Efficient evaluation of relevance feedback algorithms for XML content-based retrieval systems

Purpose – Information retrieval (IR) and feedback in Extensible Markup Language (XML) are rather new fields for researchers; natural questions arise, such as: how good are the feedback algorithms in XML IR? Can they be evaluated with standard evaluation tools? Even though some evaluation methods have been proposed in the literature it is still not clear yet which of them are applicable in the context of XML IR, and which metrics they can be combined with to assess the quality of XML retrieval algorithms that use feedback. This paper aims to elaborate on this.Design/methodology/approach – The efficient evaluation of relevance feedback (RF) algorithms for XML collection posed interesting challenges on the IR and database researchers. The system based on the keyword‐based queries whether on the main query or in the RF processing instead of the XPath and structure query languages which were more complex. For measuring the efficiency of the system, the paper used the extended RF algorithms (residual collection...

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