Philosophy and Methodology of Clustering in Pattern Mining:
Japanese Anthropologist Jiro Kawakita’s KJ Method
TAKASHI IBA, Faculty of Policy Management, Keio University
AYAKA YOSHIKAWA, Faculty of Environment and Information Studies, Keio University
KONOMI MUNAKATA, Faculty of Environment and Information Studies, Keio University

This paper describes the methodology and philosophy behind a pattern mining process known as “clustering.” This holistic approach topattern language creation is referred to as the “KJ method” by Jiro Kawakita (Kawakita, 1967). Pattern mining is a process used to extract
the knowledge of practice (rules of thumb and tips) from individual cases and experiences, with the aim of creating a pattern language.
Clustering is carried out to discover and organize the common points from the extracted knowledge. We have used the KJ method as thefoundation of our pattern language clustering method. Invented during the 1950s and 60s, the KJ method has been widely applied in Japan,
particularly in the areas of industry and education. We seek to deepen the understanding of this method and its underlying intentions byquoting Kawakita’s explanations in an English translation. In particular, this paper elaborates on the following factual statements: themethod was developed via field science; the method uses a bottom-up approach to generate order from chaos; the method requires thatthe data be viewed outside of any existing concept or framework; the method prioritizes feelings over reason; and at the conceptual level,
the method is consistent with the essence of creativity. We expect this paper to provide readers with a clear understanding of the KJ
method with a view to using it effectively in the practice of clustering in pattern mining.

Categories and Subject Descriptors: [Social and professional topics]: Project and people management—Systems analysis and design
General Terms: Human Factors
Additional Key Words and Phrases: pattern language, pattern mining, clustering
ACM Reference Format:
Iba, T., Yoshikawa, A. and Munakata, K. 2017. Philosophy and Methodology of Clustering in Pattern Mining: KJ method invented by aJapanese Anthropologist – Kawakita, Jiro, HILLSIDE Proc. of Conf. on Pattern Lang. of Prog. 24 (October 2017), 11 pages.

1. INTRODUCTION
When creating a pattern language, it is first necessary to go through a “mining” process to gather thecontents (seeds) of what will go on to become patterns. Pattern mining is a process of collecting knowledge
from individual cases and experiences. There are various methods of pattern mining (Kerth and Cunningham,
1997; Akado, et al., 2015; Iba and Yoder, 2014), many of which suggest mining and noting a few patterns at atime, the gradual addition of which combines to constitute an entire language.
The Iba Lab, however, takes a holistic approach, mining around 30 to 40, or sometimes even 120 patterns inan organized collection from the initial stages (Iba and Isaku, 2012; Iba and Isaku, 2016). We call this approach“holistic mining,” as it aims to grasp the wholeness of the language at the mining phase, with a view tosubsequently elaborating it. Since our publication of Learning Patterns in 2008 (Iba et al., 2009; Iba and Iba Lab,
2014a), we have created more than 1,000 patterns using this approach (Iba, 2016).
In this holistic approach, it is necessary to cluster and extract many pattern seeds from the fragments ofdata acquired through mining dialogs (Collaborative Introspection or Mining Interview). To do this, we use amethod developed by Japanese anthropologist Jiro Kawakita (the “KJ method”) in the data-clustering phase.
This method has proved to be effective in our practice and has become part of our standard pattern creation
process. Recently, this mining method has been adopted by other communities such as EduPLoP (Bergin, et al.,2015; Warburton and Bergin, et al., 2016; Warburton and Mor, et al., 2016) and has been a topic of interest for
researchers in the pattern language field.
However, there are no English-language publications about the KJ method, and hence there are few
opportunities for non-Japanese speakers to learn about this approach.1 Furthermore, as feelings rather than
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that
copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.
To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. A preliminary version ofthis paper was presented in a writers' workshop at the 24th Conference on Pattern Languages of Programs (PLoP). PLoP'17, OCTOBER 2225, Vancouver, Canada. Copyright 2017 is held by the author(s). HILLSIDE 978-1-941652-06-0

