YOKAN TABLE

Intermediary System between Notables and People

Kazuya Fujisawa, Ryutaro Motora

Graduate School of Media and Governance, Keio University, Minato, Tokyo, Japan

Michiaki Yasumura

Faculty of Environment and Information studies, Keio University, Minato, Tokyo, Japan

Keywords:

Microblog, Notables, Event extraction, Talkshow, Lecture.

Abstract:

There are a lot of people who want to meet active notables by whom he or she may obtain the chance of as a

human being. Currently, the informations to meet notables are scattered in various places on the Web, and we

have to view the Web pages either from news sites, word of mouth sites, blog sites, etc. to look for necessary

information. However it is troublesome to view the web pages carefully everyday, and it is a problem to

overlook the important information. In this study, we aim to make a lot of chances to meet notable people.

In order to collect and analysis the information of notables appearance that scattered on the web are collected

and analysis, we developed a system called YOKAN (presage) table with the function of notiﬁcation of newly

arriving information on physical table.

1 INTRODUCTION

We are looking for the chance of growthing every day.

Especially, meeting notables is the best opportunity

because it brings not only knowledge and knowhow

but also a lot of inspiration. Currently, there is a lot of

information to meet notables like the notiﬁcation of

the talk events etc. But then is no much, we have to

view the Web page of the news sites, blog sites. More-

over we also need to look for necessary information

carefully, and it is a problem that we often overlook

the information. In addition, we should always check

the newly arrived information. It is difﬁcult to search-

ing an interesting notable daily, and checking the site

carefully everyday.

Therefore, we’d like to design and implement the

Web service called Yokan (presage) table that collects

notable’s appearance information. In this study, we

aim to make a lot of chance to meet notable people.

We designed and implemented Yokan talble.

2 YOKAN TABLE

The Yokan table is a systems that notiﬁes newly arriv-

ing information on physical table. In this research, we

deﬁned the design policy that people can collect in-

formation everyday without the stress, and can keep

user continuously access system. Hereafter, we ex-

plain the function of the Web part and the table part

of the system.

2.1 Web Part of the System

In this study, we focused on the talk event as a good

opportunity to meet a notable. The talk show and lec-

ture meeting informations that indicated in the future

are collected from web automatically. We deﬁned fu-

ture information is within three months. We utilized

the Twitter that display the information in time line

(Figure 1).

User’s judgment index, includes not only essential

information of (1) the date of talk-events (2) the no-

table name (2) and (3) talk-events name, but also (4)

informationof notable specialized ﬁeld and (5) degree

of attention are displayed in addition. Information is

updated every 24 hours.

2.2 Physical Table Part of the System

The purpose of the table part is to induce the user

from daily life to the Web page (Figure 2). And it

197

Fujisawa K., Motora R. and Yasumura M. (2011).

YOKAN TABLE - An Intermediary System between Notables and People.

In Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems, pages 197-200

DOI: 10.5220/0003366601970200

 SciTePress

Figure 1: Screenshot of Web service.

Figure 2: Yokan Table appearance.

informs the sense that comes close to famous people.

In this study, using metaphor that a surrounding thing

vibrated because of the rumbling of the earth when

the massive creature moved. Desktop coaster part

is prepared, and the glass of water will shake glass.

The size of the shake changes depending on degree

of attention of talk-event, and the color of the coaster

changes depending on notable specialized ﬁeld.

The users feels the scene that a notable ap-

proached on the YOKAN table in breakfast and din-

ner, and checking detailed information on the Web

service before going to school, commuting, and break

time.

3 IMPLEMENTATION

This chapter describes implementation of the soft-

ware and the hardware of the YOKAN table.

3.1 The Software

To obtain talk-event information of notables, Twitter

of the microblog service was used. It explains that

semantics step of the system as follows (Figure 3).

1. First of all, by using ”Twitter search API” that

Twitter offers, the comment that is called ”tweet”

where the keyword ”talk-show” or ”lecture” in-

cluded is acquired. These data is brought together

every day, and it processes day by day.

2. Next, to make the quote comment that is called

”retweet” and ”tweet” of the similar content

group, the vector space model is applied to the

similarity calculation of ”in one tweet” and ”an-

other tweet”. To make the feature vector of each

”tweet”, the morphological analysis is done to

each ”tweet”, and elements count of feature vec-

tor is composed of the number of all noun, each

elements weight is composed of the count of the

corresponding noun.

