Soft Computing for Perception Based Information Processing

Abstract

Humans have a remarkable capability (perception) to perform a wide variety of physical and mental tasks without any measurements or computations. Familiar examples of such tasks are: playing golf, assessing wine, recognizing distorted speech, and summarizing a story. The question is whether a special type information retrieval processing strategy can be designed that build in perception. Commercial Web search engines have been defined which manage information only in a crisp way. Their query languages do not allow the expression of preferences or vagueness. Even though techniques exist for locating exact matches, finding relevant partial matches might be a problem. It may not be also easy to specify query requests precisely and completely - resulting in a situation known as a fuzzy-querying. It is usually not a problem for small domains, but for large repositories such as World Wide Web, a request specification becomes a bottleneck. Thus, a flexible retrieval algorithm is required, allowing for imprecise or fuzzy query specification or search. In addition, they have problems as follows : (1) large answer set; (2) low precision; (3) unable to preserve the hypertext structures of matching hyperdocuments; (4) ineffective for general-concept queries. The task is to use user-defined queries to retrieve useful information according to certain measures. In order to handle these problems, we propose the Perception Index (PI) that contains attributes associated with a focal keyword restricted by fuzzy term(s) used in fuzzy queries on the Internet. If we integrate the Document Index (DI) used in commercial Web search engines with the proposed PI, we can handle both crisp terms (keyword-based) and fuzzy terms (perception-based). In this respect, the proposed approach is softer than the keyword-based approach. The PI brings somewhat closer to natural language. It is a further step toward a real human-friendly, natural language-based interface for Internet. It should greatly help the user relatively easily retrieve relevant information. In other words, the PI assists the user to reflect his/her perception in the process of query. Consequently, Internet users can narrow thousands of hits to the few that users really want. In this respect, the PI provides a new tool for targeting queries that users really want, and an invaluable personalized search. In this chapter, we also present the search mechanism based on the integrated index (DI + PI) and fuzzy query based on the integrated index (DI + PI). Moreover, we describe some features of the proposed method and suggest some considerations for implementing the proposed method. The main goal of the perception-based information processes and retrieval system is to design a model for the internet based on user profile with capability of exchanging and updating the rules dynamically and “do what I mean, not as I say” and using programming with “human common sense capability”.