The tremendous increase in documents and easier availability through electronic means has put an insurmountable burden upon organizations using humans to do abstracting. In only a few cases, such as technical and scholarly papers, can the preparation of the abstract be the responsibility of the author. With exponential increases in the number of documents available, high quality abstracts become more important as the demand for finding 'the right document' is also increasing. Thus, it is not surprising that there are efforts underway to develop machine aided methods to help improve the quality of information available to the user and to reduce the time to get the information. One of these efforts is summarization.
Summarization can be more than just abstract.
An abstract is usually thought of as being associated with a single document, but there may be a need to cluster or categorize large groups of documents with similar subject matter with a single summary. Selecting important sentences from a document. Selecting high frequency, meaningful words from a document. Selecting unusual words from a document. Counting repeated word usage to identify important sentences.