Special Feature

Navigational Information Retrieval Technologies
that Help Users Reach the Desired Information
Ryoji Kataoka†, Hiroyuki Toda, Yukio Uematsu,
Ko Fujimura, Katsuji Bessho, and Shuichi Nishioka
Abstract
We present some next-generation information retrieval technologies that help users reach the information that they are seeking according to their situation and time.

1. Toward the era of navigational search service
With the proliferation of broadband connections,
we are using the Internet more often in a variety ofways in daily life. In recent years, the rapid spread ofsearch services has been especially remarkable. Truly
effective search functions are essential for various
portal services handling a huge volume of information because the search function is the main service
that users use among the various ones provided byportals. For example, there are search services
designed for multimedia such as images, movies, andmusic on the web and ones designated for news andblog (Weblog) articles that are being updated continuously.
Search services continue to evolve. The first-generation search service, a directory-type search service,
is a major information retrieval tool and has grownalong with the Internet. The second-generation
search service is a search-engine-type service basedon direct searching by keywords and it has grownwith the volume of information available. In an age inwhich the way people use the Internet has diversified
and broadened, NTT Cyber Solutions Laboratories
thinks that the third-generation search service typewill be a navigational search service that assists users
in encountering the information they need in theircurrent situation. In this article, we present sometechnologies that will enable the next-generation nav-igational search service by referring to some of ourresearch.
2. Research topics
2.1 TopicMaster: a news article retrieving andclustering system
With the amount of information available on theInternet continuing to increase day by day, theamount of information produced by a search is likely
to continue to increase. Most existing search services
can rank search results based on certain criteria, but it
remains extremely difficult to find the desired information from the enormous list of search results. Also,
it is all too common for the user to become irritatedwhen he/she cannot come up with another appropriate keyword to prune the search results.
To alleviate this weakness of existing search services, we have invented a technique that activelyextracts proper names (such as the names of people,organizations, and places) included in the search
results as topics and generates and displays a category structure (topic tree) that properly categorizes thesearch results based on the extracted topics (Fig. 1)[1]. We applied this technique to a news service todevelop TopicMaster, a system that retrieves and categorizes news articles. TopicMaster enables users tooverview an enormous number of search results
through the topic tree and easily prune them by clicking on a topic in the tree.

† NTT Cyber Solutions Laboratories
Yokosuka-shi, 239-0847 Japan
https://www.ntt.co.jp/cclab/e/contact/index.html

Vol. 4 No. 8 Aug. 2006

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Special Feature

Dynamically constructs an index of search
results → Easy overviewing and pruning

Clustering result
ClusteringengineSearchresultSearchengineSearchengineinterface
generator(with resultclustering)

SearchresultNews
articledatabaseNewsarticle
crawler

TopicMaster

News provider

Provides results related to thelabel in the index selected by userFig. 1. TopicMaster.

2.2 MultiMedia Meister: efficient search system
for massive multimedia contents on the web
Regardless of whether the user wants a still image
or a movie, it is inconvenient and difficult to findexactly the desired image from a huge number ofsearch results. Therefore, especially for multimedia
content searches, portal services must offer a searchfunction for finding images that are difficult todescribe in words. The traditional search method uses
keywords, but it is difficult for the user to determine
which keywords will locate the desired image. For
example, when a user wants a particular image of Mt.
Fuji, it will be extremely difficult to find it unless theuniqueness of the image can be well captured by keywords known to the user. NTT Cyber Solutions Laboratories has improved the function of its original fast
full-text search engine to create MultiMedia Meister,a search system that provides a website search function suitable for multimedia [2].
MultiMedia Meister can narrow down the search
results by classification or visual similarity according
to the features of a reference image or a movie (colorand shape) in addition to the traditional keyword
search method (Fig. 2) [3]. With MultiMedia Meister,
the user not only surveys the images that wereretrieved, but can also select a returned image and use
it to refine the search process in an intuitive manner.
It normally takes time to analyze the similarity of
the images based on their features, but MultiMedia
Meister can search billions of images at a practical
18

speed because it can simultaneously retrieve text
information and image features at high speed.
2.3 BLOGRANGER: multifaceted blog searchsystemInformation distributed by blog services contains
what consumers really think. For example, blogs contain information and recent topics that have not beentaken up by the mass media and present opinions
about products or services. Such information is
expected to be used for marketing, and a number ofblog search services have appeared. However, sincemost existing services show the search results ranked
just by date or by blog access frequency, users sometimes have difficulty in reaching the information theywant in blogs, because of the massive amounts ofinformation and the frequent updating.
We have developed a blog search system called
BLOGRANGER to overcome the weaknesses ofexisting services. It shows search results categorized
and arranged by keywords in a multifaceted manner
through four useful kinds of filters. This enables
users to search for information not only by keywords
but also by four viewpoints: topics (categorization byproper name just like TopicMaster), bloggers(authors of blogs), link destinations (Web pages referenced by blog articles), and sentiments (evaluations
or impressions such as “interesting” and “wonderful”). The search results can be categorized andarranged by these four viewpoints (Fig. 3).
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Special Feature

富士山

Images Moving Music Images, movingpictures
pictures, music

Multimedia searchContent-based image retrieval

Thumbnail presentation ofmoving pictures

Preview interface

Clustering presentation ofimage search results

3D space interface

Fig. 2. Multimedia Meister.

