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An Information Management System with

the Facility to Support

Long-term Creative Thinking

Hirohito SHIBATA and Koichi HORI

RCAST, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan.

{shibata, hori}@ai.rcast.u-tokyo.ac.jp

Received 26 Feb 2002

Abstract

Most previous creativity support systems sustain short-term temporal thinking that is separate from users’daily activities. In this paper, we propose a system to support long-term idea-generation in daily life. The system consists of two subsystems: a management system for problems and ideas called IdeaManager; and a personal information storage system called iBox. When information is registered in iBox, it searches related problems and ideas in IdeaManager and presents the results. Users then try to generate or enhance ideas for automatically retrieved problems or ideas using registered information as the hint. To evaluate and enhance our system, we carried out a six-week experiment. Based on the results, we give some proposals for future systems.

Keywords creativity support system, information management system

§

1

Introduction

Since the late 1980’s, numerous systems supporting idea-generation, called creativity support systems, have been proposed.9, 17) However, most of these systems have not gained widespread use. ∗1

∗1 In particular, systems based on the creative thinking technique TRIZ2)have been intro-duced to industrial companies as tools for patent strategy. Their use, however, is restricted to improving artifacts, and we cannot adapt its technique or systems to other fields, such as concept creation or non-technical daily activities.

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The authors of this paper explain this as due to the fact that these systems support isolated aspects that are separate from professionals’daily activities.10) These systems do not support the repeated refining of problems or ideas, that is, they fail to support long-term thinking. In addition, even when problems in which they are engaged are dependent on or similar to one another, users’previous ideas remain unused. Thus these systems are useful only on a temporary level. Moreover, these systems support only intentional idea-generation. They assume that users use them with conscious of generating ideas. However, according to our experiences and prior cases of idea-generation, cases of idea-generation occur more frequently at times when one does not con-sciously try to generate ideas.3, 7)In prior research, such phenomena are referred to as inspirations, illumination, insight, Aha experience, or Eureka phenomena. In this paper, in order to avoid the mysterious imagery evoked by these terms, we venture to call these phenomenanon-intentional idea-generation.

Based on these claims, we have built a system to support long-term creative thinking.15, 16) Its target users are those who need to generate ideas and collect large amounts of information for a certain problem or theme, for example researchers or planners. The support level sustains idea-generation for problems that are important for individuals, which Boden calls P-creativity.3)

Our system consists of two subsystems: a management system for prob-lems and ideas calledIdeaManager, and a personal information storage system callediBox. When information is registered in iBox, it will automatically search related problems and ideas in IdeaManager and present the results, if there are any. Then users will try to generate or enhance ideas for automatically retrieved problems or ideas using newly registered information as the hint. Most actual non-intentional idea-generation is driven by perception of clue-giving event, such as reading a book or having a conversation. In our approach, we consider the registering of information to the storage system as a clue-giving event.

Our daily lives are filled with stimuli. These stimuli provide chances to generate ideas. Based on the concept that ”a chance is not what is given but is what we should get for ourselves,” our system amplifies chances to generate ideas through activities of information management. In this sense, our system can be called an ’information management system with the facility to support idea-generation.’

As for searches driven by the registering of information, the nature of the retrieved problems or ideas becomes an important issue. If users do not

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find the presented problems or ideas novel, they will not pay attention nor think about them.13) Therefore, we have carried out an experiment using our system to explore effective search mechanisms. Most previous studies pursued objec-tivity for short-term experiments that were disconnected from subjects’daily activities.6) However, idea-generation deeply depends on the conditions of an individuals’context, such as experience or situation. In our experiment, during six weeks, subjects managed their problems and ideas using our system for their daily activities.

The outline of the paper is as follows. In Section 2, we first explain the overview of the system. In Section 3, we explain a method of the experiment. In Section 4, we analyze the data of the experiment and discuss the results. In Section 5, we give comparisons to related work. Finally, we give the conclusions.

