=Paper=
{{Paper
|id=Vol-1437/ipamin2015_submission_9
|storemode=property
|title=Patent Analysis for Organization based on Patent Evolution Model
|pdfUrl=https://ceur-ws.org/Vol-1437/ipamin2015_paper9.pdf
|volume=Vol-1437
}}
==Patent Analysis for Organization based on Patent Evolution Model==
https://ceur-ws.org/Vol-1437/ipamin2015_paper9.pdf
Patent Analysis for Organization based on Patent
Evolution Model
Yunji Jang Jangwon Gim Jinpyo Lee
KISTI, UST KISTI KAIST
Korea Institute of Science and Korea Institute of Science and Korea Advanced Institute
Technology Information, KISTI Technology Information, KISTI of Science and Technology,
University of Science and Daejeon, South Korea KISTI
Technology, UST jangwon@kisti.re.kr Daejeon, South Korea
Daejeon, South Korea jinpyo.lee@cs.kaist.ac.kr
yunji@kisti.re.kr
Do-Heon Jung Hanmin Jung
KISTI KISTI
Korea Institute of Science and Korea Institute of Science and
Technology Information, KISTI Technology Information, KISTI
Daejeon, South Korea Daejeon, South Korea
heon@kisti.re.kr jhm@kisti.re.kr
ABSTRACT
With the rapid progress in science and technology in recent times,
new research fields are being discovered and studied each day and
1. INTRODUCTION
With the rapid progress in science and technology in recent times,
numerous research findings are being published and presented.
new research fields are being discovered and studied each day and
Considering this, organizations from various countries have been
numerous research findings are being published and presented. In
investing considerable effort to bring about internal and external
several countries including South Korea, USA, and Japan,
changes in their organizations. In fact, at many organizations,
policies for strengthening the protection of intellectual property
studies are being carried out to derive meaningful results by
are being implemented. Moreover, the number of patent
analyzing research outcomes. Thus, in this paper we propose an
applications for research results has also increased [1].
evolution model through analysis of the patent titles from one
Considering this, organizations from various countries have been
specific institution. First, we classified the keyword of title
investing considerable effort to bring about internal and external
according to properties of keyword and then defined the relation
changes in their organizations. In other words, organizations
case of patent. After, we suggest the evolution model of relation
believe that they may not be able to survive in today’s competitive
based on timeline and applied to the actual data. It can predict
market without innovation, and therefore, much effort is being
keyword of future patent by applying to actual data.
invested in that direction [2]. In fact, at many organizations,
studies are being carried out to derive meaningful results by
analyzing research outcomes [3,4]. In general, among the research
Categories and Subject Descriptors outcomes, patent data is a type of research outcome that can be
H.4 [Information Systems Applications]: Data Mining used as an indicator for measuring the technological and
I.6: [Simulation and Modeling]: Model Validation and Analysis innovative competency of an organization. Patents are not only
essential from the standpoint of copyrighting and publishing of
General Terms research and development, but also for aiding future research and
Theory development plans [5].
Patent data consist of title, technology implementation details,
Keywords technology category code, citation information, and owner
Patent Data, Patent Analysis, Patent Keyword, Patent Evolution, information. Analyzing such patent information is very important
Organization Patent because it can help in interpreting the changes in the technology,
trends, level, and commercial value. Patent analysis includes
various kinds of analysis such as frequency analysis, share
Copyright © 2015 for the individual papers by the papers' analysis, time-series analysis, citation analysis, and rights analysis.
authors.Copying permitted for private and academic purposes. Time-series analysis and two-dimensional analysis, in particular,
This volume is published and copyrighted by its editors. are more common [6].
Published at Ceur-ws.org Proceedings of the Second
International Workshop on Patent Mining and its Applications
(IPAMIN). May 27–28, 2015, Beijing, China.
2.1. Title Refinement
Table 1. Types of patent analysis
The refining patent title stage is performed prior to the extraction
Theme Details of meaningful keywords such as goal and approach. In this stage,
Frequency Filed country, Inventor, Applicant, unnecessary words are removed from the patent title. On the basis
Analysis Technology Classification .. of blank spaces, the patent title is divided. Considering the
Filed country, Inventor, Applicant, statistical numbers of divided words, they are removed step by
Share Analysis Technology analysis, Detailed technical step.
classification ..
Application rate analytics , National analysis, 2.2. Patent Representation
Time Series Inventor analysis, Applicant analysis,
To observe the keyword concept-based evolution process for a
Analysis Technical analysis, New applications analysis,
certain organization, the words from the refined titles are
New inventor analysis ..
classified into Approach, Goal Object, and Goal Predicate. Goal
Inventor correlation map, Applicant represents keywords that indicate the purpose of the patent's
Correlations
correlation map, Technical correlation map .. invention. Since the title of a patent is the name of the invention, a
Citation Citation relation analysis , Core patent goal keyword, which is the target technology, is always present.
