Fusion rules for merging uncertain information

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.

A split-combination approach to merging knowledge bases in possibilistic logic

In this paper, we propose an adaptive approach to merging possibilistic knowledge bases that deploys multiple operators instead of a single operator in the merging process. The merging approach consists of two steps: one is called the splitting step and the other is called the combination step. The splitting step splits each knowledge base into two subbases and then in the second step, different classes of subbases are combined using different operators. Our approach is applied to knowledge bases which are self-consistent and the result of merging is also a consistent knowledge base. Two operators are proposed based on two different splitting methods. Both operators result in a possibilistic knowledge base which contains more information than that obtained by the t-conorm (such as the maximum) based merging methods. In the flat case, one of the operators provides a good alternative to syntax-based merging operators in classical logic.

Lipid extraction has little effect on the delta N-15 of aquatic consumers

Proper application of stable isotopes (e. g., delta N-15 and delta C-13) to food web analysis requires an understanding of all nondietary factors that contribute to isotopic variability. Lipid extraction is often used during stable isotope analysis (SIA), because synthesized lipids have a low delta C-13 and can mask the delta C-13 of a consumer's diet. Recent studies indicate that lipid extraction intended to adjust delta C-13 may also cause shifts in delta N-15, but the magnitude of and reasons for the shift are highly uncertain. We examined a large data set (n = 854) for effects of lipid extraction (using Bligh and dyer's [ 1959] chloroform-methanol solvent mixtures) on the delta N-15 of aquatic consumers. We found no effect of chemically extracting lipids on the delta N-15 of whole zooplankton, unionid mussels, and fish liver samples, and found a small increase in fish muscle delta N-15 of similar to 0.4%. We also detected a negative relationship between the shift in delta N-15 following extraction and the C:N ratio in muscle tissue, suggesting that effects of extraction were greater for tissue with lower lipid content. As long as appropriate techniques such as those from Bligh and dyer (1959) are used, effects of lipid extraction on delta N-15 of aquatic consumers need not be a major consideration in the SIA of food webs.