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2

System Overview

Our system is based on the observation of actual idea-generation. First, we summarize the results of the study.15)

(1) There are more cases of non-intentional idea-generation than intentional ones. In the study, 33 cases (more than half of the entire 65 cases) of idea-generation were classified as non-intentional.

(2) Generating ideas is a long-term activity. Of the 32 cases in which ideas were for problems that had previously recognized, in 29 cases (90.6%) it took more than one week to generate ideas and in 22 cases (68.9%) it took more than one month.

(3) People are likely to generate ideas if they remember a corresponding prob-lem recently. For the above 32 cases, subjects in 23 cases (71.9%) thought about the problems during the one week prior to the idea-generation, and subjects in 18 cases (56.3%) thought about the problems during three days prior to the idea-generation. We call this phenomenon therecency effect in idea-generation.

(4) Most non-intentional idea-generation is driven by an external clue. Of the 33 cases of non-intentional idea-generation, subjects in 30 cases (90.9%) perceived the existence of clues for generating ideas, and in 20 cases these clues were from external sources, such as books or conversation. We call this phenomenon theclue-dependency of non-intentional idea-generation. Results (1) and (2) support our previously described claims. Our system is based on results (3) and (4). In order to obtain the recency effect in

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idea-generation, we have built a management system for problems and ideas which we call IdeaManager. In order to increase chances of the clue-dependency of non-intentional idea-generation, we have built a personal information storage system, which we call iBox, and made this cooperate with IdeaManager. Both systems run on Windows and are implemented by using the search engine of Albase.11)

2.1

IdeaManager: A Management System for Problems

and Ideas

In long-term idea-generation, a person generally searches for ideas and refines them many times until he/she acquires satisfactory ones. Here, for the next trial of idea-generation, he/she must recall the problem. In order to avoid forgetting problems and ideas,∗2 IdeaManager (Fig. 1) supports their retention and management.

Idea Window Problem Window

Related Information Window

List of names

Information - Name - Content - Keywords

Fig. 1 A screen shot of IdeaManager.

Information stocked in IdeaManager is divided into three types: prob-lems, ideas, and related information. Information of each type is stocked in a

∗2 Generally, a person faces a lot of problems and tries to resolve them simultaneously. In this case, he/she tends to concentrate on only a few important problems and forget the existence of others. Such phenomenon is known as a ’failure of prospective remembering’ in psychology and observed very often (e.g. Reference8)).

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corresponding window. Users can view problems, ideas, and related information, side by side. All information in IdeaManager has itsnameandkeywords. Only text can be stocked in the current version. Although users basically assign their own keywords, IdeaManager provides the facility to assist the user assigning key-words using morphological analysis. IdeaManager provides the following basic search functions: search by keywords, full text search, search by date, and list of all information. Each of these functions returns a list of names. By select-ing a name in the list, users can view the information along with its name and keywords.

As a management system for problems and ideas, problems have three attributes (state,deadline, andimportance) and ideas have one attribute ( evalu-ation). In addition to the basic search functions, IdeaManager includes filtering functions with the above attributes. If a deadline for a problem is near, Idea-Manager will detect it and warn the user. Users can also set a link between two pieces of information. Using this link function, users can manage problems with corresponding ideas and related information.

2.2

iBox: A Personal Information Storage System

iBox (Fig. 2) is a personal information storage system used in various types of situations, such as the work place or in other daily activities. Similarly to IdeaManager, iBox stocks all text information with its own name and keywords. iBox provides the same basic search functions as IdeaManager. Each of these functions returns a list of names. By selecting a name in the list, users can view the information along with its name and keywords.

iBox is used in our laboratory, and the following examples are types of information that the users have actually stocked in iBox: research notes, memoranda, comments on books, methodologies of programming or computer setup, technical terms, schedules, diaries, addresses, and so on.

