Results 31 to 40 of about 597,067 (301)

PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction [PDF]

Proceedings of the 28th International Conference on Computational Linguistics, 2020
يتعلم تضمين الكلمات القائم على سياق التبعية بشكل مشترك تمثيلات سياق الكلمة والتبعية، وقد ثبتت فعاليته في استخراج المصطلح الجانبي. في هذه الورقة، نقوم بتصميم تضمين الكلمات القائم على التبعية الموضعية (POD) الذي يأخذ في الاعتبار كل من سياق التبعية والسياق الموضعي لاستخراج المصطلح الجانبي. على وجه التحديد، يتم نمذجة السياق الموضعي عبر ترميز الموضع النسبي.
Yichun Yin, Chenguang Wang, Ming Zhang
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ASPECT EXTRACTION IN E-COMMERCE USING LATENT DIRICHLET ALLOCATION (LDA) WITH TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF)

Jurnal Ilmiah Kursor: Menuju Solusi Teknologi Informasi, 2022
Social media is a common thing that people use. Posts or comments found on social media describe someone’s feelings and opinions so there have to be important topics that can be extracted from social media.
Satyawan Agung Nugroho, Fitra A Bachtiar, Randy Cahya Wihandika   +2 more
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Exploring Sequence-to-Sequence Learning in Aspect Term Extraction [PDF]

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019
يهدف استخراج مصطلح الجانب (ATE) إلى تحديد جميع مصطلحات الجانب في الجملة وعادة ما يتم نمذجته كمشكلة وضع العلامات على التسلسل. ومع ذلك، لا يمكن للطرق القائمة على وضع العلامات على التسلسل الاستفادة الكاملة من المعنى العام للجملة بأكملها ولديها قيود في معالجة التبعيات بين التسميات.
Dehong Ma, Sujian Li, Fangzhao Wu, Xing Xie, Houfeng Wang   +4 more
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Design and Implementation of Aspect-Based Sentiment Analysis Task

Computer Sciences & Mathematics Forum, 2023
This paper presents the design and implementation of a deep-learning-based aspect-level sentiment analysis model for the aspect term extraction and sentiment polarity classification of Chinese text comments.
Ningyi Zhang
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Unsupervised Neural Aspect Search with Related Terms Extraction

CoRR, 2020
The tasks of aspect identification and term extraction remain challenging in natural language processing. While supervised methods achieve high scores, it is hard to use them in real-world applications due to the lack of labelled datasets. Unsupervised approaches outperform these methods on several tasks, but it is still a challenge to extract both an ...
Timur Sokhin, Maria Khodorchenko, Nikolay Butakov   +2 more
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Improving sentiment analysis with learning concepts from concept, patterns lexicons and negations

Ain Shams Engineering Journal, 2022
The way of expressing sentiment (−ve/+ve) in the form of textual information depends on the way of thinking of human beings. Identifying aspect extraction and sentiment polarity from written texts is a crucial task.
Anima Pradhan, Manas Ranjan Senapati, Pradip Kumar Sahu   +2 more
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Cross-Domain Aspect Term Extraction Fusing Global and Local Semantics [PDF]

Jisuanji gongcheng
Aspect Term Extraction (ATE) is a critical task in aspect-level sentiment analysis, and extraction and annotation costs are extremely high. When training and testing samples come from different domains, the performance of traditional methods often ...
LIU Dage, YOU Jinguo, GENG Qiqi
doaj   +1 more source

Mining aspects of customer’s review on the social network

Journal of Big Data, 2019
This study represents an efficient method for extracting product aspects from customer reviews and give solutions for inferring aspect ratings and aspect weights.
Tu Nguyen Thi Ngoc, Ha Nguyen Thi Thu, Viet Anh Nguyen   +2 more
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Syntactically Aware Cross-Domain Aspect and Opinion Terms Extraction [PDF]

Proceedings of the 28th International Conference on Computational Linguistics, 2020
A fundamental task of fine-grained sentiment analysis is aspect and opinion terms extraction. Supervised-learning approaches have shown good results for this task; however, they fail to scale across domains where labeled data is lacking. Non pre-trained unsupervised domain adaptation methods that incorporate external linguistic knowledge have proven ...
Oren Pereg, Daniel Korat, Moshe Wasserblat   +2 more
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App2Check @ ATE_ABSITA 2020: Aspect Term Extraction and Aspect-based Sentiment Analysis [PDF]

, 2020
In this paper we describe and present the results of the system we specifically developed and submitted for our participation to the ATE_ABSITA 2020 evaluation campaign on the Aspect Term Extraction (ATE), Aspect-based Sentiment Analysis (ABSA), and Sentiment Analysis (SA) tasks.
Emanuele Di Rosa, Alberto Durante
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