文章基本信息

标题：Author Verification Using a Semantic Space Model
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作者：Ángel Hernández-Castañeda ; Hiram Calvo
期刊名称：Computación y Sistemas
印刷版ISSN：1405-5546
出版年度：2017
卷号：21
期号：2
页码：167-179
语种：English
出版社：Instituto Politécnico Nacional
其他摘要：In this work we propose to solve the author verification probl em using a semantic space model t h rough L atent Dirichlet Allocation (LDA ). We experiment with the corpus used in the author identification task s at PAN 201 4 and PAN 201 5. T h e s e dataset s consist of subsets in the following languages: English, Spanish, Dutch and Greek. Each problem contained in these corpora is formed by one to five known documents which were written by one author and one unknown document. The task is to predict whether the unknown document was written by the author who wrote the known documents. We processed the documents in the dataset and captured the fingerpr int of authors by generating a probabilistic distribution of words in the documents. In PAN 2015 classification, we achieved 81.6%, 75.4%, 74.1%, 67.1% accuracy for each English, Spanish, Dutch and Greek subset respectively. In particular for the English s ubset, w e outreached the best result reported in both competitions .
其他关键词：Author verification; semantic space model; cross-genre; cross-topic; latent Dirichlet allocation.