2.3

Cooperation Between IdeaManager and iBox

Our system provides two types of cooperation. The registering or updat-ing of information in one application triggers a search for information in another application (we call this thepop-up search) and presents the results (Fig. 3).

Information stocked in iBox reflects user’s interests. Such information may have some relation to the user’s current problems. When information is registered in iBox, it searches related problems and ideas in IdeaManager. If

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Name Content of information Keywords List of names Tree of boxes

Fig. 2 A screen shot of iBox.

there are any results, iBox informs the user through a small dialog box in the corner of the display so as not to distract the user’s thought process. If the user demands it, iBox brings up IdeaManager to present the result (as a list of names). We hope that the user will be able to generate or enhance ideas for retrieved problems or ideas using newly registered information as the hint. Registered information may also work as a supportive or counter example for retrieved problems or ideas. This feature aims to support non-intentional idea-generation by using registered information as a potential clue-event. Information stocked in iBox must have novelty or meaningfulness, which Finke and his colleagues6) refer to as ’preinventive properties.’ A trial of idea-generation at this moment leads to the ’function-follows-form approach’ of idea-generation mentioned by Finke et al.

Also, when a user recognizes a problem, viewing related information might stimulate the user’s thought process. When a problem or an idea is registered in IdeaManager, it searches related information in iBox. If there are any results, IdeaManager informs the user of that. If the user demands it, IdeaManager brings up iBox to present the results (as a list of names). We hope that the user will then be able to generate or enhance ideas for registered problems or ideas using retrieved information as hints. This feature aims to support intentional idea-generation.

As for idea-generation, we do not think that it is effective to force users to try to generate ideas at just any time or place. The ability to pay attention

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iBox IdeaManager Information Memo Diary Schedule Paper Idea Problem Search

Popup problems and ideas

Problem Idea Popup information Search Idea Problem Idea Trial of idea-geneeration Generate ideas Enhance ideas

Fig. 3 Cooperation between IdeaManager and iBox.

is an important resource for people, and systems should present the right thing at the right time.5) In our approach, we consider the right thing to be the in-formation stocked by the user, since that inin-formation will be filtered through the reader. We consider the right time to be the moment when information is registered, since this is the moment when the user, with his/her mind filled with this information, discovers some interesting information.

The search mechanism in the pop-up search is a crucial point of investi-gation in our experiment. We introduce various types of search mechanisms in the next section.

§

3

Experimental Method

3.1

Various Search Mechanisms

The objective of the pop-up search is to present information that will stimulate users’thinking processes. Thus this objective is different from that of general information retrieval techniques that aim to enhance recall and preci-sion. To stimulate users’thinking, it is necessary for retrieved information to be referred by the users themselves. We consider the following factors important for that end.

Similarity between registered information and retrieved information,

Users’familiarity with searched information.

As for similarity between registered information and retrieved informa-tion, our search mechanisms are based on the number of co-occurrences of words.

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We have prepared three-level search mechanisms (high,middle, andlow). At the high level, the system searches for information containing the same keywords as-signed by users, then sorts the results according to the number of co-occurrences, and finally presents the top 5 results in the pop-up search. At the middle level, the system expands keywords using a thesaurus dictionary, then searches infor-mation containing the expanded keywords, sorts the results, and finally presents the top 5 results. At the low level, the search mechanism is the same as the middle level except that the low level presents the bottom 5 results at the end. Here, the thesaurus dictionary utilized is an internal Fuji Xerox Co., Ltd. The-saurus, which has 53,446 entries and 119,374 words. By expanding keywords using a thesaurus, we expect information that may not have obvious relevancy to the registered information will be retrieved. In a prior study, we found that if there were too many results in the pop-up search, users would not look through them.16) So, in this experiment, we controlled the number of results to 5.

