کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946519 1439290 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cross-language article linking with different knowledge bases using bilingual topic model and translation features
ترجمه فارسی عنوان
مقاله متقابل زبان با پایگاه های مختلف دانش با استفاده از مدل موضوع دو زبانه و ویژگی های ترجمه
کلمات کلیدی
پیوند مقاله متقابل زبان، پیوند کشف، مدل موضوع دو زبانه
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Creating links among online encyclopedia articles in different languages is crucial in the construction and integration of large multilingual knowledge bases. Most research to date has focused on linking among different language versions of Wikipedia, yet other large online encyclopedias in a variety of languages exist. In this work, we present a cross-language article-linking method using a bilingual topic model and translation features based on an SVM model to link articles in English Wikipedia and Chinese Baidu Baike, the most widely used Wiki-like encyclopedia in China. To evaluate our approach, we compile data sets from Baidu Baike articles and their corresponding English Wikipedia articles. The evaluation results show that our approach achieves at most 0.8158 in MRR, outperforming the baseline system by 0.1328 (+19.44%) in MRR. Our method does not heavily depend on linguistic characteristics, and it can be easily extended to generate cross-language article links among different online encyclopedias in other languages.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 111, 1 November 2016, Pages 228-236
نویسندگان
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