An Automatic Document Coloring and Browsing System
Tomoyuki UCHIDA and Hidehiko TANAKA
abPresident, Yun Factory Corporation, 7-17-10 Koyama Shinagawa-ku, Tokyo, 142 Japanemail:tomo@yun.co.jpaDepartment of Electrical Engineering, Faculty of Engineering, The University of Tokyo,
7{3{1 Hongo Bunkyo-ku, Tokyo, 113 Japan email:tanaka@mtl.t.u-tokyo.ac.jpb1INTRODUCTION

In recent years, the number of online documents, for example WWW, has increased. Nevertheless they are still expressed in traditional black-and-white. Color devices such as color
CRT are available, and document expressions which make full use of this chromatic faculty is in great demand[1]. We will study e ective coloring of documents to increase theirlegibility and understandability.
The diculty of making the most of the good e ects is due to its complicated side e ects
such as unpleasant feeling, distraction and individual variation[2]. Previous researches tend
to consider only on gaudy primary colors and on xed devices such as paper. But there
are quiet colors and dynamic devices which can change coloration, and there is still muchto investigate on document coloring.
Thus we measured by experiment the in uence of color given to a reader, and studied
the way to make the most of colored documents. And nally we developed an automaticJapanese document coloring and browsing system (named CERAS) was developed. Froman estimation experiment, CERAS improved the speed and accuracy of reading.
2

COLOR EFFECT

There are various psychological e ects of using colors[1]. First of all, color can express up
to millions of attributes human can distinguish. Especially a phenomenon called pop-outthat can discover the stimulus of a purpose in a glance from within a plural stimulus isvery e ective. Next, color can bring the sense of warmness, size, distance and weight.
Besides that, color brings feelings such as beauty and joy, as it is now acknowledged in theadvertisement eld. If the e ects of these colors are used e ectively, it will be expectedthat a reader can get the outline of a document faster and understand the content of adocument further and enjoy reading more.
In our experiments, coloring promotes understanding and remembering the content ofa document.
The coloring rules are established taking into the advantages and side e ects. But itis dicult to construct only one coloring rule that always extracts maximum e ect in allstyles of documents, reader's attitudes and purposes. For that reason, it is more desirable
that a document browser selects best coloring rules dynamically.

3

AUTOMATIC COLORING SYSTEM `CERAS'

We developed a colored text browsing system named CERAS. This system gives color to
an input plain text and displays it on a computer CRT. Users can customize the coloringrules and tune the expression interactively by a GUI. Document processing is implemented
on a UNIX workstation, and GUI on a Windows95 PC.
Morpheme analysis is carried out to sentences in the text, and coloring points; type ofcharacter, part of speech and keywords, are extracted. CERAS gives color expressions toextracted points considering the reader's customize information and feedback informationfrom the GUI. The browser image is shown in Figure 1. It displays a colored text in a bigwindow. Operation is carried out by mouse.
A \Pi menu" is used as a GUI to input user customize coloring information and to tune
the color expression interactively in the system. Pi menu shown in Figure 2 is displayed
on top of the text screen centering around the mouse pointer, when the left button of
the mouse is clicked. The user moves the mouse pushing the button to the direction of amenu button and selects a function. The tuning expression is assigned to the rst layerof the Pi menu. Customizing is assigned to the second and third layer. For example thebottom menu button of the rst layer is assigned to weaken the expression. Therefore if
this button is kept selected, the expression becomes more quiet and ends as a black-andwhite expression. The top button is assigned to strengthen the expression and makes theexpression gaudy.

Figure 2: Feedback GUI \Pi menu".
Figure 1: Appearance of the colored text browser.

CERAS acts in either General coloration mode or Speci c coloration mode. In Generalcoloration mode, documents are colored by general features, such as type of character andpart of speech. Speci c coloration mode is used when a user has a speci c point to read,and the user can enter this mode anytime, to specify a keyword by clicking the right buttonof a mouse on it. In this mode, words related to the keyword are also colored by using
a thesaurus. The related words are expressed by the color whose strength is associatedwith the strength of the relation. The user can quickly nd out interesting parts within adocument.
4ESTIMATION OF CERAS

Keyword coloration function of CERAS was evaluated by a news article classi cation experiment.