As for users’familiarity with searched information, we have prepared two-level search mechanisms (oldandrecent). For the old condition, in the pop-up search driven by iBox, the system searches information with a final reference time of over 2 days prior to the current search, and in the pop-up search driven by IdeaManager, the system searches information with a final reference time of over 31 days. For the recent condition, in the pop-up search driven by iBox, the system searches information with a final reference time of 1 day prior, and in the pop-up search driven by IdeaManager, the system searches information with a final reference time that is within the previous 30 days. We customized accordingly the threshold of users’familiarity with the pop-up search driven by iBox and IdeaManager. That was because we considered the problems and ideas were more important than other information, and users seemed to tolerate the repeated references. These thresholds were determined empirically based on our prior study.

3.2

Procedure

The subjects were six students in the graduate school of engineering. Their research fields were in computer-human interaction or robotics. The test period was for six weeks. In this period, they managed their actual problems and ideas using IdeaManager and managed other information using iBox.

In order to have subjects store their personal information in advance, iBox was distributed two months before the start of the experiment. At the

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start of the experiment, the average number of pieces of information they had stored was 363.8. The contents of the information were reading notes, papers, research notes, methodologies of programming or computer setup, their diaries, schedules, and so on. Subjects were not forced to store any specific kind of information in iBox, but they were instructed to manage their actual problems and ideas using IdeaManager. The qualitative level of the problems or ideas was not restricted.

There are six conditions for the pop-up search mechanisms (three for similarity and two for users’familiarity). The system changed pop-up search mechanisms every week exactly from the start of the experiment. In this as-signment, we noted that search mechanisms differed among all subjects in the first week, and effects caused by the order of search mechanisms were removed from the whole experiment. Subjects did not know the algorithms of pop-up searches, but they were notified that search mechanisms changed every week so as to avoid positive or negative biases of previous search mechanisms.

§

4

Experimental Results and Discussion

We gathered three types of experimental data: action logs that the system recorded, answers to questionnaires, and retrospective protocol data for pop-up searches. In this section, we analyze these data.

4.1

Analysis of Action Logs

In the experiment, the systems kept action logs of searches (including pop-up search), referencing of information, and so on. Because the action logs did not include any textual information that subjects edited, subjects’privacy was protected and we can assume that it did not affect the subjects’behavior.

[ 1 ] Use of the System

One of the purposes of this experiment was to investigate subjects’be-havior to the pop-up search. Because the registering or updating of information drives the pop-up search, it is necessary to note the frequency of these types of actions. Table 1 shows the total number of registrations and updates for the entire group of subjects. Subjects registered 399 pieces of information in iBox and also registered 97 problems, 89 ideas, and 55 pieces of related information in IdeaManager. This means that during the six-week period, on average, one subject registered 66.5 pieces of information in iBox, and also registered 16.2 problems, 14.8 ideas, and 9.2 pieces of related information in IdeaManager. We

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can say that our system was used frequently in subjects’actual activities.

Table 1 The number of register and update.

Register Update Total

iBox 399 1,503 1,902

IdeaManager Problems 97 208 305 704 Ideas 89 238 327 Related Information 55 17 72

[ 2 ] References of Information

In order to investigate the conditions under which subjects referred to ”popped-up” information, we look at the ratio of the numbers of information referred to, to the numbers of information retrieved by the pop-up search. We call this the reference ratio for the pop-up search. Although the reference to popped up information did not always bring about idea-generation, its evaluation is meaningful for the following two reasons. First, having access to information is an essential condition for stimulating thinking processes and generating ideas. Second, having access to information enhances familiarity with the information and raises the possibility of future idea-generation even if they could not generate ideas at that time. Table 2 shows the reference ratio according to the pop-up search mechanisms.

Table 2 The reference ratio according to pop-up search mechanisms. In each cell of the table, an upper value shows the reference ratio for pop-up searches driven by iBox, and a lower value shows the reference ratio for pop-up searches driven by IdeaManager.

