Tran Xuan Tu

Tran Xuan Tu

Technical Lead - Data Platform

Publications

A Model of Vietnamese Person Named Entity Question Answering System

Published in PACLIC, Bali, Indonesia, 2012

In this paper, we proposed a Vietnamese named entity question answering (QA) model. This model applies an analytical question method using CRF machine learning algorithm combined with two automatic answering strategies: indexed sentences database-based and Google search engine-based. We gathered a Vietnamese question dataset containing about 2000 popular “Who, Whom, Whose” questions to evaluate our question chunking method and QA model. According to experiments, question chunking phase acquired the average F1 score of 92.99%. Equally significant, in our QA evaluation, experimental results illustrated that our approaches were completely reasonable and realistic with 74.63% precision and 87.9% ability to give the answers.

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User Interest Analysis with Hidden Topic in News Recommendation System

Published in IEEE Computer Society Washington, DC, USA, 2010

To take advantage of the Internet - vast but complicated information resources, Recommendation systems help users find out information they need by providing them personalized suggestions. This research area is receiving more and more attention from researchers and used in some famous websites like EBay, Amazon, etc. In this paper, we proposed a Recommendation System for Vietnamese electronic newspaper which uses content-based filtering techniques associating with the attention of users shown in user’s profile. These users’ attentions are determined by inferring a set of common Hidden Topics from the documents which users preferred. Experimental results showed that approach is feasible with positive results and its capabilities for reality development.

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