Letters

Development of an Informationclassification System Based on Access Logs
Noriyuki Hayashi†, Keita Ooi, and Takeya Mukaigaito
Abstract
With the amount of information on the Internet continuing to increase rapidly as broadband and mobile
communication environments expand, information-classification technology is essential for retrieving
desired information efficiently from the wealth of information on the Internet. NTT Information Sharing Platform Laboratories is developing an information-classification system based on access logs. We
have developed a new Web browsing system called C-Chart using this information-classification technology. This enables Web browsing using information classification by C-Chart.

1. Need for information classification
In recent years, we have seen the rapid expansion of
the broadband environment through FTTH (fiber tothe home) and ADSL (asymmetric digital subscriberline) and of the mobile environment through cellular
phones equipped with i-mode and other Internetaccess systems. This development has helped produce a flood of information on the Internet, making iteven more difficult for users to access the information
they need.
To find information on the Internet, Web users use
search services like Google and Yahoo! or goo inJapan [1]. In services of this type, the user enters keywords related to the desired information and thenattempts to locate that information from among thelimited number of search results returned. However,
the amount of information on the Internet continues
to increase, and in the future, we can expect the number of search results to be huge. Thus, finding desired
information from all the results presented may takeconsiderable time, and one could fail to find thedesired information even after spending all that time(Fig. 1(a)).
Some Web sites, especially those involved with ecommerce, customize and present information foreach user as part of their services. Customization of† NTT Information Sharing Platform Laboratories
Musashino-shi, 180-8585 Japan
E-mail: hayashi.noriyuki@lab.ntt.co.jp

Vol. 2 No. 8 Aug. 2004

this kind, however, faces potential problems. For
example, as the number of users and amount of information increase, the processing required to customize
information for each user will likewise increase and it
may become impossible to display customized information in real time. In addition, realtime customization of information may even degrade service quality
and prevent optimal customization from beingachieved. In short, customization of user informationmay make it difficult to provide the service itself (Fig.
1(b)).
NTT Information Sharing Platform Laboratories
advocates information classification as an effectivemeans of solving the above issues. This is because
classifying the information in a huge number ofsearch results can make the information-selection
process more efficient. Information classification canalso benefit services that customize information foreach user. It can be used to classify users having similar interests, preferences, and behaviors into thesame category so that they can be processed together
as a group. This will eliminate the need for individualuser processing and reduce the computational load.
2. Information-classification technology based onaccess logs
NTT Information Sharing Platform Laboratories iscurrently researching and developing informationclassification technology based on access logs [2]. In
this approach, some kind of relationship is considered89Letters

FuturePresentSearch site

Present search results

InternetInternet

Search results Search results Search results • • •Search results Search results Search results • • •Search results Search results Search results • • •User• Finding desired information takes time as the number of search results increases.
• Desired information may not be obtained.
(a) Information searching

Search Search Search
results results results

UserPresentFuture

User X
User Y

Information
customization
service

Search results Search results Search results • • •Search results Search results Search results • • •Search results Search results Search results • • •Search site

Search Search Search
results results results

User Z

Info. A

Info. B

Info. C

Info. D

Info. E

Info. F

Info. G

Info. H

Info. IXYZ• • •Information
customization
service• • •• • •Optimal information customization
InternetInternet
Info. G

Info. H

Info. I

Info. A

User Z• Processing increases.
• Service quality deteriorates.
Info. ...

User Z(b) Information customization service

Fig. 1. Future issues in information searching.

Contents accessed withina certain period of time
Content Content
A
B

Relationship exists
between contents
Content Content
A
B

Contents accessed by multiple
users within a period of time
Content Content
AB

Strong relationship exists
between contents
Content Content
A
B(a) Extraction of relationships

ContentContentContentContent

ContentContentContentContent

Content

Content

Content

ContentContent groupContent

Content

Content

Content

Content

Content

Content

to be related are connected, and if thenumber of interconnections exceeds acertain value, those contents are categorized as a content group having astrong relationship. In this technology, the system updates the classifications in the neighborhood of accessed
content every time an access log isupdated. Limiting the range of computation in this way reduces the computational load when classifying hugeamounts of information and enables
realtime information classification tobe performed.

Content3. C-Chart(b) Classification

We have developed a new Web
browsing system called C-Chart *1
Fig. 2. Information-classification technology based on access logs.
using this information-classification
technology [3]. C-Chart does more
to exist among contents accessed by the same user
than simply provide links. It also allows users towithin a certain period of time. Furthermore, a strong
browse through information using information classirelationship is considered to exist among certain confication based on access logs. The provision of suchtents that have been accessed by multiple users withcategorized information can make informationin the same period of time. Using access logs in thisway enables relationships between contents to be*1 C of C-Chart expresses cluster, context, and content.
derived (Fig. 2). In particular, contents that are found90

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browsing more efficient. It should also enable users tomake discoveries that were not possible with previous
browsing systems. Its configuration is shown in Fig.
3. The server consists of a proxy that obtains accesslogs of user information browsing, an engine thatclassifies information based on the obtained accesslogs and generates classification data, and a databasethat stores that classification data.
The system converts this classification data into
metadata in RDF*2 format and then sends the data toa user terminal. This process gives generated dataTo InternetRDF

