Towards big topic modeling
نویسندگان
چکیده
منابع مشابه
Towards Big Topic Modeling
To solve the big topic modeling problem, we need to reduce both time and space complexities of batch latent Dirichlet allocation (LDA) algorithms. Although parallel LDA algorithms on the multi-processor architecture have low time and space complexities, their communication costs among processors often scale linearly with the vocabulary size and the number of topics, leading to a serious scalabi...
متن کاملTopic Modeling and Classification of Cyberspace Papers Using Text Mining
The global cyberspace networks provide individuals with platforms to can interact, exchange ideas, share information, provide social support, conduct business, create artistic media, play games, engage in political discussions, and many more. The term cyberspace has become a conventional means to describe anything associated with the Internet and the diverse Internet culture. In fact, cyberspac...
متن کاملTowards Conceptual Predictive Modeling for Big Data Framework
Predictive modeling is the process of creating a statistical model from data with the purpose of predicting future behavior. In recent years, the amount of available data has increased exponentially and “Big Data Analysis” is expected to be at the core of most future innovations. Due to the rapid development in the field of data analysis, there is still a lack of consensus on how one should app...
متن کاملModel-Parallel Inference for Big Topic Models
In real world industrial applications of topic modeling, the ability to capture gigantic conceptual space by learning an ultra-high dimensional topical representation, i.e., the so-called “big model”, is becoming the next desideratum after enthusiasms on ”big data”, especially for fine-grained downstream tasks such as online advertising, where good performances are usually achieved by regressio...
متن کاملTopic Modeling using Topics from Many Domains, Lifelong Learning and Big Data
Topic modeling has been commonly used to discover topics from document collections. However, unsupervised models can generate many incoherent topics. To address this problem, several knowledge-based topic models have been proposed to incorporate prior domain knowledge from the user. This work advances this research much further and shows that without any user input, we can mine the prior knowle...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Sciences
سال: 2017
ISSN: 0020-0255
DOI: 10.1016/j.ins.2016.12.014