rational thinking play a significant role in this method, it can be a difficult topic to understand. However, theemphasis on feeling and quality is consistent with ideas put forward by Christopher Alexander (Alexander,
1979; Alexander, 2002), suggesting that this method makes sense in terms of the consistency between thepattern language methodology and its underlying theory. This paper presents a discussion of the patternmining methodology via an examination of Jiro Kawakita’s description of the KJ method.
2. OVERALL PROCESS FOR CREATING A PATTERN LANGUAGE
There are three main phases in the process of pattern language creation (Iba and Isaku, 2016): Pattern
Mining, Pattern Writing and Pattern Symbolizing (Figure 1). The Pattern Mining phase is used to extract
knowledge of practice (rules of thumb and tips) from positive experiences, which are then noted in a specificformat that summarizes the Context, Problem, and Solution (CPS). We call this unit a “seed of a pattern” (Iba
and Isaku, 2016; Sasabe, et al., 2016). In the next phase, Pattern Writing, a full description of the patterns(Context, Problem, Force, Solution, Action, Consequence) is written down based on the seeds of patterns. This
description is then subject to a detailed collaborative revision process. In the final phase, Pattern Symbolizing,a Pattern Name and Pattern Illustration are added to express the essence of patterns symbolically (Iba andIsaku, 2016; Shibata, et al., 2016). During these processes, certain phases are revisited/repeated as thelanguage develops, as necessary.

Fig. 1. Overview of the process for creating pattern languages

In this paper, we focus on the clustering phase–a key phase in the pattern mining process. This phaseoccurs after the collection of experiential data and plays three important roles. First, it helps us to discover thecommon patterns drawn from individual experiences. At the end of the clustering process, we are left withmultiple groups of sticky notes with similar contents. Simply stated, these are the patterns lurking beneath themultiple experiences and cases. In a similar manner to the “rule of three” used in software pattern analysis,
seeking common points between these experiences and cases is an essential part of the process by which ideas
become patterns.
The second important role of clustering is to adjust the level of abstraction and granularity of the possible
patterns. Fragments of information extracted from the mining dialog usually differ in terms of the level of
1 It is said that the Affinity Diagram, which is known in the English-speaking world, was also devised by Jiro Kawakita. In this sense, thismethod was derived from the KJ method; however, it is uncertain whether the underlying theory and methodology have been translated
adequately. Furthermore, it is argued by some that it is similar to the Grounded Theory Approach (1967). However, the two methods,
although invented at around the same time, were created separately and have different core characteristics. The analysis of commonalities
and differences between the two may be a topic of interest for future works.
Philosophy and Methodology of Clustering in Pattern Mining: Page - 2

