Summarization from Medical Documents: A Survey <s> Introduction <s> A series of information retrieval experiments was carried out with a computer installed in a medical practice setting for relatively inexperienced physician end-users. Using a commercial MEDLINE product based on the vector space model, these physicians searched just as effectively as more experienced searchers using Boolean searching. The results of this experiment were subsequently used to create a new large medical test collection, which was used in experiments with the SMART retrieval system to obtain baseline performance data as well as compare SMART with the other searchers. <s> BIB001 </s> Summarization from Medical Documents: A Survey <s> Introduction <s> 1. SYSTEM TECHNICAL DESCRIPTION The ClassMiner system demonstrates a fully implemented tool for scalable video skimming and summarization. The key technology in the system is the integrated medical video content structure and events mining process, which was presented in a paper at the SIGMOD workshop on Data Mining and Knowledge Discovery [1]. As the system architecture in Fig. 1 indicates, we first apply a general video shot segmentation and key-frame selection scheme to parse the video stream into physical units. Then, the video group detection, scene detection and clustering strategies are executed to mine the video content structure. Various visual and audio feature processing techniques are utilized to detect some semantic cues, such as slides, face and speaker changes, etc. within the video, and these detection results are joined together to mine three types of events (presentation, dialog, clinical operation) from the detected video scenes. Finally, a scalable video skimming and summarization tool is constructed based on the mined video content structure and event information to help the user visualize and access video content. <s> BIB002
New technologies, such as high-speed networks and inexpensive massive storage, along with the remarkable growth of the Internet, have led to an enormous increase in the amount and availability of on-line documents. This is also the case for medical information, which is now available from a variety of sources. However, information is only valuable to the extent that it is accessible, easily retrieved and concerns the personal interests of the user. The growing volume of data, the lack of structured information, and the information diversity have made information and knowledge management a real challenge towards the effort to support the medical society. It has been realized that added value is not gained merely through larger quantities of data, but through easier access to the required information at the right time and in the most suitable form. Thus, there is a strong need for improved means of facilitating information access. The medical domain suffers particularly from the problem of information overload since it is crucial for physicians and researchers in medicine and biology to have quick and efficient access to up-to-date information according to their interests and needs. Considering, for instance, the scientific medical articles, [1, p 38] BIB002 and cardiothoracic surgery BIB001 ; and over 1000 journals in the more gen-