Data Set Used
For the task of turning a natural language question into an explicit intermediate representation of the complexity in question answering systems, all published works so far use rule-based approach to the best of our knowledge. We believe it is because of the complexity of the representation and the variety of question types and also there are no publicly… (More)
This paper describes our robust, easy-to-use and language independent toolkit namely RDRPOSTagger which employs an error-driven approach to automatically construct a Single Classification Ripple Down Rules tree of transformation rules for POS tagging task. During the demonstration session, we will run the tagger on data sets in 15 different languages.
This paper presents a new approach to learn a rule based system for the task of part of speech tagging. Our approach is based on an incremental knowledge acquisition methodology where rules are stored in an exception-structure and new rules are only added to correct errors of existing rules; thus allowing systematic control of interaction between rules.… (More)
In this paper, we present a study applying reject option to build a two-stage sentiment polarity classification system. We construct a Naive Bayes classifier at the first stage and a Support Vector Machine at the second stage, in which documents rejected at the first stage are forwarded to be classified at the second stage. The obtained accuracies are… (More)
We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while… (More)
This paper presents a new conversion method to automatically transform a constituent-based Vietnamese Treebank into dependency trees. On a dependency Treebank created according to our new approach, we examine two state-of-the-art dependency parsers: the MSTParser and the MaltParser. Experiments show that the MSTParser outperforms the MaltParser. To the best… (More)
Recent years have witnessed a new trend of building ontology-based question answering systems. These systems use semantic web information to produce more precise answers to users' queries. However, these systems are mostly designed for English. In this paper, we introduce an ontology-based question answering system named KbQAS which, to the best of our… (More)
—Ontologies have served as a knowledge representation about the whole world or some part of it. Building ontologies is a challenging and active research area. Manually constructed Ontologies often have higher quality than the ones created by automatic or semi-automatic approaches but they tend to be more applicable to small domains. Automatic approaches are… (More)
We present the first ontology-based Vietnamese QA system KbQAS where a new knowledge acquisition approach for analyzing English and Viet-namese questions is integrated.
In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task. Our approach is based on an incremen-tal knowledge acquisition method where rules are stored in an exception structure and new rules are only added to correct the errors of existing rules; thus allowing systematic control of the… (More)