Shifting ICT to ICA - Towards I nformation and C ommunication A ctivity N avigation -

Hideaki Takeda / National Institute of Informatics

Shifting ICT to ICA- Towards Information and Communication Activity Navigation -

Hideaki TakedaNational Institute of Informatics

&The Graduate University for Advanced Studies

[email protected]://www-kasm.nii.ac.jp/~takeda/


Table of Contents

NMM:Re-configuration of personal human network

Kmedia: Finding relationship via WWW bookmarks

TelMeA: Expressive Media for Online Communities

Community Navigator: Collaborative Scheduling Support System for Conferences

Social Scheduler: Collaborative Scheduler for Personal Resources

TelMeA for e-Kyoshitsu: Application to Distance Learning

Introduction: Shifting ICT to ICA

Our Research Topics

Summary

H. Takeda

Shifting ICT to ICA- Towards Information and Communication Activity Navigation -


From “old computing” to “new computing”“The old computing was about what computers could do; the new

computing is about what users can do. Successful technologies are those that are in harmony with users’ needs. They must support relationships and activities that enrich the users’ experiences.” Ben Shneiderman, Leonardo's Laptop: Human Needs and the New Computing Technologies, MIT Press, 2002

Paradigm shift is needed Technology-centered approach Human-centered approach


ART(Activity-Relationship-Table)

COLLECT(Information)

RELATE(Communication)

CREATE(Innovation)

DONATE(Dissemination)

Self

Family and friends(2-50 intimates)

Colleagues and neighbors(50-5,000 regular encounters)

Citizens and markets(5,000+)

Ben Shneiderman, Leonardo's Laptop: Human Needs and the New Computing Technologies, MIT Press, 2002


Communication Layer

RelateCollaborate

Present

　 Communication layer concerns potential information. Potential information 　　 can 　 be revealed through communication among people.

Information and Communication Activities Two layers for our activities

Create

Information Layer

Collect Donate

　 Information layer only concerns explicitly represented and processed 　 information.


Information Activities A cycle of information exploitation

Collect Find and retrieve information

Create Process (classify, extract, combine, mix, …) information Generate new information

Donate Publish and distribute information

Create

Information Layer

Collect Donate


Communication Layer

RelateCollaborate

Present

Communication Activities A cycle of human relationship exploitation

Relate Find and contact people

Collaborate Work with other people (organized work, teamwork, cooperation, …)

Present Identify and contribute ourselves to communities


RelateCollaborate

Present

Information and Communication Activity Navigation (ICAN)

Support by computers for six categories of ICA

CreateCollect Donate

NMM:Re-configuration of personal human network

Kmedia: Finding relationship via WWW bookmarks

TelMeA: Expressive Media for Online Communities

Community Navigator: Collaborative Scheduling Support System for Conferences

Social Scheduler: Collaborative Scheduler for Personal Resources

TelMeA for e-kyoshitsu

H. Takeda, M. Hamasaki, T. Matsuzuka, Y. Taniguchi

Discovery of Shared Topics Networks among People

A Simple Approach to Find Community Knowledge from WWW Bookmarks


Purpose Generation of human network guiding individual information

activities An example

I want to watch sports programs on TV. What your recommendation?

Who and What Shared Topics Network among Users (STN)


Bookmarks as Knowledge

A bookmark folder= A topic interested by the user

URLs in a bookmark folder= Examples of the topic

21

4 3e

a b

f c

dz

x

User

y

WWW page (information on the topic)

Folder (topic)

Bookmark (person’s interest)

5

g Shared Topics Network


A

C

B

Discovery of topic relations

computer-relatedresearch-related

search

Informationretrieval

academia

Common relations (search, IR), (academia, research-related) similar but words themselves are different

Un-common relations …(Unix, academia)

Speciality of thecommunity


A

C

B

Discovery of relationship among people

computer-relatedresearch-related

search

Informationretrieval

academia

What are common topics with others? Who is good at this topic?

unix

research

research


Category Resemblance (1)Categorization Is Human Relation?

Human relation can be measured by resemblance of folder structure

Folder structure is similar Not similar

Cij =Nfij × Rfij

NpijCij : Category resemblanceNfij : No. of recommended folders Rfij : Folder relevanceNpij : No. of recommended pages


Better page recommendation results for new group made from category resemblance (CR)

22.12.22.32.42.52.62.72.8

In-community

Cross-community

New groups

All

Page RecommendationScore

Effects of Category Resemblance (4) for Page Recommendation


Summary Proposal of shared topic network to enhance user’s

communication Proposal of algorithm of discovery of shared topic networks with

WWW bookmark files Validity of our approach by an experiment Proposal of category resemblance as measurement for community

effects

M. Hamasaki, H. Takeda

Re-configuration of personal networks by the neighborhood matchmaker method


Purpose Personal network is usually “ad hoc”

We may miss better friends nearby We need better network One Solution:

Collect data for all people, then generate the “best” networkDisadvantage:

Scalability Privacy

Our approach: Neighborhood Matchmaker Method (NMM)


Neighborhood Matchmaker Method (NMM)

A iterative approach to optimize the network Every node works as a matchmaker for neighborhood nodes to

improve the network The basic idea

In our real life, introducing new friends by the current friends is a practical way to optimize personal networks

We can know persons who you have not known before Your friend can filter people for you

Advantages No need for central servers Applicable to any size of community Less computational cost


Algorithm 1. A node calculates connection values between its neighbor nodes

We call that node “matchmaker” 2. If the matchmaker finds a pair of nodes which has a good enough connection

value, it selects this pair for recommendation. The matchmaker introduces both nodes of recommended pair to each other

3. The node that receives recommendation decides whether it accepts or not. If it accepts, it adds a path to the recommended node

!?