Query

Select by sentiment
Select by link
Select by blogger
Select by topic

Search result

Sentiment filter

Link filter

Topic filter
Blogger filter

Fig. 3. BLOGRANGER.

Out of these four filters, the blogger filter makes
use of one of the characteristics of blogs: the articles
are edited by one author (blogger). To see if the blogger writes good articles to which many people wantto link or if the blogger links good articles to his/her
blog, BLOGRANGER numerically evaluates blog
Vol. 4 No. 8 Aug. 2006

articles based on their link relationships. It then ranks
blog articles by popularity [4]. By getting a list ofbloggers who have written highly ranked articles,
users can easily identify useful articles written byreliable bloggers from among the enormous numberof search results.
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Special Feature

2.4 Kanshinji Antenna: Japanese-language
concept search system
The technologies we have presented here are navigation-oriented and assist the user by narrowing
down the search results: they focus on the problem
that search services generally return a huge numberof search results to the user. Another problem withexisting search services is that search results are limited by the information contained in the input keyword, so they may contain very little in the way ofdesired information if the first keyword is inappropriate. Therefore, the next-generation search services
need navigation technologies that can expand thesearch target according to the user’s search goal.
To solve those problems, we are developing aJapanese-language concept search technology. This
determines the concept of the words or phrases input
by the user. For searching, it collects documents
based not only on the input keyword but also on texts
similar in concept to the keyword or phrase input by
the user.
There is one more feature. Since concept searchservices require a dictionary to determine the similarity of semantic content between words, new words
that are not registered in dictionaries, because theyappear on the Internet for the first time, degrade
search precision. Our technology solves this problem.
If an unknown word is detected in the search results,

the semantic content of the unknown word is automatically identified and registered based on the similarity of semantic content between words in thesearch results and those already registered in the dictionary [5]. Thus, this technology enables concept
searches to be provided by Internet search services
for the first time.
We have developed Kanshinji Antenna, a systemthat allows Japanese-language concept searching tobe added to the latest news and blog articles searchservice (Fig. 4). When the user registers a keyword or
sentence related to the information they want as an“antenna”, they can retrieve all information associated with their interest.
2.5 TopicAlert: push-type topic notification
systemIn order to discover information on service-providing sites such as news websites or blogs that frequently release the latest information, it is importantthat these sites provide users with the latest information on a timely basis. This has led to the gradual proliferation of alert services that send notices to users
by e-mail or other means when the desired information is released to the public.
Since existing alert services allow users to set only
simple search conditions, it is difficult to receive justthe information that suits the user’s taste from blogs.

Use existing antenna tobrowse latest articles.

Focus on one
article and searchfor similar articles.

Use the slider toadjust the degree ofantenna sensitivity
for each keyword.

Set and saveyour personaluse antenna.

Fig. 4. Kanshinji Antenna.

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Special Feature

TopicAlert’s condition-setting screen
Specify search
conditions andnotification mode.

Crawlingfor new
information

TopicAlert

Preview function
showing alert images

Newarrival

RSS

Blog

Current
eventsTVprogram

Quick check Catch theof postings
latest news
on yourwithout failfavorite blogs

Never missyour favorite
programs

ReminderNewsflash

RSS: rich site summaryFig. 5. TopicAlert.

Moreover, since the existing alert services can matchthe search conditions users already set with newly
arriving information only in a one-by-one manner,
they demand extensive hardware resources to provide
immediate services, which leads to high operating
costs.
Our push-type topic notification system TopicAlert
uses high-speed XML (extensible markup language)filtering that enables efficient information matchingto achieve quick selection of information by setting
specific search conditions while keeping the traditional system environment (Fig. 5) [6]. Here, we
explain how this system works. The XML filtering
method converts and structures the search conditionsof topics that the user wants into the XPath*1 format.
With this technology, the system compares those topics with the search criteria such as keywords or genres input by other users and integrates the overlapping
search criteria. In this way, the system only has tosearch using the integrated search criteria once. XML
filtering thus makes the matching process more efficient. New information extracted from the Internet isconverted into XML format data. TopicAlert reads
this XML format data to match the integrated search

criteria from the top. In this way, TopicAlert can identify all users who need the information while minimizing the matching process because it can narrow
down the search criteria that match newly arriving
information by using the integrated search criteria.
3. Future developments
We have verified the technologies presented in thisarticle in terms of their technological and operational
usefulness through tests on “goo Labs” [7], the experimental site built into NTT Group’s integral portalsite “goo”. MultiMedia Meister has been commercialized as a search engine for a multimedia searchservice for images, moving pictures, and music ongoo. We are committed to continuously developing
the next-generation information search technologies
to provide users with safe, reliable, and convenient
search services.
References
[1]

[2]

*1 A standard that defines the description method designating thespecific elements in an XML document.

