| 摘要 |
A process and system for database storage and retrieval are described along with methods for obtaining semantic profiles from a training text corpus. A neural network (103) is used to extract semantic profiles (109) from text corpus. A new set of documents obtained from the Internet is then submitted for processing to same neural network, which computes the semantic profile representation for these pages using the semantic relations (106) learned fr om profiling the training documents. These semantic profiles are then organized into clusters in order to minimize the time required to answer a query (109) . When a user carries the database, i.e., the set of documents, his or her que ry is similarly transformed into a semantic profile and compared with the semantic profiles of each cluster of documents. The query profile is then compared with each of the documents in the cluster and the documents with th e closest weighted match are returned as search results.
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