Calculating connection values

matchmaker

matchmakerGood !!

Introducing each nodes

OKOK

Adding a new path

matchmaker


Results: Cover-Rate w.r.t. Nodes The path size is fixed as three times as the node size All cases were converged The average of cover-rate and the turn of convergence vary with the node size

00.10.20.30.40.50.60.70.80.9

1

0 50 100 150 200 250 300 350 400 450 500

20node40node60node80node100node

Cov

er-R

ate

Turn

100node

80node

20node

40node

60node


Results: Average of Convergence Turn The number of convergence turn is linearly increased with the

node size Computational cost

NMM: O(N) Central Server Model: O(N2)

0

100

200

300

400

500

600

10 20 30 40 50 60 70 80 90 100

1p/node2p/node3p/node4p/node5p/node

Con

verg

ence

Tur

n

The node size

1path/node

5path/node

2path/node

4path/node

3path/node


Conclusion Proposal of optimization of “ad hoc” network Good news for the Internet communities

No need for central servers Applicable to any size of community Anytime Algorithm

H. Takeda, M. HamasakiIn cooperation with Yutaka Matsuo and Takuichi Nishimura

Community Navigator:Collaborative Scheduling Support System for Conferences


Purpose System Aim: Support people to find their friends in a specific group Research Theme: Investigate different human networks in the same group Three human networks

Human network in the activity: I worked with him Human network by communication: I know him Human network by behavior: I meet him

Scheduling on conferences Plan and Action

“I know him”“I worked with him” “I meet him”

Planning action


System Functions Easy-to-use scheduling system for the conference

Just add presentations what you want to watch Can refer schedules of other people

Manually collaborative scheduling Can only see schedules of who know you

Can recommend schedules collaborative scheduling

On-site support of schedules Small communication device with sensors

Takuichi Nishimura, Hideo Itoh, Yoshinobu Yamamoto and Hideyuki Nakashima. ``A compact battery-less information terminal (CoBIT) for location-based support systems," In Proceeding of SPIE, number 4863B-12, 2002.

Cobit


Outlook


Recommendation Recommendation by pattern similarity

Naïve collaborative filtering Paper recommendation Person recommendation

Recommendation by personal networkReply on selection by friends Paper recommendation Person recommendation

Paper1

Paper2

Paper3

Paper4

Paper5

Person A 1 0 1 1 1Person B 0 1 0 1 0Person C 1 1 1 1 0Person D 0 0 1 1 1


Recommendation

Ikki Ohmukai, H. Takeda

Social Scheduler: Collaborative Personal Task Scheduler



Mobile Task Scheduler for Daily Life Everyone belongs several groups and communities Some groups were built emergently and have ambiguous

boundaries No one cannot manage “my” schedule

Collaborative Model of Personal Scheduling Based on information sharing with one’s friends Access control and filtering according to each group Cell-phone application


Social SchedulerCollaborative Personal Task Scheduler

Create friends network by authorization Task conditions become viewable and updatable by each other

Server merges all friends network into alliance network The system considers partial complete graphs as emerging gro

ups (unit of information sharing/filtering)



Experiment12 subjects from various

communities3 weeks in use41.9 tasks/person76 collaborative tasks

Social NetworkThe system can find multiple

communities around the user

Distance of each friend can be measured by the number of groups they share

Toru Takahashi, Yasuhiro Katagiri, H. Takeda

TelMeAShow Me What You Mean -

Expressive Media for Online Communities


TelMeA2002


Conversation Process in TelMeA2002

3. The massage is accumulated in the conversation log

Personified Media

Participant of a TelMeA Community

2. Submit the message to the community server

Hello!

Other Participants of the Community

6. The message is asynchronously enacted

1. Edit a message in terms of a script language

EditorScreen Shot of TelMeA2003

4. Request for seeing the message from others

Conversation Log of the TelMeA Community

5. The required message is downloaded

Hello!


Our Goal

Find pragmatic rules of social and nonverbal interactions Supporting social and nonverbal interactions Archiving the logs of long-term community activities Analyzing usages and effects of nonverbal expressivity

Make a model of multimodal social interaction Calculate social evaluations for involved information Summarize or make reutilize the involved information

Toru Takahashi, Yasuhiro Katagiri, H. Takeda

e-kyoshitu(e-classroom) Project


Trial Use: e- 教室 (e-classroom) Project e- 教室 (e-classroom) Project:

Run by NPO Distance learning for children (mainly junior-high school, 12-15y

rs) Several classrooms (math, economics, CG, etc)

TelMeA for e- 教室 Experimental use of TelMeA Classroom for

Leaning “agent” as new technologies by usingCommunicating to each other (“BBS” for participants)

(demo)


TelMeA for e- 教室


The current status of “TelMeA for e- 教室” Period: c.a. 4 month (2003.1.16-) Login users: 64 Posted users: 24 Post No.: 297, Post thread No.: 22


Summary Information technologies, in particular AI can offer new

opportunities for communities Reducing constraints of the real world

Time, space, etc new communication ways

Knowing new related people, communication via agents etc They will change meaning or roles of communities

e.g, Very weak communitiesQuick life cycle of communitiesBelonging so many communities


Summary Challenges

Support of life cycle of communitiesCreate, maintain, diverse, merge, disappear

TrustTrust is very difficult Trust may be more complicated than the real world…

Documents

Shifting ICT to ICA - Towards I nformation and C ommunication A ctivity N avigation -