کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6926017 1448888 2018 21 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Self-training on refined clause patterns for relation extraction
ترجمه فارسی عنوان
خودآموزی در الگوهای بند تصفیه برای استخراج رابطه
کلمات کلیدی
استخراج رابطه، استخراج اطلاعات باز، الگوریتم خودمراقبتی، تجزیه همگانی، تجزیه وابستگی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing & Management - Volume 54, Issue 4, July 2018, Pages 686-706
نویسندگان
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