Vol. 4 No. 8 Aug. 2006

H. Toda and R. Kataoka, “A Clustering Method for News Articles
Retrieval System,” in Poster Proceedings of the WWW 2005 Conference, 2005.
H. Takeno and T. Inoue, “Distributed information gathering and fulltext search system Infobee/Evangelist,” NTT R&D, Vol. 52, No. 2,
2004 (in Japanese).

21Special Feature

[3]

[4]

[5]

Y. Uematsu, R. Kataoka, and H. Takeno, “Clustering Presentation ofWeb Image Retrieval Results using Textual Information and ImageFeatures,” in Proceedings of the EuroIMSA 2006 Conference, 2006.
K. Fujimura, T. Inoue, and M. Sugizaki, “The EigenRumor Algorithm
for Ranking Blogs,” in Proceedings of the WWW 2005 Workshop on
the Weblogging Ecosystem: Aggregation, Analysis and Dynamics,2005.
K. Bessho, O. Furuse, and R. Kataoka, “Concept Vector Generation[6][7]

Method Based on Co-occurrences between Words and Semantic
Attributes,” in Proceedings of the 20th Annual Conference of theJapanese Society for Artificial Intelligence, 2006 (in Japanese).
M. Onizuka, F. Y. Chen, R. Michigami, and T. Honishi, “IncrementalMaintenance for Materialized XPath/XSLT Views,” in Proceedingsof the WWW 2005, 2005.
http://labs.goo.ne.jp/Ryoji Kataoka

Ko Fujimura

Senior Research Engineer, Supervisor, Media
Computing Project, NTT Cyber Solutions Laboratories.
He received the B.E. and M.E. degrees in electronic engineering from Chiba University, Chiba,
in 1985 and 1987, respectively. He joined NTT
Communications and Information Processing
Laboratories in 1987 and engaged in research ontransaction processing and multimedia databases. He is currently engaged in R&D of information retrieval technologies. He is a member of theInformation Processing Society of Japan (IPSJ).

Senior Research Engineer, Media Computing
Project, NTT Cyber Solutions Laboratories.
He received the B.E. and M.E. degrees in electrical engineering and the Dr.Eng. degree in
information engineering from Hokkaido University, Hokkaido, in 1984, 1986, and 1989, respectively. He joined NTT Information Processing
Laboratories in 1989 and engaged in R&D oftransaction processing systems and digital ticket
systems and standardization of payment systems
in the Internet Engineering Task Force andInfrared Data Association. Since 2003, he has
been engaged in research on community mining
and blog search engines. He is also a visiting professor of the University of Electro-communications, Tokyo. He is a member of IPSJ, the Institute of Electronics, Information and Communication Engineers (IEICE) of Japan, and the Japan
Association for Social Informatics.

Hiroyuki Toda
Research Engineer, Media Computing Project,
NTT Cyber Solutions Laboratories.
He received the B.E. and M.E. degrees in material science from Nagoya University, Aichi, in
1997 and 1999, respectively. He joined NTT
Cyber Space Laboratories in 1999. Since then, hehas been engaged in R&D of information
retrieval, text mining, and clustering. He is currently a Ph.D. student at the University of Tsukuba, Ibaragi. He is a member of ACM SIGIR,IPSJ, and the Database Society of Japan (DBSJ).

Katsuji Bessho
Research Engineer, Media Computing Project,
NTT Cyber Solutions Laboratories.
He received the B.S. and M.S. degrees in mathematics from Osaka University, Osaka, in 1992
and 1994, respectively. He joined NTT in 1994.
He is currently at the Media Computing Project,
NTT Cyber Solution Laboratories and working
on natural language processing technology. He isa member of IEICE, IPSJ, and the Association
for Natural Language Processing.

Yukio Uematsu
Research Engineer, Media Computing Project,
NTT Cyber Solutions Laboratories.
He received the B.E. and M.E. degrees in computer science from Tokyo University of Science,Tokyo, in 2001 and 2003, respectively. He joined
NTT Cyber Solutions Laboratories in 2003.
Since then, he has been engaged in R&D of information retrieval, text mining, and web image
retrieval. He is currently a Ph.D. student at
Tokyo University of Science, Tokyo. He is amember of IPSJ and the Japanese Society for
Artificial Intelligence.

22Shuichi Nishioka
Research Engineer, Promotion Project 1, NTT
Cyber Solutions Laboratories.
He received the B.E. degree in electrical andcomputer engineering and the Dr.Eng. degree in
information media and environment sciencesfrom Yokohama National University, Kanagawa, in 1995 and 2005, respectively. Since joining NTT Laboratories in 2005, he has been
engaged in research on database management
systems, copyright management systems, andXML processing systems. He is a member ofIPSJ and DBSJ.

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