In this article, we integrate traditional database and text database that can process mass of data to implement a criminal investigation database system for theft. The system consists of criminal events database, attribute-term matrix and similarity comparison module. The criminal events database, a relational database, keeps the criminal facts for each lawbreaker. Policeman can retrieve previously-recorded people who have used the similar criminal model and stolen the similary boody as those of the underlying event from the text database as the possible suspects to be investigated. We also promote a new way to separate sentences of a description into terms by looking up a term dictionary and involving a statistical theory. An attribute-keyword matrix is then constructed as the semantics model of the investigation system. Besides, a vector space model, term weighting and the composed weighting are used to evaluate the similarities between the boody and criminal model of a criminal record and underlying event. Therefore, police can first investigate the N suspects who commit most similar suspects suggested by the system so as the investigation resources and human emergy can be dragmatically saved. Since thefts often use the same criminal model to steal similar boody.

資料來源:http://handle.ncl.edu.tw/11296/ndltd/10412485750449083224