3. For the similarity calculation, using cosine simi-

larity. The cosine similarity of feature vector X

and feature vector Y is calculated in expression

(1). Merge of ”tweet” is done by using the short-

est distance method of a hierarchical clustering,

and merge is repeated until cosine similarity be-

come under the sub threshold. When clustering is

ﬁnished, each cluster becomes one event.

sim(X, Y) =

−→

X ·

−→

|X| ·

−→

|Y|

∑

(1)

Weight of element

of feature vector X

Weight of element

of feature vector Y

4. Finally, name of person, the person’s category and

events name have been extracted from each event

information. The morphological analysis is done

to each event information. When the combination

of last name and ﬁrst name existed, it extracted

as a name of person. Person’s tag information is

extracted from person search engine ”Fined him

in SPYSEE” (http://spysee.jp/), and the person’s

category is decided from tag information by the

rule that the system decided beforehand. By the

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HTTP access to URL that exists in event informa-

tion, contents of the Title tag in the HTML source

has been extracted as an event name.

3.2 The Hardware

Figure 3 showed the structure of hardware. The

hardware of the YOKAN table used a wooden table

(100mm x 70mm x 70mm) on the market. To keep

space that built in the mechanism internally, the top

board with space was added. And space that holds

the mechanism internally was secured. we used the

DC solenoid (12V) and the 3M Co. pocket projector

(MPro120), for shaking mechanism and for color pro-

jection mechanism respectively. For we used Arduino

to detect the glass on the coaster. And the system also

controls the DC solenoid and projection color.

Figure 3: System conﬁguration diagram.

4 DISCUSSION

We found that more than 90% is next three month

information in the extracted information. Because

Figure 4: Hardware conﬁguration diagram and structure.

this future information often contains URL, an ofﬁcial

Web site of talk-events information can be acquired.

As a result, it has been understood to obtain useful

information by focused on at the date.

Recently, the weight of the feature vector uses

only the number of the nouns, so we have to examine

weight. Moreover, the threshold of the cosine simi-

larity of clustering is set to ”0.5”. But after a detailed

experiment is done, it is necessary to ﬁx this thresh-

old.

From now on, we will explain comparative exper-

iments on the data acquired from micro blog and gen-

eral search engine, and experiment on utility using a

lot of data and examinee.

5 RELATED WORKS

It remarkable that the number of Twitter user is 11

milion in Japan on November, 2010. Because a lot

of services that focused on event informations and re-

searches that using information on the micro blog ex-

ists, and we introduces them in this chapter.

There are some researches that regard each user

who sends information from microblog as one sen-

sor (Fujisawa, 2010). That means regard Micro blog

as network service observes real space, and it tries to

understand various events that occur by a real space

from the sensing from the user. Those analyses are

used the user’s location information and the remark

time as index. This research is same as our study

about focus on event informations. But our study fo-

cuses on not user’s location informations and post-

ing time, but date informations of ”Tweet” to extract

event informations.

Web service called ”KOTOSAGA” that helps to

see event informations (http://www.cotosaga.com/).

It uses the crawler of original development, and it

collects event informations automatically from more

YOKAN TABLE - An Intermediary System between Notables and People

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than 700 event informations sites. ”KOTOSAGA” is

based on the element of ”date” and ”place”, so we

can also know information around the event hall, for

example, weather, map etc.

6 CONCLUSIONS

In this study, we aim try to give chance for people who

want to meet notable. For this purpose our system

called Yokan Table that collects notable’s event infor-

mation. And the Yokan table that notify newly arrived

information on desktop glass was designed and im-

plemented. Usually, to meet notable, we should view

the Web page from the news site, by word of mouth

site, site of notable himself etc. Moreover we also

need to look for necessary information carefully, and

it is the problem that we often overlook the informa-

tion. Because Yokan table installed the entrance to

web in daily life, users can obtain the chance meeting

notable more comfortably. In the future, we want to

aim at personalizing to offer information matched to

user’s interest.

REFERENCES

T. Fujisaka, R. Lee, K. Sumiya 2010. Estimating Inﬂuence

Regions of Social Events by Geo-tagged Micro-Blogs

Analysis, DEIM Forum 2010 D7-4.

KOTOSAGA. http://www.cotosaga.com/

SPYSEE. http://spysee.jp/

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