This paper presents a system which detects and corrects morpho-syntactic errors in Dutch texts. It includes a spelling corrector and a shift-reduce parser for Augmented Context-free Grammars. The spelling corrector is based on trigram and triphone analysis. The parser is an extension of the well-known Tomita algorithm (Tomita, 1986). The parser interacts with the spelling corrector and handles ...

Map/Reduce is a popular parallel processing framework for data intensive computing. For overlapping the Map task’s execution phase and the Reduce task’s intermediate data fetching and merging phase, existing Map/Reduce schedulers always pre-launch the Reduce task at the specific threshold where its map tasks have been launched, and this pattern incurs the occupation of the consuming resources o...

Map/Reduce approach has been popular in order to compute huge volumes of data since Google implemented its platform on Google Distributed File Systems (GFS) and then Amazon Web Service (AWS) provides its services with Apache Hadoop platform. Map/Reduce motivates to redesign and convert the existing sequential algorithms to Map/Reduce algorithms for big data so that the paper presents Market Bas...

The introduction of dynamic oracles has considerably improved the accuracy of greedy transition-based dependency parsers, without sacrificing parsing efficiency. However, this enhancement is limited to projective parsing, and dynamic oracles have not yet been implemented for parsers supporting non-projectivity. In this paper we introduce the first such oracle, for a non-projective parser based ...

This paper proposes a method to improve shift-reduce constituency parsing by using lexical dependencies. The lexical dependency information is obtained from a large amount of auto-parsed data that is generated by a baseline shift-reduce parser on unlabeled data. We then incorporate a set of novel features defined on this information into the shift-reduce parsing model. The features can help to ...

As the web, social networking, and smartphone application have been popular, the data has grown drastically everyday. Thus, such data is called Big Data. Google met Big Data earlier than others and recognized the importance of the storage and computation of Big Data. Thus, Google implemented its parallel computing platform with Map/Reduce approach on Google Distributed File Systems (GFS) in ord...