abstraction and the scale of contents. Were a full description of the patterns to be written at this stage, theoutput would be discrete in terms of abstractness and granularity. However, clustering in this phase allows fora consistency in the set of patterns by comparing every sticky note and group generated.
The third important role of clustering is the support it provides for our exploration of the essential groupmessage. The clustering process involves deep reflection about the meaning of every single sticky note. It
demands that we go beyond the superficial meaning of the words. The opportunity for discussion provides theopportunity to obtain a common understanding of the patterns, which becomes the foundation of the next
activity, Pattern Writing.
Our activities have revealed that clustering is an effective and essential step in the creation of patternlanguages. The KJ method, which is the basis of this clustering method, is well-known in Japan and frequently
applied to various fields, including industry and education. It is also significant that this method came out offield science. As such, it is a method that sums up knowledge of practice via observation and dialog.
We will now give an overview of the clustering phase process. This begins with writing down knowledge ofpractice (rules of thumb and tips) collected from the mining dialog sticky notes and placing them on the craft
paper on the table at random (Figure 2: Starting from Chaos). We then attempt to work out the essence of thecontents of the individual sticky notes (Figure 2: Hidden Meanings) by bringing together those notes withsimilar contents. It is important to bear in mind that simply moving notes with existing classification standards
such as “-ish” and “-related” is not the purpose here. Rather, the idea is to grasp the true meaning of what is
written on the notes, and to compare pairs of notes individually (Figure 2: One-to-One Comparison). Clustering
should be done using a bottom-up approach involving every single sticky note, and should never be performed
to fulfill a preexisting categorization. This is the most important aspect of the KJ method, which we discuss ingreater detail later in this paper.
Clustering is usually carried out by multiple people talking to each other and moving the sticky notes(Figure 2: Talking while Moving). While some groups of sticky notes will be generated gradually, doubt may
remain about what has been clustered, and it is important to check the clustered notes repeatedly. In the initialstages, it is normal that some notes do not fit the group in which they have been placed (Figure 2: Doubting
Clusters). But when it appears that the classification of the sticky notes makes sense, each group should becircled to clearly slow the “islands” on the craft paper (Figure 2: Discovering the Islands). Each island thenbecomes a seed of pattern.
The creation of Presentation Patterns (Iba and Iba Lab, 2014c) involved seven hours of clustering. As thetime required for clustering depends on the number of sticky notes, Collaboration Patterns required 20 hours
to classify the 360 sticky notes (Figure 3).

Starting from Chaos

Talking while Moving

Hidden Meanings

One-to-One Comparison

Doubting Clusters

Discovering the Islands

Fig. 2. Patterns for clustering in pattern mining (Sasabe, et al., 2016; Iba and Isaku, 2016)

3. THE KJ METHOD INVENTED BY JIRO KAWAKITAThe KJ method was originally invented by Jiro Kawakita, a cultural anthropologist who was searching for amethod to organize data collected from various cultures. Kawakita, whose work took place in the 1960s, a time
before modern methodologies such as ethnography were developed, believed there are three ways of
Philosophy and Methodology of Clustering in Pattern Mining: Page - 3

conducting research: “armchair science” (which consists of theorization and speculation), “experimental
science,” and “field science.” Of these three, he states that field science is an area that has received very little
attention over the years and is methodologically underdeveloped.
Due to the lack of viable existing methodology, Kawakita invented the KJ method as a way of organizing
data collected through fieldwork. He wanted to understand foreign cultures from their own perspectives rather
than perceiving them through the conceptual framework of their culture. Furthermore, he wanted a methodthat would derive meaningful discoveries from a diverse and miscellaneous collection of data.
“In organizing data, it is sometimes insufficient to simply go through the process of summarizing
and analyzing the contents with similar quality. Why is this the case? When talking aboutorganizing, it means as a process of collecting data that have completely different properties andare incomparable with each other, and deducing some sort of sense from their combinations. It isalso a process in which there is a discovery made from a combination of miscellaneous data. In
order to ‘organize’ data in this sense, a mere process of categorization is insufficient.” (Kawakita,
1967, p.53)
This insufficiency comes about because, “intrinsically, categorization is a process of grouping that occurs
within a single-category data set, which focuses on similarity; some sort of common property” (Kawakita, 1967,p.52). The KJ method was thus invented out of the necessity for “a method to integrate miscellaneous data”(Kawakita, 1967, p.53). It is the product of a search for a way in which “significant integration can be
discovered from a set of miscellaneous data that cannot be compared with each other” (Kawakita, 1967, p.5354).
Kawakita describes the KJ method’s process as follows. First, a large sheet of craft paper is spread onto atable. Much smaller pieces of paper (containing individual data) are then placed on the sheet and spreadaround (Figure 1). The smaller pieces of paper are placed at random and appropriately spaced.

