Weak Information Structure for Human Information Sharing
Harumi Maeda, Masao Kajihara, Hidekazu Adachi
Atsushi Sawada Hideaki Takeda Toyoaki Nishida,

andGraduate School of Information Science
Nara Institute of Science and Technology
8916-5, Takayama, Ikoma, Nara 630-01, Japan
Phone: +81-7437-2-5265

Abstract

E-mail: harumi-m@is.aist-nara.ac.jp

This paper demonstrates the e ectiveness of
the weak information structure for human
information sharing. The weak information structure is an information representation which connects various information media
without de ning the semantics rigorously. Byleaving the interpretation of the semantics totacit human background knowledge, it becomescompact and robust. To investigate how e ective the weak information structure is in realworld problems, we test two cases and reportour results. (1) We have developed a systemcalled CM-2 which gathers and reorganizes information on the Internet. Concerning precision and recall rate, the results are between 68{
90%. (2) We have developed a system called InfoCommon which supports information sharing
in community. More than 50% of users answer
that the system is useful for getting information
they need.

1 Introduction

Fax: +81-7437-2-5269

World Wide Web has become popular for human information sharing on the Internet. As large-scale information resources on the Internet are increasing rapidly,
it becomes more and more dicult to obtain information we need. Although a number of search tools areavailable, there are few intelligent systems which help us
reorganize vast information obtained from the Internet.
We point out that this results from conceptual diversity
in HTML documents on WWW.
On the other hand, programming languages or knowledge representation such as rst-order logic or frames
have been used for computer information sharing. Unfortunately, these are so logically rigid that one must
spend tremendous amount of e orts on information acquisition. This defect forces too much on human e ort
and hence signi cantly hinders accumulation of a large
amount of useful information.
We investigate an intermediate information representation which is weaker than well-de ned knowledge representation for human information sharing.

Weak Information Structure

NaturalKnowledge
Hypertexts
Language
Representations
Images
Texts
Movies Sounds
various information media

Figure 1: The Weak Information Structure
In this paper, we propose that the weak information
structure is e ective for human information sharing. The

weak information structure is an information representation which connects a wide variety of information media
such as natural language texts, hypertexts and images
without de ning the semantics rigorously (Figure 1). By
leaving the interpretation of the semantics to tacit human background knowledge inherently shared with people, it becomes compact and robust. Moreover, the weak
information structure is easy to generate from raw datafor both of humans and computers, and therefore can reduce the cost of information acquisition and integration.
To investigate how e ective the weak information
structure is in real world problems, we test two cases
and report our results: (1) gathering and reorganizationof information on the Internet and (2) information sharing in community.
In what follows, rst we describe two cases of experiments and then make discussion.

2 Test Case 1: Information Gatheringand Reorganization on the Internet

It is dicult to nd relevant information from large-scale
information resources on the Internet. To integrate awide variety of diverse information on the Internet, wedeveloped a system called CM-21 : a system for information gathering and reorganization.
1\CM" stands for \Contextual Media" which stands for
our long term theoretical research goal.

2.2

CM- 2 information base
WWW
page

Experimentmanual input using editor

WWW Pages

captureJames F.Allen's Home Page

unify

weak informatin
structure
reorganize

Barbara Hayes-Roth's Home Page

knowledge
cycle

reorganize

reorganize
reorganize

Well-structured knowledge

Figure 2: Overview of CM-2
2.1 Overview of CM-2
CM-2 consists of a collection of information bases. Each
CM-2 information base is possessed by an individual per-son or a group and it consists of a collection of workspaces
and agents. Each workspace provides a particular view ofmultimedia information stored in the information base.
Each agent manipulates information tasks and interacts
with the user. The user or the agents can interact withother, or incorporate information from other kinds ofinformation sources connected to the Internet.
The basic entities of the weak information structure
in CM-2 are a unit which represents either a concept oran external datum, and an association which connects acollection of key concepts with a collection of units which
is normally reminded by the given keys.
CM-2 has following functions.

