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What is AMiner Open?

AMiner Open is an open source community who focuses on developing and publishing elegant algorithms, models and tools for science big data mining and knowledge intelligence with AMiner open resources. Welcome to test, download and use any resource here. Looking forward your join!

Prediction API
Introduction?
AMiner Prediction API is a toolkit for science data prediction, such as scholar portrait property prediction. The toolkit aims to utilize science data and machine learning algorithms to provide more intelligent functionality for global researchers. All algorithms and models which the toolkit uses are derived from AMiner.
https://github.com/AMinerOpen/prediction_api
Online Demo
name description url parameters method
name description
NSFC Subject Classifier Classify which subjects the publications belong to. https://innovaapi.aminer.cn/tools/v1/predict/nsfc titles The titles of publications. POST
Get a professor's research interests. https://innovaapi.aminer.cn/tools/v1/predict/nsfc/person pid The professor's id in AMiner. GET
NSFC AI Subject Classifier Get the classification of the keywords and a subject tree. https://innovaapi.aminer.cn/tools/v1/predict/nsfc/ai words Keywords. POST
JobHopping Prediction Predict where a professor will job-hop. https://innovaapi.aminer.cn/tools/v1/predict/career org_name The professor's organization. GET
per_name The professor's name.
Gender Prediction Predict a person's gender. https://innovaapi.aminer.cn/tools/v1/predict/gender name The person's name. GET
org The person's organization.
Expert Recommendation Recommend some experts in the given field. https://innovaapi.aminer.cn/tools/v1/predict/experts num The number of experts POST
text Field
Homepage Paper Crawler Crawl personal homepage papers https://innovaapi.aminer.cn/tools/v1/crawl/homepage/papers url The link of homepage POST
Get Started
An example
            nsfc= Classifier()
            pub_titles = ['基于多通道卷积神经网络的中文微博情感分析']
            subject = nsfc.classify(pub_titles)
            
Result
{
            'level1': [
                {'code': 'F02', 'name': '计算机科学', 'p': 0.9745969772338867},
                {'code': 'F01', 'name': '电子学与信息系统', 'p': 0.02385014481842518},
                {'code': 'B05', 'name': '分析化学', 'p': 0.0005464374553412199},
            ], 
            'level2': [
                {'code': 'F0206', 'name': '自然语言理解与机器翻译', 'p': 0.8545559048652649},
                {'code': 'F0205', 'name': '计算机应用技术', 'p': 0.08089018613100052},
                {'code': 'F0305', 'name': '人工智能与知识工程', 'p': 0.023599255830049515},
            ], 
            'level3': [
                {'code': 'F020601', 'name': '计算语言学', 'p': 0.9999170303344727},
                {'code': 'F020504', 'name': '生物信息计算', 'p': 4.625070505426265e-05},
                {'code': 'F020506', 'name': '人机界面技术', 'p': 2.3111495465855114e-05},
            ]
}

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