Fig. 3. Clustering using the KJ method for creating a pattern language“Once all of the paper has been placed, it is then time to read all of them, patiently and calmly,
starting from the ends or the center or anywhere. It is not really necessary to read all of them; it ismore about gazing over them. A discussion of three hours can produce as much as two or threehundred pieces of paper, and this may be overwhelming to some people who are impatient.
However, there is absolutely no need to panic. Just gaze through the entire sheet starting fromanywhere.” (Kawakita, 1967, p.73-74)
At this point, it is natural to get “a feeling of anxiety that ‘such a scattered mess may never become
organized’” (Kawakita, 1967, p.121). The Iba Lab’s experience is that a small sense of despair when faced with
two or three hundred scattered sticky notes is normal. However, the KJ method has never failed to reach aconclusion, as long as sufficient time and effort are invested in the process.

Philosophy and Methodology of Clustering in Pattern Mining: Page - 4

“After a while, a feeling of familiarity will appear among the pieces of paper. There willappear noticeable connections between the papers, such as that ‘this paper is saying thesame thing as that paper’ or ‘these papers are highly similar.’ Once such connections arefound, move the pieces of paper next to each other. In this way, groups of paper will begin toappear throughout the entire table. Small teams of individual pieces of paper, in a sense.”(Kawakita, 1967, p.74)
When implementing this process, it is important to feel rather than to think logically. What is most important is
to “genuinely listen to the essence of what each piece of paper is saying. Cluster them based on the affinity of
their essential meaning. They should not be clustered based on resemblance of what they superficially look like”(Kawakita, 1970, p.58). Kawakita stresses that human feelings outweigh rational thought.
“What should be given the most attention is to cluster pieces of paper that feel similar toeach other, and when doing this, the power of feeling must come first. However, those withlittle experience are inclined to cluster based on reason more so than by listening to their
feeling. Namely, they think such that ‘paper A and paper B should be clustered together forthis and that reason.’” (Kawakita, 1970, p.58)
From another perspective, “the feeling that it is all coming together naturally is more important than to focus
on clustering the pieces of paper” (Kawakita, 1970, p.59). This bottom-up process of thoroughly comparing andarranging the individual sticky notes will allow them to settle into clusters.
“As many small teams gradually form and there are many clustered, take a close look at oneof the teams. Let’s say that there is a team consisting of five pieces of paper. The reason those
five pieces of paper were gathered together is because there was some sort of feeling ofaffinity. However, now looking at them for the second time, it is now necessary to read into
the five pieces of paper in detail. Read thoroughly, and reconsider logically ‘why these fivepieces of paper should be clustered together.’” (Kawakita, 1967, p.74)“During this process, there are sometimes mistakes found in the initial clustering. Theremay be times when an irrelevant piece of paper had been added to a team by mistake.
Generally, the contents of the five pieces of paper will communicate ‘the reason why those
five pieces of paper must be clustered together.’” (Kawakita, 1967, p.75)
Kawakita stresses that “group formation” must “always proceed from smaller scale to larger scale”. In otherwords, it must be done in a bottom-up rather than a top-down manner (Kawakita, 1967, p.77). However, hesays that some people, while understanding this, will still want to begin working from a larger scale.
“This occurs because people already have in their head, a dogmatic principle of how togroup the data; such that based on their knowledge, ‘all of these pieces of paper should be
divided into three large categories: market research, quality control, and labor management’and so on. In other words, what they are doing is merely applying their dogmatic framework
for categorization, and sorting and arranging the pieces of paper under that pre-establishedframework. With this sort of approach, the creative significance of the KJ method iscompletely lost.” (Kawakita, 1967, p.78)
Those people are “merely imposing their categorization framework upon the groups of pieces of paper. They
are letting their preconceived ideas, their dogmatic framework be the master, under which the pieces of paper
are subjugated” (Kawakita, 1970, p.59). If the process were conducted from the smaller scale, as ought to be
the case, the product would be “a natural formation resulting from genuine attention to the opinions given
forth, the suggestions from the information themselves” (Kawakita, 1967, p.78). This is the most important
aspect of the KJ method, and one that is commonly misunderstood.
In Kawakita’s own words, this can be rearticulated as “speaking for the data” (Kawakita, 1967, p.203).
“Thoroughly pay attention to what the clusters of data is saying, and if the data has something to say, listen to it.
Listen to what the data says and understand it” (Kawakita, 1996, p.11). In the KJ method, the contents of thePhilosophy and Methodology of Clustering in Pattern Mining: Page - 5

