Neo4j Applications - scientific maps

1. Problems

At present, China is already a scientific and technological power, but our research community there are obvious pain point questions:

• Repeat research problem
• Low level of intelligence search technology research and data
• Research and social issues
• Research plagiarism

Neo4j is undoubtedly to solve the above mentioned problems scientific point of pain powerful tool.

2. Create a research mapping model case

(1) Function: This case is used to describe the relationship between researchers, papers, keyword, academic journals.
(2) the implementation of the program.

create
(张教授:研究人员{姓名:"张教授"}),
(李老师:研究人员{姓名:"李老师"}),
(王老师:研究人员{姓名:"王老师"}),
(论文1:论文{论文名:'论文1'}),
(论文2:论文{论文名:'论文2'}),
(论文3:论文{论文名:'论文3'}),
(论文4:论文{论文名:'论文4'}),
(论文5:论文{论文名:'论文5'}),
(论文6:论文{论文名:'论文6'}),
(论文7:论文{论文名:'论文7'}),
(论文8:论文{论文名:'论文8'}),
(学术期刊1:学术期刊{刊名:'学术期刊1'}),
(学术期刊2:学术期刊{刊名:'学术期刊2'}),
(学术期刊3:学术期刊{刊名:'学术期刊3'}),
(关键词1_1:关键词{词名:'关键词1_1'}),
(关键词1_2:关键词{词名:'关键词1_2'}),
(关键词1_3:关键词{词名:'关键词1_3'}),
(关键词2_1:关键词{词名:'关键词2_1'}),
(关键词2_2:关键词{词名:'关键词2_2'}),
(关键词2_3:关键词{词名:'关键词2_3'}),
(关键词3_1:关键词{词名:'关键词3_1'}),
(关键词3_2:关键词{词名:'关键词3_2'}),
(关键词3_3:关键词{词名:'关键词3_3'}),
(张教授)-[:作者]->(论文1),
(张教授)-[:作者]->(论文2),
(张教授)-[:作者]->(论文3),
(张教授)-[:作者]->(论文4),
(张教授)-[:作者]->(论文5),
(张教授)-[:作者]->(论文6),
(张教授)-[:作者]->(论文7),
(张教授)-[:作者]->(论文8),
(李老师)-[:作者]->(论文1),
(李老师)-[:作者]->(论文2),
(王老师)-[:作者]->(论文5),
(王老师)-[:作者]->(论文6),
(论文1)-[:发表]->(学术期刊1),
(论文2)-[:发表]->(学术期刊1),
(论文3)-[:发表]->(学术期刊1),
(论文4)-[:发表]->(学术期刊2),
(论文5)-[:发表]->(学术期刊2),
(论文6)-[:发表]->(学术期刊2),
(论文7)-[:发表]->(学术期刊3),
(论文8)-[:发表]->(学术期刊3),

(论文1)-[:关键词]->(关键词1_1),
(论文1)-[:关键词]->(关键词1_2),
(论文1)-[:关键词]->(关键词1_3),
(论文2)-[:关键词]->(关键词2_1),
(论文2)-[:关键词]->(关键词2_2),
(论文2)-[:关键词]->(关键词2_3),
(论文3)-[:关键词]->(关键词2_3),
(论文4)-[:关键词]->(关键词1_2),
(论文5)-[:关键词]->(关键词3_1),
(论文5)-[:关键词]->(关键词3_2),
(论文5)-[:关键词]->(关键词3_3),
(论文6)-[:关键词]->(关键词2_1),
(论文7)-[:关键词]->(关键词3_1),
(论文8)-[:关键词]->(关键词3_2)
return *

(3) the results

(4) a summary count the number of articles published by the three authors.

Perform the following procedures:

match (p:研究人员)-[a:作者]->(论文) return p.姓名 as 作者姓名,
count(论文) as 发表论文数 order by 发表论文数 desc

FIG execution results are as follows.

3. Document Search

(1) Description of
research literature search each researchers in their daily research work often need to face the problem, but the existing system is often used to retrieve full-text search, full-text search of the benefits of higher accuracy, but there are also more efficient than It is low, and the reliability is not high degree of association.
If you are using Neo4j retrieval, not only can quickly retrieve articles matching the highest degree, it can also have a high correlation with papers retrieved, greatly enriched the diversity of retrieving content.
(2) Function: Create a similar paper map.
(3) the implementation of the program.

create
(论文1:论文图谱{论文名:'论文1'}),
(论文2:论文图谱{论文名:'论文2'}),
(论文3:论文图谱{论文名:'论文3'}),
(论文4:论文图谱{论文名:'论文4'}),
(论文5:论文图谱{论文名:'论文5'}),
(论文6:论文图谱{论文名:'论文6'}),
(论文7:论文图谱{论文名:'论文7'}),
(论文1)-[:相似]->(论文2),
(论文1)-[:相似]->(论文3),
(论文2)-[:相似]->(论文4),
(论文2)-[:相似]->(论文5),
(论文3)-[:相似]->(论文5),
(论文5)-[:相似]->(论文6),
(论文7)-[:相似]->(论文2),
(论文7)-[:相似]->(论文6)
return *

(4) Results of

(5) to find a path between the paper 6 is similar to these two papers papers delivered.

execute program:

match n = allshortestpaths((论文1:论文图谱{论文名:'论文1'})
-[*..6]->(论文6:论文图谱{论文名:'论文6'})) return n;

Results of the

4. Atlas research cooperation

(1) describe demand
as well as an important research in the analysis of maps of the work, that is, research cooperation and collaboration between different research institutions among different researchers. When a certain researchers or research institutions are interested in looking for partners, cooperation can play a larger map supporting role.
(2) Function: Create a knowledge map research cooperation.
(3) the implementation of the program.

create
(作者1:论文作者{作者名:'作者1'}),
(作者2:论文作者{作者名:'作者2'}),
(作者3:论文作者{作者名:'作者3'}),
(作者4:论文作者{作者名:'作者4'}),
(作者5:论文作者{作者名:'作者5'}),
(作者6:论文作者{作者名:'作者6'}),
(作者1)-[:论文合作]->(作者2),
(作者1)-[:论文合作]->(作者3),
(作者2)-[:论文合作]->(作者4),
(作者2)-[:论文合作]->(作者5),
(作者3)-[:论文合作]->(作者5),
(作者5)-[:论文合作]->(作者6)
return *

(4) the results of

(5) to find the shortest path to the two authors.
execute program:

match n =allshortestpaths((作者1:论文作者{作者名:'作者1'})
-[*..6]->(作者5:论文作者{作者名:'作者5'})) return n;

Results of the.