Intelligent information analysis through a human-computer integrated approach

Information analysis typically involves discovering information, determining contextual relevance, and synthesizing useful knowledge from multiple sources. When the search and retrieval of information from heterogeneous data is based purely on key words, it may result in missing potentially important sources or could result in finding too many unrelated sources. Higher level understanding of terms in a domain, i.e., semantics, can help in dealing with these problems. Developing an understanding of information sources in the form of semantic representation is fundamentally a complex reasoning process. Manual generation of semantic concepts in a domain is inefficient. Complete automation of the process leads to inaccuracies and could be ineffective. The article describes an approach that integrates computerized processes with human reasoning methods for generating semantic concept spaces to support information search and retrieval from distributed information sources.