Analysis analysis .. Based on the type of Patent, Approach keywords are sometimes
Rights Patent family map .. present, which are keywords that describe the core technology
Analysis used to develop the goal technology. In this study, a dictionary
was built for classifying keywords into Approach and Goal. The
Several studies have attempted to analyze the characteristics of classified Approach and Goal keywords are tagged as object and
companies based on the citation relationship of patents, for predicate through a prebuilt morpheme analyzer. When the
example, the number of research projects that attempt to morpheme analysis is completed, a relation network is drawn to
determine the technological strategy of a competing company map the relation types between Approach, Goal Object, and Goal
through citation relationship has been on the rise [7-10]. Predicate.
These studies analyze a company based on the information of the 2.3. Relation Type Definition
patents the companies have applied for; however, to the best of
our knowledge, no study has performed a time-series analysis of All types were defined for the types of relations for patent
patent data yet. Therefore, in this paper, we propose a patent expressions between two or more patent titles. The relations
evolution model based on time-series analysis. Furthermore, defined in this paper refer to cases in which one or more keywords
unlike previous papers, in this paper, we only analyze the title, overlap among three keywords that are separated into Approach,
among the many patent data, as a patent title can adequately serve Goal Object, and Goal Predicate.
as representative information about a patent.
2. PATENT ANALYSIS MODEL
In this study, we analyze the evolution process of a patent title in
four stages. Figure 1 shows procedure of patent analysis. First,
after removing the useless, meaningless words from a patent title,
the remaining words, keywords, which represent the purpose of
the patent and the patent's core technology, are extracted. Next,
while drawing a relation network to map the relation type between
the extracted keywords, the evolution of relation types is
examined by applying time-series analysis.
Figure 2. Patent relation types
Figure 2 shows the relation types that can be derived on the basis
of Approach, Goal Object, and Goal Predicate. A circle indicates
an Approach, a triangle indicates a Goal Object, and a diamond
indicates a Goal Predicate. Figure 2-1) indicates one patent type.
Figure 2-2) relation type is X-type. X- type is a case involving
several Approaches and several Goal Predicates mapped to one
Goal Object. Figure 2-3) relation type is Y- type. The Y- type is a
case involving several Approaches mapped to a Goal Object and
Goal Predicate pair. Figure 2-4) relation type is inverted Y- type.
The inverted Y-type is a case of several Goal Predicates mapped
to an Approach and Goal Object pair. Figure 2-5) relation type is
V- type. In the V-type, several Goal Objects and several
Figure 1. Patent analytics model Procedure Approaches are mapped to one Goal Predicate. Figure 2-6)
relation type is inverted V-type. In the fifth inverted V-type,
several Goal Objects and Predicates are mapped to one Approach. Table 2. Semantic stopword dictionaries
The ◇ type is a case involving several Goal Objects mapped to an
Approach and Goal Predicate pair. Finally Figure 2-8) refers to Semantic Stopword General Stopword
the Double X type having the several approaches, Goal Object, System and Method Optimum
and Goal Predicate. X type of relationship types can also have
resulted in multiple forms, but we studied only Double X type of Apparatus and method Effective
relationship type.
Method and System For
2.4. Evolution Model Definition System and Apparatus About
In this section, a definition is provided for the evolution model. Framework Included
The evolution model is made using the characteristics of relation
types based on the time-series data of a certain organization. System At
Figure 3 shows a model that can evolve according to the relation
: :
type. As an example of an evolvable model, “A type can evolve to
B type” refers to a case where the condition of B type is satisfied
when A type and B type are combined. In other words, when A Table 3. Distinguishing word dictionaries
type and B type are combined , it should be B type.
A-G Distinguishing word A-G Distinguishing word
Based on Applied
Based Through
Using By
Centered According to
Table 3 used is a terminology dictionary for classifying Approach
and Goal. After classifying Approach and Goal, the remaining
words are processed as useless words. In fact, the words of
Korean are more than English word. So Table 3 is smaller than
Korean dictionaries.