pieces of paper are the main subject, and the people are merely a media to help organize this content.
Consequently, group formation is not an artificial result. Rather, it comes about in deference to the “voices” ofthe sticky notes.
“As the group formation proceeds, the person taking part in the process will begin toexperience a new, refreshing sensation. The most important point of this sensation is to beable to feel that he/she genuinely listened to the voice of truth, and followed a moral
principle void of disagreeability.” (Kawakita, 1967, p.121)“When the map has been completed, the refreshing sensation will reach its climax. It is afeeling that ‘the chaos has long passed.’ Furthermore, that will be accompanied by a feeling ofcompleteness for ‘creating something significant.’” (Kawakita, 1967, p.122)
This statement, which is by no means exaggerated, aligns with our experiences as authors of this paper. As
seen in his use of the term “create” above, Kawakita’s thoughts on creativity lie at the heart of the KJ method.
“What the KJ method shows is that in order to truly exhibit creativity, one must go througha state of selflessness once, before insisting on the self.” (Kawakita, 1996, p.28)
The fact that order comes about via the chaotic beginnings of the KJ method is not simply a matter of technique.
Rather, it is the very essence of creativity.
“‘The chaotic beginning’ is essential. In that state, there is no distinction between the subject
and the object. I believe that first, there is chaos, and then a sort of impulse that something
must be done, appears. I believe that this is born out of a chaotic state. Therefore, people who
use the KJ method try to do something about the chaos, and observe and create labels to
make decisions or find a solution. That is, they intentionally find them out of a chaotic world
with no barriers. Once they take them and label them, data is born. I believe that only after
data is created in this way, the ‘I’ or the self is born to encounter that data. Therefore, I
believe this is where the separation of the subject occurs for the first time. I don’t believe that‘the separation of the subject occurs first.’” (Kawakita, 1996, p.154)
In his book on creativity, Kawakita also states the following:“A creative act involves the creation of the object itself, but also generates change within
the individual who is engaging in the creation. In other words, the subject is also being
created. A creation that is done one-sidedly is not truly a creative act. The more creative theact is, the more remarkable the change within the subject will be.” (Kawakita, 1993, p.86)s
For this reason, the process of pattern mining makes it is possible to discover something other than thatformerly believed. And this discovery also entails a change on the part of the individual responsible.
“The series of emotional experiences that occur with the practice of the KJ method is an
important issue in addition to the obvious end product. This is because they account for asignificant part of the creative experience, and because such creative experience has thepower to change the self.” (Kawakita, 1967, p.122)
An experience such as this is also extremely important in the context of creative learning. It forms the basis forour use of pattern language creation and clustering methods such as the KJ method in the educational setting.
4. THE KJ METHOD IN THE CASE OF PRESENTATION PATTERNS (2011)
Here, we examine how the KJ method was used in creating Presentation Patterns (Iba et alum 2012; Iba and
Iba Lab, 2014b) in 2011. Presentation Patterns describes the secrets to giving a creative presentation. It
Philosophy and Methodology of Clustering in Pattern Mining: Page - 6

contains 34 tips on the methods, viewpoints, and mindsets needed to design a creative presentation, which are
explained in 34 patterns (Figure 4).
Presentation Patterns, a pattern language for creative presentations, was created by project members
using holistic mining techniques. The KJ method was used to cluster the ideas that came out of these mining
sessions.
The project, led by Takashi Iba, was a collaborative work involving 14 students at the Iba Laboratory.
Participants were recruited according to their different experiences of presentations, including public speaking,musical performance, drama, and dance. The original pattern ideas were mined from the project members’
own experiences. Mining dialog between members with a broad variety of presentation experiences elicitedideas for what constituted a “good” presentation.

