A Multi-agent Based Intelligent WWW Interfacer
Yasuhiko KITAMURA
Faculty of Engineering, Osaka City University
3-3-138, Sugimoto, Sumiyoshi-ku, Osaka, 558-8585, JAPAN
Phone & Fax: +81-6-6605-3081, E-mail: kitamura@info.eng.osaka-cu.ac.jp

Introduction
The WWW technology is rapidly proliferating into our society and, as an infrastructurethat supports our daily life, it is widely used for various purposes such as e-commerce,
research and education, personal or group information dissemination, special interest
community creation and so on. The amount of WWW information increases veryrapidly day by day, but that makes retrieving information more and more. Searchengines are most widely used tool to retrieve information from the WWW, but it is notalways very useful for novice users such as aged people. For example, when a user
wants to know a recipe for pork, he/she may submit just “pork” as a keyword to asearch engine, then he/she may get stuck with a large number of URLs including not
only about recipes but also about farming, retailers, restaurants, and so on.
Generally speaking, there are two ambiguities concerning WWW information
retrieval by using a search engine. The first ambiguity is about information sources.
Currently the HTML is mainly used to describe WWW pages, but it is not wellequipped for specifying semantic information in the pages. Hence, a standard searchengine hits a page just when the page includes the specified keywords. The second
ambiguity is about user’s queries. For example, when a user submits a keyword “pork”,
he/she may have an intention like “I would like to cook a dish with pork. Yesterday I
cooked a Chinese dish, so today a Japanese one. I am on diet now, so I prefer alow-calorie one.” in his/her background. Of course, current search engines cannot
accept the above intention as it is, they just can accept a few keywords that include in
the intention.
To deal with the above ambiguities, we are currently developing a multi-agent based
intelligent WWW interfacer as shown in Figure 1. Our system consists of multiple
information agents, each of which provides domain specific information, and a personalagent, which manages its user ’s profile information. Each agent has its own characterinterface and an information retrieval task is represented through dialogues between theuser and the personal agent and between the personal agent and information agents.

Figure 1: System Architecture.
In our system, to deal with the ambiguity of informatio n sources, we utilize domain
specific information agents. An information agent provides information concerning aparticular domain such as recipes, restaurants, retailers, and so on. We expect theinformation agents cannot only provide noiseless information but also facilitate abilities
of extracting more detailed information (ex. extracting ingredients from a recipe page)and integrating information from multiple sources (ex. relating ingredients to retailers
that carry them).
To deal with the ambiguity of user’s query, we utilize the multi-character interface. In
the interface, the process of information retrieval is represented to the user throughinteractions and dialogues among character agents. When an agent makes a mistake
about understanding the user ’s intention, the user can point out the mistake directly tothe agent. We expect, through the interaction between the user and the agents, the agents
can naturally learn the user’s intention.
In the following, we describe “keyword spice”, a technology that agentizes a genericsearch engine into a domain specific information agent, and more about themulti-character interface.

Keyword Spice1
A flaw of search engine is that, when a user submits a simple keyword, it returns a large
number of various WWW pages that relate to the keyword. To reduce the number ofpages, the user usually adds some more keywords, but how appropriate the additional
We are currently studying keyword spice by using a Japanese search engine, so thekeyword spices found discussed in this paper may not work well for non-Japanesesearch engines.
1

keywords are seems to depend on the experience of the user. For example, when wewant to retrieve recipe pages for pork, it is more effective to submit “pork, ingredient ”
than “pork, recipe.” Moreover, the keyword “ingredient ” is effective in not only for“pork” but also for other recipe keywords such as “beef” and “chicken. ” Using thistechnique, we can build a domain specific search engine (or information agent) from ageneric search engine just by adding some keywords, which we call keyword spices.
Here we show how to find domain specific keyword spices as follows.
1.

2.
3.
4.

Collect a set of WWW pages, which is denoted to be S, by using a generic searchengine by submitting domain specific keywords (ex. pork, beef, chicken, and soon.)
Classify S into the set of domain (ex. recipe) related pages, which is denoted to be T,
and the set of unrelated ones, which is denoted to be F.
Select frequent keywords (ex. top 50) that appear in the set T. The keywords arecalled keyword spice candidates.
Calculate the appropriateness ratio A(c) of each candidate c, which is defined to beA(c)=(the number of pages in T that include c)/(the number of pages in S that
include c).

