Abstract : It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer; secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods.
Zhongzhi Shi; Zhaohui Wu; David Leake; Uli Sattler. 8th International Conference on Intelligent Information Processing (IIP), Oct 2014, Hangzhou, China. Springer, IFIP Advances in Information and Communication Technology, AICT-432, pp.96-105, 2014, Intelligent Information Processing VII. 〈10.1007/978-3-662-44980-6_11〉
https://hal.inria.fr/hal-01383321
Contributeur : Hal Ifip
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Soumis le : mardi 18 octobre 2016 - 14:53:44
Dernière modification le : vendredi 3 novembre 2017 - 22:24:06
Baoyuan Qi, Gang Ma, Zhongzhi Shi, Wei Wang. Collecting Valuable Information from Fast Text Streams. Zhongzhi Shi; Zhaohui Wu; David Leake; Uli Sattler. 8th International Conference on Intelligent Information Processing (IIP), Oct 2014, Hangzhou, China. Springer, IFIP Advances in Information and Communication Technology, AICT-432, pp.96-105, 2014, Intelligent Information Processing VII. 〈10.1007/978-3-662-44980-6_11〉. 〈hal-01383321〉