Fig. 4. 34 Patterns in Presentation Patterns

Fig. 5. Clustering phase for Presentation Patterns

Philosophy and Methodology of Clustering in Pattern Mining: Page - 7

During the mining dialog session, members jotted down attributes they considered important for attractive
presentations. Each member wrote down their ideas on sticky notes, gave a description to the whole group,
then placed their notes on the table. Members cited specific episodes related to their prior experience so thateveryone was able to understand the significance of the individual notes. The goal was to glean as many ideas
as possible for potential patterns. Repetitions, add-ons and opposite opinions were welcomed, and nothing was
excluded. Selection and grouping were postponed until later. These two mining dialog sessions generated 207
potential ideas for patterns.
These ideas were organized using the KJ method. In the clustering phase, ideas that are thought to have
similar attributes are grouped together and placed close to each another (Figure 5 & 6). However, thesesimilarities must not be mere superficial resemblances. Core traits and functions must be observed anddiscussed before a connection between two notes can be made. Another important aspect to bear in mind isthat notes must be moved as pairs.

Fig. 6. Starting from Chaos: example of clustering for creating Presentation Patterns

Once the process starts, clusters of notes with similar ideas begin to emerge. The temptation arises toconnect an idea to a group of ideas; however, this would once again be superficial. Categories of ideas emerge
as a result of connecting pairs of ideas. The KJ method is complete when group members believe that all ideas
have been mapped into the correct relations. At this point, the notes have formed emergent clusters, each ofwhich is a potential pattern. Some of these clusters contain dozens of notes, while others contain a few. In thepresent example, the 207 ideas emerging from the mining dialog phase formed 40 clusters.
Our focus here is on two patterns from Presentation Patterns: “Presentership” and “Touching Present”. We
will examine how the individual sticky notes were clustered to form the basis of these patterns.
The first example, “Presentership”, is a pattern relating to audience considerations in presentation design.
This pattern was created from five different ideas from project members, which were written down on
individual sticky notes and clustered (see Figure 7). The following is a sample conversation from the discussionthat surrounded the clustering.
•Group member A: “’Look at the entire audience’ is definitely an important part of a presentation.”•Group member B: “I agree. I think this is very similar to ‘be aware that there is an audience watching.’
I think these two ideas stress the importance of having a good stage presence.”

Philosophy and Methodology of Clustering in Pattern Mining: Page - 8

•Group member C: “Okay, let’s put those two together. Hmm, I think ‘don’t look down at your notes’ isan important part of being aware of the audience!”•

Group member A: “Yes, those should be placed side by side. So should ‘Don't hide behind the podium.’”•

Group member D: “Ah, I also think that ‘look at the person who is speaking when you are not the
speaker’ is similar to not looking down at your notes. I often take note of this when presenting as partof a group.”

Fig. 7. Cluster of sticky notes for “Presentership”, Presentation Patterns

The second example is “Touching Gift”, a pattern about considering the audience when designing apresentation. The concept for this pattern came from a cluster of seven sticky notes (see Figure 8). As shown
here, the seemingly unrelated sticky notes come together as a result of one-on-one comparisons. Each “island”
represents the multiple elements that come together to create the concept of the pattern.

