2 research outputs found

    Knowledge-based document retrieval with application to TEXPROS

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    Document retrieval in an information system is most often accomplished through keyword search. The common technique behind keyword search is indexing. The major drawback of such a search technique is its lack of effectiveness and accuracy. It is very common in a typical keyword search over the Internet to identify hundreds or even thousands of records as the potentially desired records. However, often few of them are relevant to users\u27 interests. This dissertation presents knowledge-based document retrieval architecture with application to TEXPROS. The architecture is based on a dual document model that consists of a document type hierarchy and, a folder organization. Using the knowledge collected during document filing, the search space can be narrowed down significantly. Combining the classical text-based retrieval methods with the knowledge-based retrieval can improve tremendously both search efficiency and effectiveness. With the proposed predicate-based query language, users can more precisely and accurately specify the search criteria and their knowledge about the documents to be retrieved. To assist users formulate a query, a guided search is presented as part of an intelligent user interface. Supported by an intelligent question generator, an inference engine, a question base, and a predicate-based query composer, the guided search collects the most important information known to the user to retrieve the documents that satisfy users\u27 particular interests. A knowledge-based query processing and search engine is presented as the core component in this architecture. Algorithms are developed for the search engine to effectively and efficiently retrieve the documents that match the query. Cache is introduced to speed up the process of query refinement. Theoretical proof and performance analysis are performed to prove the efficiency and effectiveness of this knowledge-based document retrieval approach

    Knowledge-based document filing for texpros

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    This dissertation presents a knowledge-based document filing system for TEXPROS. The requirements of a. personal document processing system are investigated. In order for the system to be used in various application domains, a flexible, dynamic modeling approach is employed by getting the user involved in document modeling. The office documents are described using a dual-model which consists of a document type hierarchy and a folder organization. The document type hierarchy is used to capture the layout, logical and conceptual structures of documents. The folder organization, which is defined by the user, emulates the real world structure for organizing and storing documents in an office environment. The document filing and retrieval are predicate-driven. The user can specify filing criteria and queries in terms of predicates. The predicate specification and folder organization specification are described. It is shown that the new specifications can prevent false drops which happen in the previous approach. The dual models are incorporated by a three-level storage architecture. This storage architecture supports efficient document and information retrieval by limiting the searches to those frame instances of a document type within those folders which appear to be the most similar to the corresponding queries, Specifically, a. three-level retrieval strategy is used in document and information retrieval. Firstly, a knowledge-based query preprocess is applied for efficiently reducing the search space to a small set of frame instances, using the information in the query formula. Secondly, the knowledge and content-based retrieval on the small set of frame instances is applied. Finally, the third level storage provides a platform for adopting potential content-based multimedia document retrieval techniques. A knowledge-based predicate evaluation engine is described for automating document filing. The dissertation presents a knowledge representation model. The knowledge base is dynamicly created by a learning agent, which demonstrates that the notion of flexible and dynamic modeling is applicable. The folder organization is implemented using an agent-based architecture. Each folder is monitored by a filing agent. The basic operations for constructing and reorganizing a folder organization are defined. The dissertation also discusses the cooperation among the filing agents, which is needed for implementing the folder organization
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