Weak Information Structure
James F.Allen

URCS Faculty Member

Ph.D.

TRAINS

Barbara Hayes-Rothhayes-roth@cs.stanford.edu

University ofJames Allen
Toronto University ofRochester
research interests

KSL
Affiliation/
Position

Knowledge Representaiotn andReasoning

Reasoning About Plans

E-mail Address

Adaptive
Intelligent
Systems
Project Leader

Senior Research
Scientist

CM-2 output

CM-2 generates units andassociations from various information sources (e.g.
HTML documents on WWW and newspaper databases)by using morphological analysis and heuristics and analyzing the structure of the documents.
Information Gathering

Information Uni cation

CM-2 uni es various asso-

ciations such as generated from WWW pages and those
constructed by humans into new information bases.

Uni ed information
bases often contain redundant or inconsistent information. Following functions help humans to edit and reorganize information bases. (1) Focus: to hide units which
are unrelated to selected units, (2) Neighbor Search: todisplay units which are related to selected units, (3) Path
Finding: to display relations between selected units, (4)Unit Search: to display selected units.
Information Reorganization

Information
Decomposition

CM-2 decomposes large information
bases into small pieces which are easy to handle.

Figure 3: Overview of Information Gathering and Reorganization in CM-2
We gave 100 WWW pages concerning AI researchers
to CM-2 for organizing AI directories. CM-2 extracted
units about 7 classes (researchers, projects, e-mail, topics, universities, departments and laboratories), and generated associations. CM-2 reorganized these units andassociations to display various lists according to user's
input.
The overview of the process is illustrated in Figure
3. The algorithm is quite simple; (1) to generate units
and associations by morphological analysis and analyzing HTML structure, (2) to identify class of the generated units using heuristics, (3) to unify units and associations using heuristics, and (4) to reorganize associations
by path- nding according to user's input.

Table 1: Result of Test Case 1
Test
Precision
RecallTest 1 (researcher)
90%
83%
Test 2 (project)
68%
73%
units 2 100 (%)
Precision: appropriate
generated units
appropriate units
Recall: units whichshould be extracted 2 100 (%)
and (2) to display projects' list (Test 2). From this experiment, we found that (1) the weak information structure is easy to generate from HTML documents and (2)reorganizing diverse information can be performed atreasonable rate (68{90%) for the rough algorithm. This
indicates that the use of the weak information structure
and users' background knowledge is e ective to extract
and reorganize information from WWW pages.

3 Test Case 2: Information Sharing in
Community
3.1

Overview of InfoCommon

Figure 4 shows an example result when a user input\reasoning",\researcher",\e-mail",\project" and \university". For example, researchers such as Adam Farquhar, Alon Levy, Edward Feigenbaum and James Allen
are extracted rst, because the word \reasoning" andtheir names are written near in WWW pages, and then
their related information is reorganized.
A summary of the results of two tests are shown in
Table 1: (1) to display researchers' list (Test 1) and (2)to display projects' list (Test 2). The results of Test 1(90% at precision rate, 83% at recall rate) are better
than those of Test2 (68% at precision rate, 73% at recallrate), because original WWW pages are persons' pages.
From these results, we found that (1) the weak information structure is easy to generate from HTML documents and (2) reorganizing diverse information can be
performed at reasonable rate for the rough algorithm byusing the weak information structure and users' background knowledge.

Not only formal information, but also informal information such as word-of-mouth information is importantto support information sharing in community. In order
to integrate heterogeneous information for information
sharing in community, we developed a shared card information system called InfoCommon. InfoCommon allows
seamless keyword-based access to a variety of information cards to create a shared information base.
We employed several design principles to facilitate information sharing in community. First, we try not to enforce anyone particular concept. Instead, we allow much
freedom in the usage of terms and the structure of shared
information and to incorporate useful information fromvarious viewpoints. Second, we make the information
space a single seamless space. This releases the userfrom working with a rigid menu. Third, we enable theuser to build a personal information space where he/she
can organize relatively small amounts of information as
desired[Nishida et al., 1995].
InfoCommon provides visual interface for retrieving
and sending information cards. Figure 6 shows a screen
image of InfoCommon. The relation between two information cards is displayed by a link. InfoCommon information base consists of (a) a knowledge base which links
keywords and information cards using the weak information structure and (b) an information card base as shownin Figure 7.
InfoCommon supports the following functions.