Users’ Familiarlity Total Old Recent Similarity High - 45/51 45/51 (88%) 11/125 0/4 11/129 (9%) Middle - 31/43 31/43 (72%) 18/61 0/41 18/102 (18%) Low 1/1 28/46 29/47 (62%) 6/46 1/25 7/71 (10%) Total 1/1 (100%) 104/140 (74%) 105/141 (74%) 35/232 (15%) 1/70 (1%) 36/302 (12%)

Based on Pearson’sχ2 test, the following differences are significant.

In the pop-up search driven by IdeaManager, the reference ratio of the old condition was higher than that of recent condition (p < .005).

In the pop-up search driven by iBox, the reference ratio of the high-similarity condition was higher than that of middle-high-similarity condition

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(p < .05).

In the pop-up search driven by IdeaManager, the reference ratio of the middle-similarity condition was higher than that of high-similarity con-dition (p < .05).

The first result shows subjects’preferences for old conditions over recent con-ditions. From the viewpoint to derive the recency effect in idea-generation, it is unnecessary to present information that is already well known to users. Moreover, from the viewpoint to derive the clue-dependency of non-intentional idea-generation, it would be ineffective to present recent information, because well-known recent information would not be consulted.

The second set of results shows that subjects preferred high-similarity conditions to middle-similarity in the pop-up search driven by iBox. The third re-sult shows that subjects preferred middle-similarity conditions to high-similarity in pop-up search driven by IdeaManager. This indicates that the system should pop up problems or ideas with high-similarity for non-intentional idea-generation, and it should pop up related information without high-similarity for intentional idea-generation.

We think these results provide us with important information for the design of thinking support systems.

4.2

Analysis of User Reports

We now look at user reports in a post-experiment questionnaire. As for IdeaManager, subjects reported that they ”felt relief because they could leave the management of problems and ideas to IdeaManager” and ”got accustomed to describing what the problem was.” Subjects also described that they ”were sometimes confused about whether to register information in Idea-Manager or in iBox and whether they would register information in IdeaIdea-Manager as a problem or an idea.” Because people may forget spontaneous problems or ideas easily, it is necessary for the user to be able to register them without hesi-tation. IdeaManager should therefore be able to store information immediately and modify the classification later if need be. As for iBox, there were some user requests to expand its facilities, but no negative reports were given.

Regarding cooperation between IdeaManager and iBox, subjects re-ported that they ”could remember forgotten information” and ”could broaden their explorative fields of thinking using retrieved information.” However, sub-jects also reported that ”though there were a few cases when the pop-up search

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operated effectively, the ratio of those cases was low.”

4.3

Analysis of Behavior for the Pop-up Search

There were both positive and negative user reports for the pop-up search. In order to investigate for what kinds of activities our approach was effective, we analyzed users’behavior toward the pop-up searches. Two of the subjects (P2and P5) were selected and asked to report ”what they were doing at that time” and ”what they were thinking at that time.” The reasons why they were selected are as follows: (1)P5registered most problems and ideas (25 and 32 respectively) and P2registered the second most (29 and 14 respectively); (2) they both were in similar activity phases, that is they were summarizing their research and writing a masters thesis; and (3)P5reported that pop-up searches were totally effective whileP2reported that they were ineffective. Because this retrospective reports were carried out sometime after the experiment, they might have forgotten or revised their memory.4)To prevent forgetting, we reconstructed their behavior using action logs as a memory aid. To prevent memory revision, we instructed them not to force themselves to recall what they could not remem-ber with certainty. Using this reconstruction of their behavior, they reported that they recalled more than they had expected.

Protocol data for P2’s 23 pop-up searches and P5’s 59 were collected. The two subjects were asked to submit the contents of their problems and ideas to a degree that would not infringe on their privacy. P2submitted all problems and ideas and P5submitted 23 problems and all 32 ideas. We analyzed their behavior toward the pop-up searches using the protocol data, the contents of the problems and ideas, and action logs. We show some typical examples of their behavior in Table 3.

