query expansion.
As can be seen from Table 11, “hcu1” is superior to
the baseline system.
From these results, “Abbreviations” is useful not
only for Japanese but also for English. Although“hcu2” does not improve upon the baseline method,
we cannot conclude that “hyponyms” is not useful,because there were fewer USPTO patents, which wereused in constructing the thesaurus, than Japanese patents. We believe that using “hyponyms” still has thepotential to improve upon the baseline systems.

5.4

Discussion

Table 12 The umber of Topics that “hcu1”
and “hcu2” could Improve the MAP(Japanese Retrieval Subtask)bhcu1 vs.
baseline
hcu2 vs.
baseline
hcu1 vs.
baseline
hcu2 vs.
baseline

Improve1009(0.667)997(0.659)1243(0.738)1227(0.728)Same
305(0.202)304(0.201)
157(0.093)161(0.096)

Impair199(0.132)212(0.140)285(0.169)297(0.176)In the same way as for Japanese Retrieval Subtask,
we also compared our systems with the baseline system. The result is shown in Table 13. From the result,
we can find that performances of “hcu1” and the baseline system are almost the same. “Hcu2” improved 20

Improve
115(0.056)407(0.197)147(0.066)465(0.209)Same
1826(0.882)898(0.434)1877(0.845)739(0.333)

Impair128(0.062)765(0.370)199(0.089)1017(0.458)Conclusions

We participated in the NTCIR-6 Patent Retrieval
Task and evaluated our system for the Japanese andEnglish Retrieval Subtasks. We constructed Englishlanguage and Japanese-language thesauri, and usedthem for query expansion. As a result, we confirmedthat “abbreviations”, “synonyms”, and “related terms”
are useful for improving the MAP in the Japanese andEnglish Retrieval Subtasks. We also confirmed theeffectiveness of “hyponyms” for the Japanese Subtask.

7

To confirm the effectiveness of our method more
precisely, we calculated the MAP for each topic andcounted the number of topics that our system wassuperior to the baseline system. The result for Japanese Retrieval Subtask is shown in Table 12. As canbe seen from Table 12, both “hcu1” and “hcu2” improved 66 percent of cases in set a, and 73 percent in
set b, while impaired in 13 percent in set a, and 17
percent in set b. We show an example topic that oursystem performed the best in appendix. From the result, we can conclude that our method can correctly
expand queries in most cases.

a6

hcu1 vs.
baseline
hcu2 vs.
baseline
hcu1 vs.
baseline
hcu2 vs.
baselineAcknowledgment

The author would like to express his gratitude to
the organizers of the NTCIR-6 Patent Task for theirsuggestions to improve his paper. This work was supported by Industrial Technology Research Programin ’06 from New Energy and Industrial Technology
Development Organization (NEDO) of Japan.

References
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Patent Retrieval Task at the NTCIR-6 Workshop.
In Proceedings of the Sixth NTCIR Workshop
Meeting, 2007.
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14th International Conference on Computational
Linguistics, pp. 539–545, 1992.
L. Lee. Measures of Distributional Similarity. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, pp. 25–32,
1999.
D. Lin. Automatic Retrieval and Clustering of Similar
Words. In Proceedings of the 17th International
Conference on Computational Linguistics, pp.
768–774, 1998.
H. Mase, T. Matsubayashi, Y. Ogawa, T. Yayoi, Y.
Sato, and M. Iwayama. NTCIR-5 Patent Retrieval
Experiments at Hitachi. In Proceedings of the fifth
NTCIR Workshop Meeting, pp. 318–323, 2005.

E. Morin and C. Jacquemin. Acquisition and Expansion of Hypernym Links. Computer and the Humanities, Vol. 38, No. 4, pp. 343–362, 2004.
Y. Oishi, K. Itou, K. Takeda, and A. Fujii. Statistical
Analysis for Thesaurus Construction using an Encyclopedic Corpus. In Proceedings of the 5th International Conference on Language Resources and
Evaluation, pp.1368-1371, 2006.

S. Sato and Y. Sasaki. Automatic Collection of Related Terms from the Web. In ACL-03 Companion
Volume to the Proceedings of the Conference, pp.
121–124, 2003.
A. Shinmori, M. Okumura, Y. Marukawa, and M.
Iwayama. Rhetorical Structure Analysis of Japanese Patent Claims using Cue Phrases. In Proceedings of the Third NTCIR Workshop, 2002.

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Appendix
Topic: 3792
非磁性支持体の少なくとも一方の面上に、電子線硬化性樹脂を含む非磁性層と、該非磁性層上に鉄（Ｆｅ）を主成分とする磁性粉末を含む磁性層を設けてなる磁気記録媒体
磁気記録媒体であって、磁性層のガラス
磁気記録媒体転移温度（Ｔｇ）が６５℃以上であり、非磁性層は、電子線硬化性樹脂を含む非磁性層用塗料を非磁性支持体上に塗布して形成した塗膜を電子線硬化してなるものであって、電子線硬化前の塗膜のガラ
ス転移温度（Ｔｇ）が３０℃～５３℃であり、かつ、該電子線硬化性樹脂が、イオウ含有極性基を有する電子線硬化性の塩化ビニル系樹脂と、リン含有極性基を有する電子線硬化性のウレタン樹脂とを含有することを特徴とする磁気記録媒体
磁気記録媒体。
磁気記録媒体(A magnetic recording system, which has a non-magnetic layer containing reinforced plastic by electronic
beam and a magnetic layer containing magnetic powder, which primarily constituent is Iron (Fe). A magnetic
recording system, whose glass transition temperature (Tg) in the magnetic layer is over 65°C and ...)
Figure 2 A Sample of Topic
Table 14 Results of Expansion for “磁気記録媒体
磁気記録媒体”
磁気記録媒体 (magnetic recording system)
Expansion
Weight
hcu1
hcu2
1
2
3
4
5

Abbreviations
Wa
2
1

Synonyms
Ws
22

Related Terms
Wr
2
2

Hyponyms
Wh
0
1

FD 等
(FD etc.)
基盤(base)
磁気ディスク(magnetic disc)
MO
(MO)
APS
(APS)

磁気記憶装置(magnetic storage medium)
カメラ(camera)
磁気抵抗型ヘッド(magnetoresistive head)
薄膜磁気ヘッド(thin film magnetic head)
情報記録媒体(information recording medium)

磁気ディスク(magnetic disc)
磁気テープ(magnetic tape)
磁気カード(magnetic card)
ディスク(disc)
カード(card)

磁気シート(magnetic sheet)
ビデオ用(for video)
オーディオ用(for audio)
磁気記録カード(magnetic recording card)
コンピュータテープ(computer tape)Figure 2 is a sample of topic that our system improved the MAP in comparison with the baseline system. This topic is about “magnetic recording system”,
and our system expanded this term in four methods.
The expanded terms for each method are shown in
Table 14. We also show term weights for eachmethod. As can be seen from Table 14, four methods(especially Synonyms and Related Terms) could expand valid terms. Using these terms in Table 14, both
“hcu1” and “hcu2” retrieved two correct patents inranks one and two (MAP: 0.667), while the baseline
system retrieved in ranks 668 and 669 (MAP: 0.002).