Fig. 8. Cluster of sticky notes for “Touching Gift”, Presentation Patterns

Philosophy and Methodology of Clustering in Pattern Mining: Page - 9

5. CONCLUSION
Jiro Kawakita believed that the KJ method was both a philosophy and a technique. These two elements are
generally differentiated, with focus generally given to one or the other. For Kawakita, however, the KJ method
was an approach in which “the philosophy and technique must not be separated” (Kawakita, 1996, p.153). In
this sense, this paper has introduced not only the KJ method itself but also the philosophy behind it.
According to Kawakita, “it is not sufficient for people to know about the KJ method intellectually; it is only
fully understood when it is experienced” (Kawakita, 1967, p.127). The authors of this paper encourageinterested readers to put the KJ method into practice and experience the process. In so doing, patterns derived
from clustering may prove themselves to be a valuable resource (Sasabe et al., 2016; Iba and Isaku, 2016).
ACKNOWLEDGMENTS
We would like to thank our shepherd, Joseph Yoder, for his generous support and advice during therevising of this paper. Our thanks also to Christian Kohls, Michael Weiss, Guido Münster and otherparticipants for their valuable contributions to Writers' Workshop discussions.
REFERENCES
Akado, Y., Kogure, S., Sasabe, A., Hong, J-H, Saruwatari, K., and Iba, T. (2015) “Five patterns for designing pattern mining
workshops,” EuroPLoP’15 Proceedings of the 20th European Conference on Pattern Languages of Programs (EuroPLoP2015).
Alexander, C. (1979) The Timeless Way of Building, Oxford University Press.
Alexander, C. (2002), The Nature of Order: An Essay of the Art of Building and the Nature of the Universe, Book 1: The
Phenomenon of Life, Center for Environmental Structure.
Bergin, J., Kohls, C., Köppe, C., Mor, Y., Portier, M., Schümmer, T. and Warburton, S. (2015), “Assessment-Driven Course
Design-Fair Play Patterns,” in Proceedings of the 22nd Conference on Pattern Languages of Programs (PLoP2015).
Iba, T. (2016) “Pattern Language 3.0 and Fundamental Behavioral Properties,” in Pursuit of Pattern Languages for Societal
Change. Designing Lively Scenarios in Various Fields, eds by Peter Baumgartner, Tina Gruber-Muecke, Richard Sickinger,
Berlin: epubli, pp.200-233.
Iba, T., and Iba Laboratory. (2014a) Learning Patterns: A Pattern Language for Creative Learning, CreativeShift.
Iba, T., and Iba Laboratory. (2014b) Presentation Patterns: A Pattern Language for Creative Presentations, CreativeShift.
Iba, T., and Iba Laboratory (2014c) Collaboration Patterns: A Pattern Language for Creative Collaborations, CreativeShift.
Iba, T., and Isaku, T. (2012) “Holistic Pattern-Mining Patterns: A Pattern Language for Pattern Mining on a Holistic Approach,”in the 18th Conference on Pattern Languages of Programs (PLoP2012).
Iba, T., and Isaku, T. (2016) “A Pattern Language for Creating Pattern Languages: 364 Patterns for Pattern Mining, Writing,and Symbolizing,” in the 23rd Conference on Pattern Languages of Programs (PLoP2016).
Iba, T., Matsumoto, A., and Harasawa, K. (2012) “Presentation Patterns: A Pattern Language for Creative Presentations,”
EuroPLoP’12 Proceedings of the 17th European Conference on Pattern Languages of Programs.
Iba, T., Miyake, T., Naruse, M., and Yotsumoto, N. (2009) “Learning Patterns: A Pattern Language for Active Learners,”
PLoP’09 Proceedings of the 16th Conference on Pattern Languages of Programs (PLoP2009).
Iba, T., and Okada, M., Iba Laboratory and Dementia Friendly Japan Initiative. (2015), Words for a Journey: The Art of Being
with Dementia, CreativeShift.
Iba, T., and Yoder, J. (2014) “Mining Interview Patterns: Patterns for Effectively Obtaining Seeds of Patterns,” inSugarloafPLoP 14 Proceedings of the 10th Latin American Conference on Pattern Languages of Programs(SugarloafPLoP2014).
Sasabe, A., Kaneko, T., Takahashi, K., Iba, T. (2016) “Pattern Mining Patterns: A Search for the Seeds of Patterns,” in the 23rd
Conference on Pattern Languages of Programs (PLoP2016).
Kawakita, J. (1967) Hassouho: Sozosei Kaihatsu notameni [Abuduction Method: For Development of Creativity], in Japanese,
Chuokoronsha.
Kawakita, J. (1970) Zoku Hassouho: KJ-ho no Tenkai to Ouyo [Abuduction Method, Continued: Evolution and Application of KJ
method], in Japanese, Chuokoronsha.
Kawakita, J. (1993) Sozo to Dento: Ningen no Shino to Minshushugi no Kongen wo Saguru [Creation and Tradition: Search forFoundation of Human and Democracy], in Japanese, Shodensha.
Kawakita, J. (1970) Kawakita Jiro Chosakushu 6: KJ-ho to Miraigaku [Writings of Jiro Kawakita, Vol. 6: KJ method andFuture Research], in Japanese, Chuokoronsha.
Kerth N. L. and Cunningham W (1997) “Using Patterns to Improve Our Architectural Vision,” IEEE Software 14(1), Seite 53-59.
Shibata, S., Kogure, S,, Shimizu, H., and Iba, T. (2016) “Pattern Symbolizing Patterns: Symbolizing the content and value by
expressions to facilitate intuitive comprehension,” in the 23rd Conference on Pattern Languages of Programs (PLoP2016).
Warburton, S.; Bergin, J.; Kohls, C.; Köppe, C. & Mor, Y. (2016), “Dialogical assessment patterns for learning from others,” inProceedings of the 2016 VikingPLoP conference, ACM, Leerdam, Netherlands.
Warburton, S., Mor, Y., Kohls, C., Köppe, C., Bergin, J. (2016). “Assessment driven course design: a pattern validation
workshop,” in 8th Biennial Conference of EARLI SIG 1: Assessment & Evaluation, Munich, Germany.
Received May 2017; revised September 2017; accepted January 2018
Philosophy and Methodology of Clustering in Pattern Mining: Page - 10

