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Constructing hierarchical advisors and advisees relationships using web information

This research is aimed to build a social network system for college teachers by retrieving different data sources available on the Internet, the characteristics of the constructed social network are represented in graphic and numeric modes. By applying relationships maintained in the social network, we can find the shortest path between any two researchers or the ego-center social network of any individual teacher according to the input parameters given by a query user.. That is to say we have realized the knowledge map concept for college teachers.
In this research, we focus on searching the advisory relationships between advisors and students. . Because after a Ph.D. student graduated, he/she could be an advisor guiding other students, by applying recursion of advisory relationships ¡A we can construct a multi-level hierarchy of family-tree for a given advisor and the family-tree can be viewed as a whole family-tree and just those non-leaf nodes. We also analyzed some interesting characteristics of the created family-tree¡A compared with the human relationships in our real society to evaluate and explain some phenomena happened in our academic society.
Furthermore, we combine two information of social network and knowledge map for developing the ANIWEB system, providing web-based query functions for users to search teachers¡¦ social network. Two types of query can be applied, one is searching for teacher¡¦s personal information, such as biography, educational background, specialty and NSC projects; the other is searching for social network information about an interested teacher, such as multi-level advisory relationship, co-advisory relationship, ego-center social network and the shortest path between any two teachers.
Users can apply different search patterns for their different needs. For example, a user can first search for those teachers with an expertise of a given research topics, then search for the shortest path from the social network to find out the expert he/she could get in touch.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0616103-152740
Date16 June 2003
CreatorsHsi, Huei-Chan
ContributorsSan-Yih Hwang, Chu-Sing Yang, Nian-Shing Chen
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616103-152740
Rightsunrestricted, Copyright information available at source archive

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