A candidate with the large A(c) can be a keyword spice. Multiple keyword spices canbe used in a multiplicative way. For example, we can use a keyword spice (ex.
ingredient or direction) to retrieve recipe pages. Moreover, we can add more keyword
spices to retrieve more specific recipe pages such as Japanese dishes (kelp or mirin canbe used as a more specific keyword spice), Western dishes (cream, wine, or butter), orChinese dishes (sesame oil, ginger)
From a viewpoint of information retrieval, keyword spice is a technique to improve theprecision of search engine, sacrificing the recall. To compensate the recall, we cansubmit an OR combination of multiple spices (ex. cream OR wine OR butter). Hence, if
we want to retrieve Western recipe pages for pork, a query can be “pork AND(ingredient OR direction) AND (cream OR wine OR butter).”

Multi-character Interface
In our system, the process of information retrieval is represented as dialogues among
the user and the agents as shown in Figure 2.

Figure 2: Multiple Character Interface. The servant initially recommends a Japanesedish, but the parrot says “The user cooked a Japanese dish yesterday, so please
recommend a Chinese dish today. ” Then, the servant says “OK. I will recommend aChinese again.”
Character interface is expected to be a more gentle or natural interface to humans thankeyboards or GUI because a user can interact with a computer as if he/she
communicates with people through dialogue. Moreover, from a business perspective
such as e-commerce, characters add more value. For example, Pokemon, Japanesecharacters born in a computer game, produces a number of related merchandize goods
and the amount of annual sales is reported to reach 400 billion yen in Japan and 200billion yen overseas. Except Pokemon, we have a number of well known characters inJapan such as Hello Kitty, Doraemon, and Momo to name a few. Microsoft also makes agreat effort to develop MS-Agent for Windows and, on the Internet, life- like agentsdeveloped by Extempo (http://www.extempo.com), Haptek (http://www.haptek.com),
VirtualPersonalities(http://www.vperson.com),
ArtificialLife(http://www.artificial-life.com), and so on are now commercially available.
In a conventional character interface, a single character interacts with its user, but weare developing a multi-character interface where multiple characters interact with eachother and the user.
An advantage of multi-character interface is that it can contribute to a multi-agent
system that tries to learn user’s intention or preference. A multi-agent system consists ofintelligent agents, each of which has some parameters to be set according to the user’sintention or preference to show some intelligent and adaptive behavior, but the problem

is how to learn the intention or preference in a distributed manner. Our multi-characterinterface can be a solution to this problem. Let us discuss with the following scenario.
(1) User->Personal Agent: “I would like to have a recipe for pork.”(2) Personal Agent->User: “OK. I will call a recipe agent.”(3) Personal Agent->Recipe Agent: “Yesterday you recommended a Japanese recipe, sotoday please recommend a Chinese recipe for pork.”(4) User->Personal Agent: “I would like to have a Japanese recipe.”(5) Personal Agent->Recipe Agent: “Please recommend a Japanese recipe for pork.”(6) Recipe Agent->User: “How about this?”(7) User->Recipe Agent: “It looks too much calories. Please recommend another one in
low calories.”
Here we assume that the personal agent manages a query log and can advise the recipe
agent to recommend a type of dishes considering the log and that the recipe agent canrecommend recipes considering the calorie. The problem here is that both agents do notknow the preference (the type of dish or the amount of calorie) exactly at the initialstage. In the multi-character interface, as the process of recipe recommendation isvisually presented through dialogues among agents, so the user can easily notice themistake of an agent and can point out the mistake directly to the agent as shown in (4)and (7) in the above scenario.

Conclusions
In this paper, we propose a multi-agent based intelligent WWW interfacer. To deal withthe ambiguities of information sources and user’s query, we developed keyword spiceand multi-character interface technologies and show their potentials.

Acknowledgement
This paper reports a part of work done by a joint project of Kyoto University, Osaka
City University, SANYO Electric, NTT West, and NTT Comware at LIST (Laboratoriesof Image Information Science and Technology) subsidized by NEDO (New Energy andIndustrial Technology Development Organization). I thank Prof. Toru Ishida for his
helpful support as the project leader and Teruhiro Yamada and Takashi Kokubo for theirefforts at the development of the system.