Representation (systemics)

About: Representation (systemics) is a research topic. Over the lifetime, 33821 publications have been published within this topic receiving 475461 citations.

Adaptive information retrieval: using a connectionist representation to retrieve and learn about documents

Abstract: AIR represents a connectionist approach to the task of information retrieval. The system uses relevance feedback from its users to change its representation of authors, index terms and documents so that, over time, AIR improves at its task. The result is a representation of the consensual meaning of keywords and documents shared by some group of users. The central focus goal of this paper is to use our experience with AIR to highlight those characteristics of connectionist representations that make them particularly appropriate for IR applications. We argue that this associative representation is a natural generalization of traditional IR techniques, and that connectionist learning techniques are effective in this setting.

System and method for retrieving entities and integrating data

Abstract: A data integration system and method gathers information dynamically from one or more data sources, which may be located at different servers and have incompatible formats, structures the information into a configurable, object-oriented information model, and outputs the information for the user according to an associated, configurable visual representation with automatic content classification.