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With the rapid increase of XML documents on the web, how to index, store and retrieve these documents has become a very popular and valuable problem. At present, there are two normal ways of retrieving XML documents. One is structure-based retrieval; the other is keyword-based retrieval. However, XML keyword search is
Metacat to improve metadata search in multiple ways: (i) by expanding standard keyword searches with ontology term hierarchies; (ii) by allowing keyword searches to be applied to annotations in addition to traditional meta-data; and (iii) by allowing more structured searches over annotations via ontology terms. We describe
The representation and organization of learning objects should provide the user with easy access to the information in which he or she is interested. Traditionally information retrieval systems support keyword-based searching where the search engine returns a set of documents (or links to the documents). In the
Access to scientific literature information is a very important, as well as time-consuming daily work for scientific researchers. Current methods of retrieval are usually limited to keyword-based searching using information retrieval techniques. In this paper, we present SemreX which implements efficient large-scale
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.