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نتیجه جستجو - Latent semantic analysis

تعداد مقالات یافته شده: 5
ردیف عنوان نوع
1 Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis
Word2vec -تحلیل معنایی نهفته مبتنی بر (W2V-LSA) برای مدل سازی موضوع: مطالعه ای در مورد تحلیل روند فناوری بلاکچین-2019
Blockchain has become one of the core technologies in Industry 4.0. To help decision-makers establish action plans based on blockchain, it is an urgent task to analyze trends in blockchain technology. However, most of existing studies on blockchain trend analysis are based on effort demanding full-text investigation or traditional bibliometric methods whose study scope is limited to a frequency-based statistical analysis. Therefore, in this paper, we propose a new topic modeling method calledWord2vec-based Latent Semantic Analysis (W2V-LSA), which is based onWord2vec and Spherical k-means clustering to better capture and represent the context of a corpus. We then used W2V-LSA to perform an annual trend analysis of blockchain research by country and time for 231 abstracts of blockchain-related papers published over the past five years. The performance of the proposed algorithm was compared to Probabilistic LSA, one of the common topic modeling techniques. The experimental results confirmed the usefulness of W2V-LSA in terms of the accuracy and diversity of topics by quantitative and qualitative evaluation. The proposed method can be a competitive alternative for better topic modeling to provide direction for future research in technology trend analysis and it is applicable to various expert systems related to text mining.
Keywords: Trend Analysis | Topic Modeling | Word2vec | Probabilistic Latent Semantic Analysis | Blockchain
مقاله انگلیسی
2 A large-group emergency risk decision method based on data mining of public attribute preferences
یک روش تصمیم گیری ریسک اضطراری گروهی-بزرگ مبتنی بر داده کاوی تنظیمات ویژگی های عمومی-2019
Aiming at the lack of public concern about the attributes of large-group emergency decision making in major emergencies, a large-group emergency risk decision method based on data mining of public attribute preferences is proposed. First, according to historical data from a similar emergency, an attribute-keyword lexicon is established using text mining and latent semantic analysis. Meanwhile, fuzzy association rule mining and a fuzzy cognitive graph are applied to obtain information regarding public opinion about the attributes. Then, a risk measurement model of degree indicators based on information entropy is presented, and according to the linguistic preference for information given by large-group members, the decision risk of large-group members is measured. On this basis, a group member clustering algorithm is constructed to cluster large groups, and then the best alternative is acquired by comparing score function and precise function of the interval intuitionistic fuzzy number. Finally, a case application using historical data is conducted to verify the method’s rationality and feasibility.
Keywords: Large-group | Preferences data mining | Risk measure | Emergency risk decision
مقاله انگلیسی
3 Deep latent factor model for collaborative filtering
مدل فاکتور نهفته عمیق برای فیلتر مشارکتی-2019
Latent factor models have been used widely in collaborative filtering based recommender systems. In re- cent years, deep learning has been successful in solving a wide variety of machine learning problems. Mo- tivated by the success of deep learning, we propose a deeper version of latent factor model. Experiments on benchmark datasets shows that our proposed technique significantly outperforms all state-of-the-art collaborative filtering techniques.
Keywords: Deep learning | Latent semantic analysis | Collaborative filtering | Recommender systems
مقاله انگلیسی
4 Could LSA become a “Bifactor”model? Towards a model with general and group factors
آیا LSA می تواند به یک مدل Bifactor تبدیل شود؟ به سمت یک مدل با عوامل کلی و گروهی-2019
One insufficiently grounded criticism made against Latent Semantic Analysis is that it is impossible to semantically interpret its dimensions. This is not true, as several studies have transformed the latent se- mantic space to interpret them, by means of some methods. One of them is the Inbuilt-Rubric method. Rather than grouping concepts around dimensions, as in Exploratory Factor Analysis based rotation meth- ods, the Inbuilt-Rubric is a method that perform an “a priori”imposition of concepts onto the latent se- mantic space. It uses a confirmatory strategy. This study seeks to propose solutions for two limitations found in the current Inbuilt-Rubric methodology: one solution is inspired by Bifactor Models and the management of common variance of the concepts involved; and the other one is based in randomizing the sequence to perform the process. Both methods outperform the current Inbuilt-Rubric version in rel- evant content detection. The reported improvements can be incorporated into expert systems that use Latent Semantic Analysis and Inbuilt-Rubric in relevant content detection or text classification tasks.
Keywords: Latent semantic analysis | Bifactor model | Distributional semantics | Inbuilt-Rubric method | Rotation | Text assessment
مقاله انگلیسی
5 بهبود خلاصه سازی متن با استفاده از منطق فازی و تحلیل معنایی پنهان
سال انتشار: 2014 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 21
در عصر جدید ، وقتی اطلاعات عظیم در اینترنت دردسترس است ، بسیار مشکل است تا اطلاعات با سرعت و بالاترین دقت استخراج گردد . در اینترنت مطالب زیادی دردسترس است که می توان از آنها اطلاعاتی را کسب کرد و اینکار به مکانیسم مناسبی نیاز دارد . این مشکل با مکانیسم خودکار خلاصه سازی متن قابل رفع شدن است . خلاصه سازی متن فرایند ایجاد نسخه های کوتاه تر از متن اصلی می باشد که شامل اطلاعات مهم می باشد . خلاصه سازی متن به طور گسترده به دو طبقه تقسیم می شود : چکیده و استخراج که برای خلاصه سازی متن بکار می رود . رویکرد ما از روش استخراج بهره گرفته است که مبتنی بر رویکرد استخراج منطق فازی و رویکرد تحلیل معنایی خلاصه سازی متن با استفاده از تحلیل معنایی پنهان می باشد .
کلمات کلیدی : خلاصه سازی متن | منطق فازی | قاعده فازی | تحلیل معنایی پنهان
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