Cases 1 to 3 are examples that pop-up searches could not operate effec-tively. From these cases, we found the following.

The system should not repeatedly pop up the same information (Case 1).

There are kinds of information that a person simply wants to register and does not want to reflect on (Case 2 and Case 3).

Case 5 and Case 6 are examples in which the pop-up searches could operate effectively. Common features among the two cases are as follows: while thinking about his research, papers that the subject had read before and for-got were searched; their contents were reflected to his OHP slide or masters thesis. Also, in his user reports,P5reported the ”pop-up search was effective

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Table 3 Examples of subjects’ behavior for the pop-up search.

No. Sub. Registration Ref. Behavior for the pop-up search 1 P2 Research note

in iBox

No Problem that had been retrieved many times was searched and he felt troblesome.

2 P2 Mail on re-search in iBox

No He simply wanted to register a mail in iBox for retention and did not intend to refer the results.

3 P5 Diary in iBox No He was writing a diary as a pastime and did not intend to refer the results.

4 P5 Idea on his presentation in IdeaManager

Yes Paper that he read before and forgot was searched. He read it and rewrote his OHP slide using its technical terms.

5 P5 Problem on evaluation for his research in IdeaManager

Yes Paper that he read before was searched and he linked it to the problem. Since around then, he referred the paper many times and its con-tents was reflected in his masters thesis.

for the refinement of his research framework and he applied his thoughts to his masters thesis.” In actuality, among his ideas, there were many on the topic of his research (at least 30 of all 32 ideas) and on his paper (at least 19), such as the characteristic of his research, the relation of his research to others, the explanation of his research paradigm, and so on.

In this experiment, there were some cases in which the pop-up search operated particularly effectively. Those are the cases in which bringing up ma-terial was useful for writing or selecting terms and expressions. Observing those cases, we can say that the system worked effectively at least in the users’writing process or in explaining research activity. Generally, in writing tasks, authors of-ten need to use source materials.12)To explain their research exactly and plainly, they must select appropriate terms and expressions that refer to other papers. To clarify the characteristic of one’s research, they must compare and refer to prior research. Moreover, they are often looking for terms useful for their writing even when they are not explicitly engaged in writing tasks. In such situations, they often find relevant information accidentally from books or conversation. The ex-perimental result shows that our approach was effective in such processes, that is, in processes of bringing up resource materials for writing or selecting terms and expressions in their daily activities.

§

5

Related Work

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activ-ities. This system stocks research notes with scanner. It has a function to deal with indices edited by users and present the spatial configuration of notes according to their similarity. The objective of this system is to trigger users’ memories by contrasting them with the current context. This system supports long-term creative thinking, and its concept is most similar to ours. However, it can only use research notes to trigger idea-generation and only support inten-tional idea-generation.

We cannot foresee when and where idea-generation will occur. To sup-port such situations, some personal information storage systems have been im-plemented on Personal Digital Assistant (for example Dynomite18)). Using these systems, users can easily store a spontaneous idea. However, these systems do not have the facilities to support idea-generation. They just support the input of generated ideas.

XLibris proposed by Schilit et al.14) supports online reading with free form digital ink annotations. It has the capacity to present related documents when readers mark up a part of a document. Its aim is to provide serendipitous access to information, as when people find an interesting book accidentally in a library. Its facility is similar to ours in its effort to present information related to what users are paying attention to. However, information presented in XLibris is not related to users’problem or ideas, and its aim is not to generate or enhance ideas.

To sum up, prior systems support only intentional idea-generation or the input of ideas. Also, they do not support reconsideration and elaboration of problems or ideas. Although each element of technology utilized in our system is not original, we believe that the framework to support non-intentional idea-generation with a cooperating information management system is significant.

