Fusion Techniques for Reliable Information: A Survey <s> Knowledge Discovery (KD) <s> This project aims to investigate knowledge-based approaches to the problem of information fusion. We show how domain-specific knowledge, in conjunction with semantic Web services, can be used to improve situational awareness in the operational deployment of humanitarian operations, especially when such operations occur against a contextual backdrop of ongoing military conflict. Information, harvested from a variety of physically disparate and semantically heterogeneous data sources, is used to establish a common repository of semantically rich, conceptual-level representations of real-world events. Reasoning services, deployed over the knowledge repository, are used to intelligently fuse information, taking into account factors such as the level of trust and confidence assigned to specific information sources. Selective attention to information of relevance to particular users helps avoid situations of information overload that might otherwise result from the information fusion process. We believe this approach to have general applicability in a wide variety of military contexts. <s> BIB001 </s> Fusion Techniques for Reliable Information: A Survey <s> Knowledge Discovery (KD) <s> In previous papers, we have presented a logic-based framework based on fusion rules for merging structured news reports. Structured news reports are XML documents, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume structured news reports do not require natural language processing. Fusion rules are a form of scripting language that define how structured news reports should be merged. The antecedent of a fusion rule is a call to investigate the information in the structured news reports and the background knowledge, and the consequent of a fusion rule is a formula specifying an action to be undertaken to form a merged report. It is expected that a set of fusion rules is defined for any given application. In this paper we extend the approach to handling probability values, degrees of beliefs, or necessity measures associated with textentries in the news reports. We present the formal definition for each of these types of uncertainty and explain how they can be handled using fusion rules. We also discuss the methods of detecting inconsistencies among sources. <s> BIB002
KD is a potential objective multisensor information fusion process BIB001 . Data mining can be viewed as a means of accomplishing the objective of the KC. It is generally associated with only a single data source. A real intelligent decision system should able to not only fuse the information coming from multiple sensors, but offer the conceptual information and knowledge BIB002 .