Figure 3. Evolution model
3.3. Statistics
The statistics produced when applying the unnecessary word
All relation types can evolve into the type of each one. Ø and I dictionary for 82 cases are shown. Goal Object and Goal Predicate
relation types can be evolved into all relative types. In addition, were extracted in all 82 cases, and Approach was extracted in only
all relation types can evolve into all relative types. However, Y 44 cases. We made the statistics about the relation type and
and can evolve into the X relation types. evolution model. Table 4 shows the cumulative statistics of
relation cases from 2005 to 2013. The X-type type appeared most,
3. EXPERIMENT followed by V-type.
3.1. Data Set Table 4. Statistics of relation type
The data set was composed of 82 patents of the Computer Base X Y V Λ ◇
Intelligence Lab of Korea Institute of Science and Technology
Information (KISTI) from 2005 to 2013. At first we started 99 2005 1 0 0 0 0 0 0
data but 17 titles having parallel structures were discarded. 2006 0 1 0 0 0 0 0
3.2. User Defined Dictionaries 2007 1 1 0 0 1 0 0
As explained in the overall process stage, a process involving 2008 3 1 0 0 0 0 0
analysis and tagging of a sentence structure was performed. Based
2009 2 3 0 0 1 1 0
on the patent title set, several word dictionaries were built.
Modeling was performed to identify similar results through 2010 2 4 1 1 4 2 0
cognitive analysis. Tables 2 and 3 is a dictionary to translate
Korean to English. Table 2 shows the part of dictionary used for 2011 2 4 2 1 5 3 1
refining useless words. 2012 3 5 3 1 5 3 1
2013 3 6 3 1 5 3 1
Sum 3 6 3 1 5 3 1
Table 5. Statistics of evolution model
I I X X XX Y Ø Ø Ø
→ → → → → → → → →
XX X X XX XX XX I V Y
2005 0 0 0 0 0 0 1 0 0
2006 0 1 0 0 0 0 0 0 0
2007 0 0 0 1 0 0 1 0 0
2008 0 0 0 0 0 0 2 0 0
2009 1 1 0 0 1 0 2 1 0
2010 0 1 0 1 3 0 1 0 1
2011 0 0 2 1 0 1 0 0 0
Figure 5. Evolution model in KISTI
2012 0 1 1 0 1 0 1 0 0
2013 0 0 0 0 1 0 0 0 0
Sum 1 4 3 3 6 1 8 1 1 The Evolution Model which can be discovered in KISTI patent
among 30 Evolution Model is 9. The numbers in Figure 5 is the
Table 5 is statistics of evolution model. It was the most abundant probability to go in the direction of the arrow. I type, Y type , V
to evolve into the Ø types from I type. This evolution case means type are evolved from the O type. The probability of evolving into
new patent is indicated in KISTI. I types is 0.8, the probability of evolving into Y and V types are
0.1. The types which can be evolved from I type are X and XX
3.4. Result type. The probability of evolving into X type is 0.8 and the
probability of evolving into XX type is 0.2. The types which can
In this section, we compare the actual results with the evolution be evolved from X types are X types and XX type. And each
model proposed in this paper. probability is 0.5. The XX type is only type which can be evolved
from Y type and XX type evolves into XX type. The inversed Y
type, Λ type and ◇ type of evolution model are not observed in
KISTI patent. By predicting the future evolution type KISTI
patent based on this result, it can be extract keywords that match
the type of evolution. For example, when the patent evolves into
the patent of X types from I type, we can predict that KISTI will
research about Goal Object.
4. CONCLUSIONS
In this paper, we proposed the patent evolution model through the
patent title analysis of the specified affiliation. We presented the
new possibility by studying the Korean title which was not active
in the existing research. We removed the stop words at the patent
title of the specified affiliation and we separated the Approach,
Goal Object, and Goal Predicate. By using separated three
keywords, we drew the connection network in the patent title
based on time series. It defined the types of relationships that may
Figure 4. Relation network of KISTI patent appear between the patent through the network connection in a
given year. And then we can know the relation case of
organization based on the result of test.
Figure 4 shows the final relation network of Approach, Goal
Object, and Goal Predicate for 2013. The network was drawn by Patent analysis systems and related methods currently rely on
NodeXL [11]. The evolution of relation types was examined by basic visualization techniques and patent maps, such as bar graph,
drawing the relation network for patent titles keywords of 2005 to pie chart, separate table, and bubble diagram. Relation types
2013, as shown in Figure 4. Figure 4 shows the evolution model between patents and an evolution model of relations were
produced from the KISTI patents. Figure 5 shows the evolution proposed only using the titles of patents.
model produced from the KISTI patents. In a follow-up study, we plan to perform the same analysis for a
different organization, and compare it with the evolution result of
this study; further, we plan to examine the expandability of the
proposed model. In particular, we aim to further develop the
proposed patent evolution model so that it can be applied to
patent titles of other countries in addition to those of South Korea.
Furthermore, we expect to use it in convergence technology
prediction by predicting a relation type, in which a patent relation
of certain relation type will evolve, through the evolution model.
international conference on Communities and technologies, pp.
255-264, 2009.
Acknowledgments
This work was supported by the IT R&D program of MSIP/IITP.
[B010-15-0353, High performance database solution development
for Integrated big data monitoring and Analytics]
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