2.3 Summary

Content-based Information Retrieval

Figure 4: An Example Result of Information Reorganization in CM-2

To investigate how e ective the weak information structure is for gathering and reorganizing information on theInternet, we developed a system called CM-2 which gathers and reorganizes information from WWW pages. We
tested two cases: (1) to display researchers' list (Test 1)

Given a setof keywords, InfoCommon will respond with the set of
information cards connected to the keywords. The resultof retrieval is stored in the user's local information basewhere the user can re-arrange the collection of information cards, and add/remove nodes/links as desired.

Figure 6: Screen Image of InfoCommon

Figure 5: InfoCommon in Use
Information Sending (Posting News)

InfoCommon Information Base

InfoCom-

mon is built on a conventional News service. Users can
add information cards on their local information baseand send them to a News server.

PDA

Purpose The answers to the question \For what did
you used InfoCommon ?" is shown in Figure 8(a). 59%
used the system for information retrieval and 19% for
information sending including News, help desk and discussion. The reasons as to why InfoCommon was used
for News were described as follows: \Because keyword
search was easy and useful (14 persons)", \Because I
found interesting topics in InfoCommon(5 persons)" and\Because I had a question (4 persons)". We determined that InfoCommon added new facility to conventional News reader. Major reasons of the choice \didn't
use" were \slow information retrieval (8 persons)" and\I couldn't connect to the server (4 persons)". These
problems involve server response and so are easily xed.

Retrieval

InfoCommon
Server

3.2 Experiment

We evaluated the usefulness of InfoCommon at the ICMAS'96 (Second International Conference on Multiagent
Systems) Mobile Assistant Project, which is the world
rst experiment in applying mobile computing systems
to community support. 100 personal intelligent communicators with handy phones were loaned to conference
participants to actually try out the system. Figure 5 isa photo taken in the Nara Park where an excursion was
held, which shows how a user actually used InfoCommon.
InfoCommon information bases store static information such as abstracts of papers, session, local information and pro les to share information among participants.
The number of information retrievals was 351 and information sending was 32 in InfoCommon over the 5 day
period.
We analyzed how InfoCommon was used by examing
log les and questionnaires.

Knowledge Base

Information
Retrieval

Information Card Base

Information
Sending
Sending

User

RetrievalMonitoring
News
Sending

Session

Abstracts

ProfilesLocal

InfoCommon
Information
Volunteer

Figure 7: overview of InfoCommon
Answers to the question \For what topic did you
use InfoCommon" are displayed in Figure8(b).

Topic

The most frequent keyword input in information retrieval was \icstat"(Table2), a special keyword
to display statistics concerning frequently asked keywords and frequently discussed subjects. This result suggests that users used InfoCommon to know what otherpeople are interested in or what are hot before information retrieval or sending. We found that such statistics
are useful for sharing information among participants.
Statistics

50
40

30

30

20

20

10
10
0

0
Information Help Discussion News Others didn't use
RetrievalDesk

research presen-sight- restaurant people othertation seeing(a)Purpose(b)Topic
Figure 8: Purpose and TopicTable 2: Frequently Asked Keywords
ranking

keyword

1
2
3
4
5
6
7

icstatnara
fipa
keihannaagent
nishimurafoodranking

7
9
9
9
9
9

keywordlunch
banqueticsuggest
kamameshi
restaurant
shuttle

40

30

30

20

20

10

10

0

usefulnot
other
useful0

usefulnot
other
useful(a)information retrieval (b)discussion
Figure 11: Usefulness
periment to evaluate the usefulness of the system fordiscussion in the future.

