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Abstract

Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.

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Abstract

In an image database environment, an image can be retrieved using common names of entities that appear in it. Shows how an image is abstracted into a hierarchy of entity names and features and how relations are established between entities visible in the image. Semantic queries are also hierarchical. Its core is a fuzzy matching technique that compares semantic queries to image abstractions by assessing the similarity of contexts between the query and the candidate image. An important object of this matching technique is to distinguish between abstractions of different images that have the same labels but are different in context from each other. Each image is tagged with a matching degree even when it does not provide an exact match of the query. Experiments have been conducted to evaluate the strategy

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