document: POLYPHONET : 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 called POLYPHONET , which employs several advanced techniques to extract relations of persons , detect groups of persons , and 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 networking 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 called Super Social Network Mining is proposed ; it utilizes simple modules using Google and is characterized by scalability and Relate-Identify processes : Identification of each entity and extraction of relations are repeated to obtain a more precise social network .
doc_bio_tags: O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O