7
6mean 5
4
3
2
1
0

3.3
0

2

4

mean ＝

6

8

10

12

14

16

18

20

22

24

o'clock
number of information retieval except for the persons involved in the project
days

Figure 9: Change of Search
Change of Search Figure 9 shows that InfoCommon
was used from evening to midnight. We analyze thatthe reasons are perhaps (1) people were busy during thedaytime, (2) information retrieval was not a very urgent
task, and (3) the system was slow.
Search Resultsne(Figure10(a)).

81% felt that the search results were

51% answered that they were satis edwith InfoCommon(Figure 10(b)).
Satisfaction

55% answered that InfoCommon was useful for getting the information they need. On the other
hand, only 26% answered that it was useful for discussion.
We feel that the period (5 days) was too short to form
the kind of community in which people create many active discussions. We need to conduct a longer-term exUsefulness

30

30

20

20

10

10
0

40

0
very
good

good moderate bad

very
bad

other
satisfied notsatisfied(a)Search Results(b)Satisfaction
Figure 10: Search Results and Satisfaction

Summary

We developed a shard card information system called
InfoCommon and evaluated it at the ICMAS'96 Mobile
Assistant Project. The following results indicate the system's usefulness for information sharing in community:(a) 51% of users were satis ed of the system, (b) 81%
felt search results were ne and (c) 55% answered thatthe system was useful for getting information they need.
We consider the results are supporting evidence of thee ectiveness of the weak information structure for information sharing in community.

4 Related Work and Discussion

CYC[Guha and Lenat, 1994] and ARPA Knowledge
Sharing E ort[Patil et al., 1992] have made a signi cant contribution in the sense they shed light on theimportance of knowledge and information sharing andthat they have presented a self-completed computationalmodel. Their approach orients computer information
sharing while our approach is for human information
sharing.
Our work is related to recent work on information
gathering from heterogeneous sources on the Internet ([Levy et al., 1994],[Armstrong et al., 1995],[Balabanovi'c and Shoham, 1995],[Li, 1995],[Iwazume et al.,1996]). Instead of focusing on the strategies and heuristics for information gathering, we concentrate on how toclassify information obtained from multiple information
sources and integrate it into personal information base.
Gaines uses semantic networks as information representation for group knowledge sharing[Gaines and Shaw,1994]. Our approach is based on much weaker information representation than semantic networks.
Kautz studied the use of agents in assisting and simplifying person-to-person communication for information
gathering tasks[Kautz et al., 1996]. They focus on theuse of a software agent. We concentrate on the processof how humans create knowledge and information.
Sumi, Hori[Sumi et al., 1992] and Kunifuji claim theimportance of knowledge and information in the eld ofcreative thinking support.
The basic recognition behind this research is a tradeo between the bene t from conceptually well-structured

information representation and the cost of informationacquisition and integration. The more well-structured
information representation becomes, the more useful it
is for computational manipulation, however, the more
expensive the cost of information acquisition and integration becomes for both of humans and computers.
Our approach is to provide a framework of collaborations for human information sharing with a low structural facilities.
The results of two test cases indicate that the weak information structure is e ective for (1) information gathering and reorganization on the Internet and (2) information sharing in community.
We found that human background knowledge can beutilized in human information sharing. In addition, we
also found that the weak information structure is easy togenerate from raw data for both of humans and computers, and can reduce the cost of information acquisition
and integration.

5 Conclusions

This paper demonstrated the e ectiveness of the weak
information structure for human information sharing.
The weak information structure is an information representation which connects various information media
without de ning the semantics rigorously. By leaving
the interpretation of the semantics to tacit human background knowledge, it becomes compact and robust. To
investigate how e ective the weak information structure
is in real world problems, we tested two cases and reported our results. (1) We developed a system called
CM-2 which gathers and reorganizes information on theInternet. Concerning precision and recall rate, the results were between 68{90%. (2) We developed a systemcalled InfoCommon which supports information sharing
in community. More than 50% of users answered thatthe system was useful for getting information they need.
As a future research, we plan to evaluate how people
actually create the weak information structure and how
people interpret the weak information structure createdby others.

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