Mining social network of conference participants from the Web

In a ubiquitous computing environment, it is desirable to provide a user with information depending on a user\´s situation, such as time, location, user behavior, and social context. At conventions, such as academic conferences and exhibitions, where participants must register in advance, the social context of participants can be extracted from the Web using their names and affiliations without asking the participants many questions. Here, we attempt to extract the social network of participants from the Web, where a node represents a participant and an edge represents the relationship of two participants. Each edge is added using the number of pages retrieved by a search engine which include both participants names. Moreover, each edge has a label such as "coauthors" and "members of the same project" by applying classification rules to the page content. We show an example of the extracted network and make a preliminary evaluation. This network can be used in many information services, such as finding an appropriate introducer or negotiator, and who one should talk to in order to efficiently expand his/her network.