The Data Mining Technology Is Applied In Tax Assessment Adminstration

Data Mining (DM) aims at analyzing massive amounts of data and extracting meaningful and comprehensible patterns, called knowledge. In recent years, DM has got domestic and international widespread concern and has been becoming most hot researching realm in the field of information systems and computer science. DM has been widely used in biomedical field, financial field, retail industry and telecommunication industry. The decision tree learning algorithm is very useful in data mining technique. The ID3 algorithm is studied in this thesis, which is the key algorithm of decision tree learning. The improved algorithm of ID3 is proposed by introducing user-interest, which resolves the problem of "the big data covers up the fraction" in the decision support process in certain degree.This thesis in the outline data mining technology and in the classified algorithm foundation, based on the traditional ID3, the method of improving ID3 is put forward by introducing the concept of user-interest, which adds user-interest to information entropy in the ID3 algorithm. Therefore it makes the algorithm depend not only on train sets but also on field knowledge of studied attribute. In this way the improved algorithm increases the classification precision. And an example is trained by ID3, which proves that improved algorithm is efficient.In addition, in this thesis,according to the object-oriented method and using C++ to actualize ID3 algorithm and improved QID3 algorithm. The present study intends to set up an integrated system of decision tree construction. This system face the practical application, realized inducted from the data to the production rule complete data mining step, and had processing attribute value function and so on flaw data, continual attribute data..This thesis also according to actual need of the tax system, the system which develops applies in the tax assessment adminstration system, through on the analysis and the excavation to the tax data, produces the usefully "classified rule" of the questionable object.