Abstract: The present invention discloses a method and system for classifying articles. The present invention can be not only capable of distinguishing the type of the article but also novelty to generate an overview article automatically in accordance with the initial prepared keyword combination or articles. Furthermore, the overview article described above comprises a representative topic corresponding to the content of the initial prepared articles, wherein the representative topic is also able to identify the field of the articles. Accordingly, by the said overview article, the present invention is capable of decreasing the time required to understand the spirit and the technical aspect of the articles so as to solve the long lasted problem of the prior art.

Abstract: A hot video prediction system is provided. A video comments database stores video comments submitted by a plurality of users. A user social network constructor establishes a user social network according to the video comments. When new comments of a new video are received, a hot video predictor uses the user social network to determine a similar theme between the new video and hot videos that have been hot for a period of time, and predicts whether the new video will become popular accordingly. A social network adaptor checks the prediction, and modifies the user social network accordingly.

Abstract: A conflict of interest detection system is provided. A data extractor retrieves a document and extracts author, title, and date information. A co-authorship finder finds out co-author relation among documents. A relevant group cluster identifies a key researcher in a particular field, and groups researchers connected to the key researcher as a group. A potential link finder identifies researchers who may have co-author relation. A relation filter filters out couples having weaker relation from the group having co-author relation. The filtered co-author relation data is then stored as a conflict of interest list.

Abstract: A hot video prediction system is provided. A video comments database stores video comments submitted by a plurality of users. A user social network constructor establishes a user social network according to the video comments. When new comments of a new video are received, a hot video predictor uses the user social network to determine a similar theme between the new video and hot videos that have been hot for a period of time, and predicts whether the new video will become popular accordingly. A social network adaptor checks the prediction, and modifies the user social network accordingly.