Web accessBrowser

ProxySend log

Access log

EngineDatabase
Extract
relationships

general-purpose features so that it can be applied to avariety of Web services and applications and not justthe client application presented here. For this reason,
we expect C-Chart to find widespread use.
The user terminal in this system consists of Internet
Explorer and the C-Chart client. The client links withthe browser to display information-classification
results from Web browsing in the client’s window (Fig.
4). The server analyzes Web access from Internet
Explorer in real time and reflects the analysis results on
the C-Chart client. The nodes shown on the client represent URLs so that clicking on a nodedisplays the Web page corresponding
to that URL on the browser. Since aclick is reflected in Internet Explorer inRDF
the node in the C-Chart client, browsing by clicking nodes is also possible.
C-ChartSince browsing can also be carried out
clientfrom an information classification
result in addition to browsing by clicking a conventional Web link, evenmore efficient browsing is possible.

Classification
dataURL
ServerUser terminal

Fig. 3. C-Chart system configuration.

*2 RDF (resource description framework): A
standard for exchanging metadata on theWeb. It prescribes a description method by
the World Wide Web Consortium (W3C) anda method of exchange between computers.

Fig. 4. Screen shot of browser and C-Chart.

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Services that classify search results for presentation
are being provided by various companies including
Vivisimo [4], Grokker2 [5], and TouchGraph [6]. Theseservices, however, classify search results while C-Chartclassifies and displays items related to search results.
This means that C-Chart can be appropriately combined with technologies that classify search results.

technology based on access logs now being
researched and developed in NTT Information Sharing Platform Laboratories and introduced the new CChart browsing system that employs this information-classification technology. We plan to improve its
performance and expand it to services and fields thatmake use of such characteristics.

4. Expansion to various services
The C-Chart system targets URLs in access logs andclassifies that information. The underlying technology,
however, can analyze anything obtained from accesslogs. When the access log of a search site, for example,
is used, the keywords entered by users for searching
can be analyzed to extract relationships among themand to classify that information accordingly.
Moreover, the purchasing log of an e-commercesite can be used to extract relationships among purchased products to classify purchasing informationand present users with recommended products.
Although conventional recommendation services
often present similar products individually as recommended items (for example, another book by thesame author), our technology can classify offeredproducts so that an e-commerce operator can present
recommended products in a more efficient manner.
5. Application to the Semantic Web
The Semantic Web *3 has been receiving muchattention as technology for increasing the accuracy ofsearch results and making it easier for users to utilize
the flood of information on the Web. Before theSemantic Web can be created, however, many issues
must be resolved, with one in particular being the generation of metadata [7]. Considering that our technology can be used to extract information structures fromaccess logs and generate and assign metadata, we arealso studying its application to the Semantic Web.

References
[1]
[2]

[3]

[4]
[5]
[6]
[7]

http://www.goo.ne.jp/
K. Ooi, N. Hayashi, and T. Mukaigaito, “C-Chart,” Semantic Web
Conference 2003, Proceedings, 6-6, Tokyo, Japan, Nov. 2003 (inJapanese).
N. Hayashi, K. Ooi, and T. Mukaigaito, “Related Information Presentation System using Access Log,” 2004 IEICE General Conference,
B-16-29, Tokyo, Japan, Mar. 2004 (in Japanese).
http://vivisimo.com/
http://www.groxis.com/
http://www.touchgraph.com/INTAP, “Annual Report for Fiscal Year 2002 of the Semantic WebCommittee,” (in Japanese).

Noriyuki Hayashi
Research Engineer, Software Architecture Project, NTT Information Sharing Platform Laboratories.
He received the B.E. and M.E. degrees in electronics engineering from Hokkaido University,Sapporo, Hokkaido in 1991 and 1993, respectively. He joined NTT in 1993. He has been
engaged in R&D of context oriented sharing
technology. His current research interests
include context-awareness and open source systems. He is a member of the Institute of Electronics, Information and Communication Engineers (IEICE).

Keita Ooi
Engineer, Software Architecture Project, NTT
Information Sharing Platform Laboratories.
He received the B.S. and M.S. degrees in mathematical science from Kyoto University, Kyoto
in 1996 and 1999, respectively. In 1999, hejoined NTT Information Sharing Platform Laboratories, Tokyo. His current interest is collaborative filtering.

6. Future plans
Takeya Mukaigaito

This article described information-classification*3 A technology for giving Web information that describes content(metadata) so that computers can understand content and automatically process it. The idea here is to collect Web metadata into adatabase and to extract and structure the knowledge to make theWeb more useful. The Semantic Web aims to provide more intelligent services. If this technology becomes practical, the searchresults will become more accurate and users will find it easier touse the massive amount of information on the Web.

92

Senior Research Engineer, Software Architecture Project, NTT Information Sharing Platform
Laboratories.
He received the B.E. degree in engineering science from the University of Tsukuba, Ibaraki in1989. In 1989, he joined NTT Communication
and Information Processing Laboratories, Kanagawa. His current interest is context oriented
application architecture.

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