This paper proposes a method to integrate computer specifications retrieved from multiple Web sites, to extract characteristic-data of each computer based on integrated information, and to present products suitable for a user's request. The specifications written in HTML are converted into normal forms called table structure. The quantitative attributes such as speed, capacity and dimensions are extracted by comparing them with the mean or mode of all sample data, and the qualitative ones such as kind of processor and graphics chip are extracted using knowledge provided manually. The recommended products are dynamically determined from the extracted data by a user's request and relevance feedback. Experimental results show the effectiveness of our method.

This paper shows an experimental approach to the understanding system of natural language and pictorial patterns. The system is titles as ISOBAR (an Information understanding System Of BAsic weather Report). It can accept both linguistic and pictorial inputs. Also it produces either linguistic or pictorial, or both, output according to the commands which it received. The most remarkable point of the system is that the performance of the system is based on the semantic processing of the input. As ISOBAR's world is limited within the weather report of Japan and Far East Asian areas with associated weather charts, so the semantic background of the system is very narrow, and is quite a specific one. But the methodologies and algorithms in the system will be the first step for the embodiment of the more complicated and more general systems. ISOBAR has two operating modes in principle. One is the accumulation of meteorological information, and the other is its retrieval. According to the experimental outcomes, the performance of the system is almost good except for the picture processing procedures. Finally, the problems for the future research are remarked.