Chuyên Đề An advanced social network extraction system from the Web

Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We
propose a social network extraction system calledPOLYPHONET, which employs several advanced techniques to extract relations of persons, to
detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information
and obtain Web documents.
Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce
the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms
for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word
relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500
participants. We overview that system. Finally, a novel architecture calledIterative Social Network Miningis proposed. It utilizes simple modules
using Google and is characterized by scalability andrelate–identify processes: identification of each entity and extraction of relations are repeated
to obtain a more precise social network.