A testee searches one or two designated descriptions inside a displayed document inspeed-reading and classi ed the document into two kinds.
First, a condition sentence is presented on the CRT to a testee, and the testee chooses
and clicks one word as a coloring keyword. Next, a news article of approximately 1,100
characters is presented on the CRT, and the testee classifes it and pushes either the rightor the left mouse button. Two patterns of combinations of colored and black-and-white
document are prepared and presented to a testee. In colored documents, keywords arecolored red and colored words are displayed in deep blue.
The number of testee is 14. Time required for a testee to click the mouse button fromthe presentation of condition sentence is measured. It is equal to the reading time inblack-and-white, because keyword is not designated in this case.
The time for choose a keyword and point it by moving the mouse is 601ms. This meansthat the overhead time for the utilization of interactive coloration function of CERAS is601ms.
Table 1: Average classi cation timemono(1target)

color(1)mono(2)color(2)

Match

12.86

3.936

10.37

4.048

Unmatch

16.47

3.675

15.98

6.647

Total(sec)

15.47

3.745

13.18

5.347

Next, the average classi cation time is shown on Table 1. The required time is reduced
to 24.2% by coloration in one target condition and to 40.6% in one of two targets condition.
And it costs less time to classify by coloration in all cases.
The correct answer rate is raised by coloration in 3 out of 4 cases. In total, it rises 5%
in one condition, 2% in two conditions.
There is a linear relationship between the location of a search goal inside an article
and classi cation time. Therefore we can estimate the reading speed according to thisrelationship. It can be said that there is a correlation between distance from the top of
an article to the search goal and classi cation time in the case of a black-and-white news
article, because a testee is apt to search the target from the top to the end.
The required time to read one content word is estimated 27.71ms and 31.22ms in one
condition and two conditions in the case of a black-and-white document. The time to checkaround a mark is 923.3ms for a keyword, and 123.6ms for a related word.
We consider that a user searches an unknown word which satis es a semantic target in
the related words.
There are n documents on the same condition. The number of keyword marks, related
word marks, content words from top to target are a, b and t.
According to the fact that the time required for semantic search costs 24.4% more thanlexical search[3], semantic search costs 123:6 1 1:244 = 153:8(ms) for each related word
marks. The overhead of coloring is 601 (ms). The average time required for searching in
the coloration documents is 601 + 923:3a + 153:8b + 3073 (ms).
In black-and-white document, we consider to 10% priming e ect additional to the above.
244 0 9It costs 462 3141 81= 34:95(ms) for each content words. Therefore, it takes 34:95t +2311(ms) to search the target.
For that reason, in the case under the following condition, CERAS is advantageous.
17:2+ 26:42a + 4:401b + 21:80
t >nn: 1 :1 ::n

0; a  0; b  0; n > 0
We tried to apply this condition to news articles using this experiment as an example.
The parameters are as following: a = 0:4500; b = 18:05; t = 355:4; n = 20
When b is free, the condition is b < 72:8. This means CERAS can use 72.8 related word
marks from the top to the target in average. It means 3.03 marks per line, too. In addition
that the limit value is 4 times as much as that in the present system.
In a news article speed-reading case, it is presumed that related word coloration ise ective for speed when the number of coloration marks are less than 3 per line on anaverage.
t >5CONCLUSION

The number of online documents and those who read documents on color devices is increasing very much. We estimated the e ect of coloring a document by experiment, anddeveloped CERAS which generates color expression automatically and responds quickly tothe user's customize and tuning request through a GUI.
In General coloration mode, CERAS presents colored expression which improves comprehension. And an user can customize its color and tune interactively while reading. In
Speci c coloration mode, CERAS has many advantages in fast-reading. Adding a special
feature makes it easy to search a keyword, which has generally been carried out in documentsearching area. But, there are no systems which can change keywords and expressions interactively nor give expressions to words related to the keywords. People frequently search
their interesting point when they read relatively less important documents such as news
paper articles. For that reason, raising eciency of this search is generally e ective. To
raise this eciency, it is e ective that a system adds a special feature to the interesting
point, and raises the search speed. CERAS accomplishes this in interactive keyword speci cation and coloration to keywords and related words. Coloration is suitable to speedup
a search utilizing its pop-out function. Moreover, interactively speci cation of keywords
interactively is considered e ective when the object of interest is changed while reading.
And there is the e ect of preventing the oversight of an interest point in relative wordcoloration. An user can nd an interest point which does not include the keyword but
its synonym. From an estimation experiment, CERAS is e ective for fast-reading of news
articles, both in time and in accuracy in Speci c coloration mode. And there is enoughmargin till a defect appears.
Still, there is room of precise estimation and examination, but this system has importantsigni cance as the tool that estimates the possibility of color expression of a document.
From now on, we will modify the system and establish a presentation method which will
increase the e ectiveness of colored documents.
References[1] William Winn,\Color in Document Design," IEEE Trans. Professional Commun., vol.34, no.3, pp.180-185, 1991.
[2] R. John Brockmann,\The Unbearable Distraction of Color," IEEE Trans. Professio
nal Commun., vol.34, no.3, pp.153-159, 1991.
[3] Ken Goryo,\What's reading," Tokyo Univ. Press, 1987.