Corpus driven machine translation approaches such as Phrase-Based Statistical Machine Translation and Example-Based Machine Translation have been successful by using word alignment to find translation fragments for matched source parts in a bilingual training corpus. However, they still cannot properly deal with systematic translation for insertion or deletion words between two distant language...

Reasoning about false beliefs of others develops with age. We present here an ACT-R model in order to show the developmental transitions. These start from a child’s reasoning from his/her own point of view (zero-order) to taking into consideration another agent’s beliefs (first-order), and later to taking into consideration another agent’s beliefs about again other agents’ beliefs (second-order...

This paper proposes a probabilistic partial parser, which we call chunker. The chunker partitions the input sentence into segments. This idea is motivated by the fact that when we read a sentence, we read it chunk by chunk. We train the chunker from Susanne Corpus, which is a modified but shrunk version of Brown Corpus, underlying bi-gram language model. The experiment is evaluated by outside t...

P2P systems provide a scalable solution for distributing large files in a network. The file is split into many chunks, and peers contact other peers to collect missing chunks to eventually complete the entire file. The so-called ‘rare chunk’ phenomenon, where a single chunk becomes rare and prevents peers from completing the file, is a threat to the stability of such systems. Practical systems ...

We have developed an ab initio protein structure prediction method called chunk-TASSER that uses ab initio folded supersecondary structure chunks of a given target as well as threading templates for obtaining contact potentials and distance restraints. The predicted chunks, selected on the basis of a new fragment comparison method, are folded by a fragment insertion method. Fulllength models ar...

The present paper describes a three stage technique to parse Hindi sentences. In the first stage we create a model with the features of head words of each chunk and their dependency relations. Here, the dependency relations are inter-chunk dependency relations. We have experimentally fixed a feature set for learning this model. In the second stage, we extract the intra-chunk dependency relation...

Natural language processing (NLP) is a very hot research domain. One important branch of it is sentence analysis, including Chinese sentence analysis. However, currently, no mature deep analysis theories and techniques are available. An alternative way is to perform shallow parsing on sentences which is very popular in the domain. The chunk identification is a fundamental task for shallow parsi...

This paper describes investigations into using syntactic chunk information as the basis for determining the similarity of candidate texts at the semantic level. Two approaches were considered. The first was a corpus-based method that extracted lexical and semantic features from pairs of chunks from each sentence that were associated through a chunk alignment algorithm. The features were used as...

Unstructured, chunk-based P2P streaming (TV and Video) systems are becoming popular and are subject of intense research. Chunk and peer selection strategies (or scheduling) are among the main driver of performance. This work presents the formal proof that there exist a distributed scheduling strategy which is able to distribute every chunk to all N peers in exactly ⌈log 2 (N)⌉+1 steps. Since th...

Chunk parsing is conceptually appealing but its performance has not been satisfactory for practical use. In this paper we show that chunk parsing can perform significantly better than previously reported by using a simple slidingwindow method and maximum entropy classifiers for phrase recognition in each level of chunking. Experimental results with the Penn Treebank corpus show that our chunk p...