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document databases
The problem of logo recognition is of great interest in the document domain, especially for document databases.
      
Query optimization in XML structured-document databases
      
String techniques for detecting duplicates in document databases
      
A Comparison of Text-Based Methods for Detecting Duplication in Scanned Document Databases
      
This paper presents an experimental evaluation of several text-based methods for detecting duplication in scanned document databases using uncorrected OCR output.
      
This paper discusses an approach for improvement of information retrieval effectiveness from document databases.
      
This paper concentrates on the problem of designing and developing a spoken query retrieval (SQR) system to access large document databases via voice.
      
In this paper, a Context Aware Language Model (CALM) framework allowing information retrieval to large document databases via voice is presented and findings from a research study using the framework will be discussed as well.
      
This paper concentrates on the problem of designing and developing a spoken query retrieval (SQR) system to access large document databases via voice.
      
In this paper, a Context Aware Language Model (CALM) framework allowing information retrieval to large document databases via voice is presented and findings from a research study using the framework will be discussed as well.
      
As the popularity of XML (eXtensible Markup Language) keeps growing rapidly, the management of XML compliant structured-document databases has become a very interesting and compelling research area.
      
Disk storage capacity was substantially increased to accommodate the increased number of E-mail messages, user files, and document databases.
      
Documents were organized into document databases based on the primary source and the month and year of publication.
      
Example problem domains would be analysis of microarray or document databases.
      
For document databases, gCLUTO could assist in the generation of the initial data matrix from a database of documents or from an online query.
      
In this case querying handwritten document databases can be carried out using graphical requests.
      
In Section 4 we describe in detail the process of mining temporal association rules in temporal document databases.
      
In this section we describe in more detail the process of mining temporal association rules in temporal document databases.
      
In this paper we address the problem of automatic selection of Web document databases in a heterogeneous distributed search environment.
      
Most hidden Web data is stored in relational databases, and sometimes in document databases.
      
 

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