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XML has become an important format for exchange data. Ranking of XML search results directly relates to XML information retrieval performance. Most of the existing ranking models consider words statistical characteristics in the XML document, but they do not consider position of the node a word belongs to. That is to say, all of nodes in XML document have the equal importance. However, different node...
and learn an arbitrary concept by using most of the current search engines, because they provide a list of results according to the input keywords. The proposed approach represents the various relationships between arbitrary concepts as an outline. For example, it is assumed that a user wants information related to an
The growing number of Restful web services available on the web raises a challenging search problem as to how the desired web services should be located. Traditional keyword searching is inaccurate, and its limitations have been noted for several years. We propose a combination method of WADL and a learning ontology
different keywords or entities to form a more comprehensive view. The proposed solution aims to combine social media data and semantic linked data to extract relevant information and capture the relationship among the entities from content shared by the audience. With a targeted audience profiling, company is able to spend
In order to overcome the defects of traditional-method filtering which based on keywords, the OWL text filtering is presented in the semantic Web environment, which makes information filtering, has been raised to the level of semantics. Through distinguishing the information between the title and text, and then
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.