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6

Conclusions

In this paper, we claim that long-term support is necessary for creative thinking in daily life. Toward this aim, we have built a system that cooperates with a personal information management system. Its main aim is to support reconsideration and elaboration of users’problems and ideas in daily life, espe-cially for non-intentional idea-generation in information management activities. To evaluate our system, we carried out a six-week experiment. In this experi-ment, we were able to gain interesting suggestions to improve our system. First, in the pop-up search, we found that the system should pop up information that

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had not been referred to recently. Second, IdeaManager should be integrated into iBox from the viewpoint of user interface. Third, there were a few cases in which our approach operated effectively for processes of bringing up material for writing or selecting terms and expressions.

Currently the authors are improving the system and are going to apply its framework to idea-generation in long-term writing processes.

Acknowledgement

Our system is implemented using the search engine of Albase implemented in Fuji Xerox Co., Ltd. We would especially like to thank Yoshifumi Matsunaga for his quick and warm-hearted response and Eiji Ishida for the technical help of Albase. We thank Kengo Omura of Fuji Xerox Co., Ltd. for his important suggestions on this research. Finally, we thank anonymous referees for constructive comments on earlier version of this paper.

References

1) Aihara, K. and Hori, K.: Enhancing creativity through reorganising men-tal space concealed in a research notes stack, Knowledge-Based Systems, 11, pp. 469-478, 1998.

2) Altshuller, G.: 40 principles: TRIZ keys to technical innovation, Technical Innovation Center, Inc., 1997.

3) Boden, M.: The creative mind, Basic Books, 1991.

4) Ericsson, K. A. and Simon, H. A.: Protocol analysis: Verbal reports as data, Cambridge, MA, MIT Press, 1993.

5) Fischer, G. and Ostwald, J.: Knowledge management: Problems, promises, realities, and challenges, IEEE Intelligent systems, 16, 1, pp. 60-72, 2001.

6) Finke, R. A., Ward, T. B., and Smith, S. M.: Creative cognition, The MIT Press, 1992.

7) Gardner, H.: Creating minds, Basic Books, 1993.

8) Harris, J. E.: Remembering to do things: A forgotten topic, in J. E. Harris and P. E. Morris (Eds.),Everyday memory, action and absent-mindedness, Academic Press, pp. 71-92, 1984.

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9) Hori, K.: A system for aiding creative concept formation,IEEE Transac-tions on Systems, Man, and Cybernetics, 24, 6, pp. 882-894, 1994.

10) Hori, K.: Toward the next-generation creativity support systems, in Pro-ceedings of JSAI AI Symposium, 1996.

11) Ishida, E.: A simple visualization system for long-term personal informa-tion storage, inProceedings of Visual 97, 1997.

12) O’Hara, K. P., Taylor, A., Newman, W., and Sellen, A. J.: Understand-ing the materiality of writUnderstand-ing from multiple sources, Journal of Human-Computer Studies, 56, 4, pp. 269-305, 2002.

13) Reeves, B. and Nass, C.: Perceptual bandwidth,Communications of the ACM, 43, 3, pp. 65-70, 2000.

14) Schilit, B. N., Golovchinsky, G., Price, M. N.: Beyond paper: Supporting active reading with free form digital ink annotations, in Proceedings of CHI ’98, 1998.

15) Shibata, H. and Hori, K.: An approach to support long-term creative thinking in everyday life, inProceedings of KES 2001, pp. 959-967, 2001.

16) Shibata, H. and Hori, K.: An approach to support long-term creative thinking and its feasibility,Lecture Notes in Computer Science, 2253, pp. 455-461, 2001.

17) Sugimoto, M. Hori, K., and Ohsuga, S.: A system for visualizing view-points and its application to intelligent activity support, IEEE Trans-actions on Systems, Man, and Cybernetics, Part C, 28, 1, pp. 124-136, 1998.

18) Wilcox, L. D., Schilit, B. N. and Sawhney, N. N.: Dynomite: A dynami-cally organized ink and audio notebook, inProceedings of CHI ’97, 1997.

References

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