Papers in PDF format

in our system is quite large, and provides sufficient, language independent information to potential buyers and
sellers of products that can be traded within the system.
We currently have no scientific criteria to show that our selection of topics and vocabularies is indeed
necessary and sufficient to provide meaningful communication in specific section. Our approach here has been to
make empirical investigations of classified ads in newspapers as well as on-line services, and include the most
commonly found topics and their related vocabularies. We are considering using computerized information
extraction from on-line services, such as in the FRUMP system, [DeJong 79] and [DeJong 82].
To continue the above example, the section Automobile may have the following definitions:
-> Topics : (Vehicle Type, Manufacturer, Price)
-> Vocabularies : ((Sedan, Hard Top/Coupe, Open Convertible, Sports Car ... etc.) ( Acura, Alfa, Audi, Austin,
BMW ... etc.) ( 1 .. 20,000))
The user can now be more specific in his formulation: "I would like to search the sell ad listings for an
automobile which is a sedan or sports car made by Audi, costing no more than $ 10,000."
The mathematical foundation for the approach in 3.1 and 3.2 above is a simple application of combination theory.
The system is a combination of well-formed sentences which can be gotten out of the formula:
Actions * Intentions * Sections
where each Section has the following number of possible combinations:
Vocabulary-Topic1 * Vocabulary-Topic2 * ... * Vocabulary-TopicN
During the design of the system we have come to talk about our enumerated language as a "pickup-language".
This is because we provide a graphical, mainly menu-based interface for submitting and trading of goods in each
section, as opposed to newspapers which require more human processing, especially for ad submissions. For
example, if someone wants to sell a car, he/she inputs information by picking up menu choices for maker, brand,
model etc. Display of information to potential buyers is then based on menu selections, so that unsuitable
information neither can be in- or output from the system.
3.3 Mapping Between Equal Vocabularies -- to Handle Multiple Languages
So far, we have mostly talked about input of information into the system, using our "pickup-language". However,
for communication to occur, there must also be output. All input to the system is stored as English "pickup-words".
When someone browses the system, this information is then presented in tabular form, as shown in Figure 1. This
tabular presentation is easily readable and has the advantage that it is highly language neutral and does not
depend on other syntactic rules, such as word order, plural forms, etc. A mapping for each word is provided so
that the user can browse the system in his/her language, regardless of what the input language originally was
[Bjorn and Kim 96].
Figure 1: Tabular representation of the "pickup-language"
The same is also true for input: For each menu choice, a mapping from a base language to each supported
language is provided, so that the user can interact with the system in his/her preferred language but still make the
information available to speakers of other languages. A mapping (from the topic level down) for the above