Appendix: How to conduct clustering in pattern mining using the KJ methodA) Grasping the Mined Elements… Form a shared understanding of the information
available to the group.
Environment for Focusing

Element Comprehension

Element Pairing

Coordinate an environment
where you can spread several
sheets of craft paper on a large
table and focus for long periodsof time. The sticky notes shouldbe placed at random to create achaotic start point.

Carefully but dynamicallycomprehend the true meaning ofeach note. Summarize theessence of the information
written on the note in your own
words, and discuss whether
your understanding is correct.

Place two elements that aresemantically proximate near toeach other. Look over the wholetable and consider the proximity
of notes in a one-to-one manner,without getting caught up in any
superficial similarities.

B) Group Thinking… Go through the process together. Think of the group as one large
brain, and talk through any thought processes so that they can be shared with othermembers.
Talking while Moving

Essence Digging

Iterative Questioning

Always talk to the group whenmoving a note. Consider one
topic at a time, as a group, andhave each person share theirthoughts.

Look for the essence of eachnote by recalling the kind of
episode it came from, and theway in which this seemed
important.

Even if a note was moved justonce, question the process andrepeatedly consider its
relationship with other notes,
adjusting its position
accordingly.

C) Finding Overlaps... Find the common meaning among several notes and notice any
overlapping patterns.
Active Inquiry
Discovering the Islands
Mapping Islands
When clustering, both the notes
and the participants should beconstantly on the move. This
allows for the notes to beconsidered from different
perspectives.

Find the “islands,” or the groups
of notes. Persist with theclustering process until thenotes find their proper resting
place.

Organize and confirm the“islands” formed bysemantically proximate notes.

Philosophy and Methodology of Clustering in Pattern Mining: Page - 11