|Various useful information and knowledge exist in a community. But these information or knowledge are held by only a few persons, they aren't make use of them fully. Recent years, many people study knowledge management: how to use knowledge in a community.
We regard files on each computer as knowledge and develop Papits for sharing files on a community. Various technologies are required for developing Papits such as Information Retrieval and Information Recommendation. We are developing such technology through deveoping Papits.
We are developing Papits: knowledge sharing support system to make people in a community promote sharing research information or knowledge. We needs much information to proceed research activity. But we have limited time for it. So, we must collect information effectively. People usually look for research information from papers, books or WWW. But it takes a long time to find suitable information bacause of the information overloads. Those who belong to a same community are doing similar or related activity. They collect same or similar information one another. It is worthwhile to share these information in a community. Usually, we hold collected information or knowledge about research activity as files on a hard disk(HD). So far we use file sharing function such as NFS or AppleShare for this problem. But it is difficult to find files suitable for user's request. Users say, "Who has a information I need?" or "Where is there suitable information?" Papits makes it easy to find shared information or knowledge in a community. Users can find information from not only each local disk on a network but also WWW or other information source transparently. Moreover Papits provide information recommendation function to make incentive for a use of system higher.
Papits uses Sherlock and Web sharing function for constructing information sharing environment in a community. These are MacOS's standard function for searching local files and sharing files on the local HD by Web. Papits collects each users' file information through CGI. So users aren't basically aware of the use of system. When CGI script receives search query, CGI script sends file search request to Sherlock through AppleEvent and returns results receiving from Sherlock to requested host. Papits collects all users' file information autonomously. Papits arranges these information based on keywords and so on. Users can view the file list and files related to the user or selected file through Papits. Moreover Papits models each users' preference or interesting topic and constructs user profiles. Papits provides various service based on the user profile such as Know Who search and Information Recommendation function. Papits has Information Coolection agent that autonomously collects information from WWW. Information Collection agent collects information from WWW based on user profiles. Information Collecting agent looks like one user of Papits. So collected information are available through Papits by the same way.
For developing Papits, various technologies are needed. We are developing each factor technologies through Papits development.
[ Information Retrieval | Information Recommendation ]