In this article, we describe system architecture, preparation of training data and discussion on experimental results of the EIWA group in the NTCIR-10 Patent Translation Task. Our system is combining rule-based machine translation and statistical postediting. The thing about our new system compared with NTCIR-9 PatentMT task is to implement automatic selecting method from multiple translations...

In this paper we describe an unsupervised learning algorithm for automatically training a rule-based part of speech tagger without using a manually tagged corpus. We compare this algorithm to the Baum-Welch algorithm, used for unsupervised training of stochastic taggers. Next, we show a method for combining unsupervised and supervised rule-based training algorithms to create a highly accurate t...

In combinator parsing , the text of parsers resembles BNF notation. We present the basic method, and a number of extensions. We address the special problems presented by white– space, and parsers with separate lexical and syntactic phases. In particular, a combining form for handling the “offside rule” is given. Other extensions to the basic method include an “into” combining form with many use...

In this paper, we propose a new method for measuring the closeness of multiple sets of rules that are combined using Dempster’s rule of combination to improve classification performance. The closeness provides an insight into combining multiple sets of rules in classification − in what circumambience the performance of combinations of some sets of rules using Dempster’s rule is better than that...

In this paper we investigate the lack of reliability and consistency of those binary rule learners in ILP that employ the one-vs-rest binarisation technique when dealing with multi-class domains. We show that we can learn a simple, consistent and reliable multi-class theory by combining the rules of the multiple one-vs-rest theories into one rule list or set. We experimentally show that our pro...

One of the most important internet challenges in coming years will be the introduction of intelligent services and a more personalized environment for user. In this paper web page prediction is presented. We use several classification techniques, namely, Support Vector Machines (SVM), Association Rule mining (ARM), and Markov model in WWW prediction. We proposed a hybrid model by combining two ...

We discuss combining knowledge-based (or rule-based) and statistical part-of-speech taggers. We use two mature taggers, ENGCG and Xerox Tagger, to independently tag the same text and combine the results to produce a fully disambiguated text. In a 27000 word test sample taken from a previously unseen corpus we achieve 98.5 % accuracy. This paper presents the data in detail. We describe the probl...

With the increasing complexity of software, new access control methods have emerged to deal with attributebased authorization. As a standard language for attribute-based access control policies, XACML offers a number of rule and policy combining algorithms to meet different needs of policy composition. Due to their variety and complexity, however, it is not uncommon to apply combining algorithm...

We propose a generic rule induction framework that is informed by syntax from both sides of a parsed parallel corpus, as sets of structural, boundary and labeling related constraints. Factoring syntax in this manner empowers our framework to work with independent annotations coming from multiple resources and not necessarily a single syntactic structure. We then explore the issue of lexical cov...