منابع مشابه
Topic 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 کاملLDA*: A Robust and Large-scale Topic Modeling System
We present LDA∗, a system that has been deployed in one of the largest Internet companies to fulfil their requirements of “topic modeling as an internal service”—relying on thousands of machines, engineers in different sectors submit their data, some are as large as 1.8TB, to LDA∗ and get results back in hours. LDA∗ is motivated by the observation that none of the existing topic modeling system...
متن کاملAutomatic Topic Identification for Large Scale Language Modeling Data Filtering
The paper presents a module for topic identification that is embedded into a complex system for acquisition and storing large volumes of text data from the Web. The module processes each of the acquired data items and assigns keywords to them from a defined topic hierarchy that was developed for this purposes and is also described in the paper. The quality of the topic identification is evaluat...
متن کاملTopic Modeling for Large-Scale Multimedia Analysis and Retrieval
The explosion of multimedia data in social media raises a great demand for developing effective and efficient computational tools to facilitate producing, analyzing, and retrieving large-scale multimedia content. Probabilistic topic models prove to be an effective way to organize large volumes of text documents, while much fewer related models are proposed for other types of unstructured data s...
متن کاملLarge-Scale Hierarchical Topic Models
In the past decade, a number of advances in topic modeling have produced sophisticated models that are capable of generating hierarchies of topics. One challenge for these models is scalability: they are incapable of working at the massive scale of millions of documents and hundreds of thousands of terms. We address this challenge with a technique that learns a hierarchy of topics by iterativel...
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ژورنال
عنوان ژورنال: DEStech Transactions on Computer Science and Engineering
سال: 2018
ISSN: 2475-8841
DOI: 10.12783/dtcse/cimns2017/17424