发现了一个挖掘科研网的工具:

http://www.arnetminer.org/

是由清华大学计算机系工程研究室开发的，感觉不错

Knowledge Discovering

(19/30)
  • The main goal is to search expertise. (When you type a keyword, the engine output the experts for that keyword).
  • Search result contains expertise's profile.
  • List a lot of topics, show the expertise and events of the topic.
  • Support ranking the authors by different attribute.
  • Support ranking the conference according to impact factor. And showing conference trends.
  • Support paper search. (When you type a keyword, the engine output the paper in right side.

Reference Management

(12/15)
  • Contains reference for some paper.
  • Contains citation for some paper.
  • Contains different format to cite the paper.

Personalization

(0/10)
  • ArnetMiner provides you a personal accounts and personal page. (few people use it).

User Experience

(13/25)
  • The interface of this web page is complex.
  • Too many words and content in each page.
  • The responds time for each query is not very fast. (larger than 1 second).

Socialization

(18/20)
  • Social graph: three relationships between each pair of authors: advisor, advisee, and coauthor.
  • Contains course search, show course and the teacher. (However, some links are out of date)
  • Addition: Social graph can find paths between two different teachers. The interface is good.

Users
  • For students to find their favorite professors.
  • For people evaluate professors according to different rankings.

Total:62.

Details:

As the introduction in ArnetMiner said "ArnetMiner aims to provide comprehensive search and mining services for researcher social networks". It is different from many other academic search such as: Google scholar.

Knowledge Discovering: The main function aims to find a researcher. For example, type Bruce Croft and press Enter. The page show Bruce Croft's profile. The profile contains: positions, affiliation, address, phone, email, homepage, research interest and many othings.

For each researcher, you can find his friends, students or co-authors in right side and find the conferences which he published a lot of papers.

In order to evaluate the professors, you can rank the professors according to different attributes. There are 8 different ranking attributes: H-index, Citation, Uptrend, Activity, Longevity, Diversity, Sociability, and New Star.

For example, we sort the expertise in machine learning area according to H-index:

It shows a list of researchers. Unfortunately, there are some researchers' picture unfound. To find more interest things, you can go through the link: http://arnetminer.org/expertrank

Additionally, it can rank the conference and analysis the authors' nationality distribution. You can go through the link: http://arnetminer.org/rank-conference-bestpaper-homepage.jsp

Reference Management: For each paper, you can find the abstract, reference and cited paper in the ArnetMiner. When you want to cite this paper, it provides a lot of format for you. For example, for paper "Click Chain Model in Web Search", you can cite it by following ways:

This function makes it easy to manage the references of our paper.

Personalization: You can login and create your page. However, I find there is only a few people use this function.

User Experience: The interface of the main function is complex, which contains too many words in one page.

Socialization: As I mentioned above, this engine mainly focus on search research social network. For each researcher, there is a social graph:

You can filter unimportant relationships by the number of co-authored papers. The relationships in different colors have different meanings. However, there are some error relationships.

Recently, there is a new function that is to find the relationship chains between two researchers. It can help us finding a strong recommendation letter.

Users: I think people who use ArnetMiner aim to evaluate the professor according to different evaluation metrics.

Author: Dong Wang

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