Review Mining and Summarization

Probabilistic aspect mining model (PAMM) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term postmarketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry. Recently, large numbers of adverse events and the development of data mining technology have motivated the development of statistical and data mining methods. These stand-alone methods, with no integration into knowledge discovery systems, inconvenient for users and the processes for exploration are time-consuming. This paper proposes an interactive system platform for the detection of PAMMs. This reduces the chance of having aspects formed from mixing concepts of different classes; hence the identified aspects are easier to be interpreted by people. The aspects found also have the property that they are class distinguishing:- they can be used to distinguish a class from other classes.