In this paper we describe a new approach to rewrite rule extraction and analysis, using Minimal Representation Graphs. This approach provides a mechanism for obtaining the smallest possible rule set – within a context-dependent rewrite rule formalism – that describes a set of discrete training data completely, as an indirect approach to obtaining optimal accuracy on an unseen test set. We demon...

This paper presents an effective approach to discard most entries of the rule table for statistical machine translation. The rule table is filtered by monolingual key phrases, which are extracted from source text using a technique based on term extraction. Experiments show that 78% of the rule table is reduced without worsening translation performance. In most cases, our approach results in mea...

This paper proposes a hybrid approach to the design of a compact fuzzy rule-based classi>cation system with a small number of linguistic rules. The proposed approach consists of two procedures: rule extraction from a trained neural network and rule selection by a genetic algorithm. In this paper, we first describe how linguistic rules can be extracted from a multilayer feedforward neural networ...

The paper presents a constructive interpretation for proofs in classical logic of 0 1 sentences and for a witness extraction procedure based on Prawitz's reduction rules.

The method of rule extraction based on differential evolution (DE-Rule) is proposed in this paper. The style of rule is IF-THEN. Connection word is AND in the antecedent of rule. The consequence of rule is class label. The above rule is encoded and expressed to individual in population of differential evolution. Then the population is iterated through differential mutation and binomial crossove...

Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new ru...

This study proposes a knowledge discovery method that uses multilayer perceptron (MLP) based neural rule extraction (NRE) approach for credit risk analysis (CRA) of real-life small and medium enterprises (SMEs) in Turkey. A feature selection and extraction stage is followed by neural classification that produces accurate rule sets. In the first stage, the feature selection is achieved by decisi...

There is a wealth of information about financial systems that is embedded in document collections. In this paper, we focus on a specialized text extraction task for this domain. The objective is to extract mentions of names of financial institutions, or FI names, from financial prospectus documents, and to identify the corresponding real world entities, e.g., by matching against a corpus of suc...