Abstract: A method for implementing a collaborative training and learning system on a computer system accessible to a plurality of remote users through a computer network includes (a) submitting questions, (b) combining the questions to provide a test, (c) administering the test to a group of students, and (d) computing a power score for each question.

Abstract: A method and apparatus for implementing a collaborative training and learning system on a computer system accessible to a plurality of remote users through a computer network includes (a) means for displaying at a user site at least one template which includes a question field, an answer field, a discussion field, a rationale field and a references field, (b) means for inputting user-data including a user-defined question to be included in a predetermined area of the template, (c) means for storing the user-data in a predetermined field of a database, (d) means for retrieving the user-data from the database and for displaying the template and the user-data on a display of the computer system, and (e) means for collaborating with other users of the system.

Abstract: On the World Wide Web, and other interactive media, it is possible to show different ads to different people who are simultaneously viewing the same content. This invention is based on the fact that people who have shown a tendency for similar likes and dislikes in the past will show a tendency for such similarities in the future. Those people who strongly display such similarities with respect to a particular person ("the subject") are referred to as that person's "community." If the members of a subject's community tend to click on a particular Web ad, then it is likely that the subject will also tend to click on that ad. This invention combines techniques for: determining the subject's community, and determining which ads to show based on characteristics of the subject's community. The information used to determine whether a given individual should be in the subject's community is gleaned from the individual's activities in the interactive medium.

Abstract: An automated collaborative filtering (ACF) system for recommending at least one item to a first user based on similarity in preference of the user as compared with other users. The ACF system stores rating data for items provided by users of the system. Upon request of the first user, the system determines similarity values for the first user as compared with other users that have provided rating data for items that the first user has also rated. Based on the similarity values, a subgroup of users is selected that is then used to provide recommendations to the first user.