کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4946375 | 1439283 | 2017 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Universal, unsupervised (rule-based), uncovered sentiment analysis
ترجمه فارسی عنوان
جهانی، بدون نظارت (مبتنی بر قانون)، تجزیه و تحلیل احساسات کشف شده
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کلمات کلیدی
تجزیه و تحلیل احساسات، چند زبانه، تجزیه وابستگی، پردازش زبان طبیعی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
We present a novel unsupervised approach for multilingual sentiment analysis driven by compositional syntax-based rules. On the one hand, we exploit some of the main advantages of unsupervised algorithms: (1) the interpretability of their output, in contrast with most supervised models, which behave as a black box and (2) their robustness across different corpora and domains. On the other hand, by introducing the concept of compositional operations and exploiting syntactic information in the form of universal dependencies, we tackle one of their main drawbacks: their rigidity on data that are structured differently depending on the language concerned. Experiments show an improvement both over existing unsupervised methods, and over state-of-the-art supervised models when evaluating outside their corpus of origin. Experiments also show how the same compositional operations can be shared across languages. The system is available at http://www.grupolys.org/software/UUUSA/.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 118, 15 February 2017, Pages 45-55
Journal: Knowledge-Based Systems - Volume 118, 15 February 2017, Pages 45-55
نویسندگان
David Vilares, Carlos Gómez-RodrÃguez, Miguel A. Alonso,