Paper_Ranker.md

Paper Ranker

Introduction

There are some professors that have the same name. In this case, we have difficulties in distinguishing whether a publication is long to a professor. PaperRanker is a class which is used to predict how much possibility there is that a publication is belong to a professor.

Our idea is that we can use some correct publications and coauthor relationship to solve this problem. If a correct coauthor relationship exists in an unsure publication, the possibility that this publication is belong to that professor is much higher.

Definition

def __init__(self, use_clf=False)

Based on the idea that a professor's interest won't change too much, we also try to use NSFC Subject Classifier to help us to predict. If you want to use it, you should set use_clf=True.

Method

label

def label(self, correct_pubs, unsure_pubs, threshold=0.5, trans=youdao_translate)

Introduction

Use iterative algorithm to predict how much possibility there is that a publication is belong to a professor.

Paramters

correct_pubs

A list of this professor's publications. This is a list of dictionaries. And the dictionary should have following fields.

name	Introdcution
title	string, publication title
authors	A list of string, authors
year	integer, publication year

For example:

{
    "title": "Study of quantitative elastography with supersonic shear imaging in the diagnosis of breast tumours",
    "year": 2013,
    "authors": [
        "Zhili Wang",
        "Junlai Li",
        "Min Li",
        "Yan Huang",
        "WenBo Wan",
        "Jie Tang"
    ]
}

unsure_pubs

A list of unsure publications. The format is similar to correct_pubs

threshold

If the possibility of a publication is smaller than this threshold, it won't consider as a correct publication.

trans

In fact, the classifier can only work on Chinese words because of the classification standard and the training data. In order to handle publications in other languages, you need to provide a translation function. It should be able to translate a list of strings in another language to Chinese.

In default, we provide a translator based on youdao api. But you cannot use this translator too often because it is only a free version.

Return value

(a,b), two list of unsure publications and their possibilities. The first one has high possibilities, and the second one has low possibilities.

ranking

def ranking(self, correct_pubs, unsure_pubs, threshold=0.5, trans=youdao_translate)

Introduction

Predict how much possibility there is that a publication is belong to a professor. The algorithm will be used just for one time.

Parameters

Return value

Similar to label

Test

The experiment is based on the publications from Jie Tang (唐杰) and Jie Tang (唐捷) .

I use baidu translation as the translator and set threshold = 0.5

Precision Rate	Recall Rate	F1 Score
0.960	0.705	0.813