Distributed intelligence as an information retrieval system

Abstract

The traditional knowledge based approach is not a feasible choice to be utilized in information retrieval in domains such as Geographic Information Systems (GIS), because accurate information of geographic data is spatially distributed and vast in volume. The challenge is to improve the process of information retrieval, which can be applied to varying contexts such as GIS, going beyond the limits imposed by the knowledge base centric approaches. Social networks possess a vast amount of unstructured knowledge in its user base, which can be used in drawing interesting patterns, if analyzed in a systematic approach. 1n this paper, we emphasize on an approach for information search and retrieval, by combining the social network of human intelligence and knowledge bases of information. Users of the system can present natural language queries, and questions can be directed to relevant experts within the social network. Distributed information retrieval and information fusion is applied to optimize the process of single answer generation. The feasibility of our proposed architecture is investigated by implementing a QA(Question Answering) system on a social network as a proof of concept. The Question Answering System is based on geographic queries which will be directed to relevant users within the network to gather answers. Varying methods of information fusion and Natural Language Processing have been researched and discussed to discover the suitable approaches for answer generation. With the wide acceptance of the social networking paradigm and sharing of information, this approach can - be extended to other domains as well.