基于主题建模的海量文献挖掘
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attention !
Review the topics and retraining
Search documents related to specific topic
Review abstract
Try PyTM Now!
pytm-v0.1.0.rar FTP /share/link?shareid=10 63985988&uk=3474053942 Sina weibo: BloodD
2. What is topic model? 3. What can PyTM do?
face recognition • ～8500 papers
tools
• Machine learning
targets
• Easy research
We want to handle the mass documents with a series of automatic analysis tool.
The topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. (Wiki) In general, we can mining the latent structure of the text corpus. (一般来说，主题建模可以帮助我们从文本资料中，挖掘出潜在的语义结构， 称为主题；简单的说，主题建模可以将文本资料进行自动的聚类，并且为每 一类附上主题的标签。)
By do topic modeling, we can find which words often appear together in documents and we could define them as a topic.
FFA
OFA
What can PyTM do?
Training the topics
报告人：党晓彬 神经影像计算小组@刘嘉实验室
National Key Laboratory of Cognitive Neuroscience and Learning ，Beijing Normal University (BNU)
1. Mass document data brings trouble!
Conclusion
1. We hope the computer could truly understand the document and satisfy our need. 2. Topic modeling is a popular tool in machine learning field, and powerful to mining the latent semantic structure. 3. Our tool can make modeling more convenient and yield insight into relative field research.
Review the topics and retraining
Search documents related to specific topic
Review abstract
Try PyTM Now!
pytm-v0.1.0.rar FTP /share/link?shareid=10 63985988&uk=3474053942 Sina weibo: BloodD
2. What is topic model? 3. What can PyTM do?
face recognition • ～8500 papers
tools
• Machine learning
targets
• Easy research
We want to handle the mass documents with a series of automatic analysis tool.
The topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. (Wiki) In general, we can mining the latent structure of the text corpus. (一般来说，主题建模可以帮助我们从文本资料中，挖掘出潜在的语义结构， 称为主题；简单的说，主题建模可以将文本资料进行自动的聚类，并且为每 一类附上主题的标签。)
By do topic modeling, we can find which words often appear together in documents and we could define them as a topic.
FFA
OFA
What can PyTM do?
Training the topics
报告人：党晓彬 神经影像计算小组@刘嘉实验室
National Key Laboratory of Cognitive Neuroscience and Learning ，Beijing Normal University (BNU)
1. Mass document data brings trouble!
Conclusion
1. We hope the computer could truly understand the document and satisfy our need. 2. Topic modeling is a popular tool in machine learning field, and powerful to mining the latent semantic structure. 3. Our tool can make modeling more convenient and yield insight into relative field research.