# Holistic evaluation of XML queries with structural preferences on an annotated strong dataguide

## TL;DR

This paper presents a comprehensive approach for evaluating XML structure preference queries using a three-phase plan, enhancing the effectiveness of retrieving relevant semi-structured data.

## Contribution

It introduces a novel three-phase evaluation plan for structure-based preference queries in XML, combining rewriting, evaluation, and merging techniques.

## Key findings

- Effective evaluation plan for structure preferences in XML
- Improved retrieval of relevant semi-structured data
- Enhanced performance of preference query processing

## Abstract

With the emergence of XML as de facto format for storing and exchanging information over the Internet, the search for ever more innovative and effective techniques for their querying is a major and current concern of the XML database community. Several studies carried out to help solve this problem are mostly oriented towards the evaluation of so-called exact queries which, unfortunately, are likely (especially in the case of semi-structured documents) to yield abundant results (in the case of vague queries) or empty results (in the case of very precise queries). From the observation that users who make requests are not necessarily interested in all possible solutions, but rather in those that are closest to their needs, an important field of research has been opened on the evaluation of preferences queries. In this paper, we propose an approach for the evaluation of such queries, in case the preferences concern the structure of the document. The solution investigated revolves around the proposal of an evaluation plan in three phases: rewriting-evaluation-merge. The rewriting phase makes it possible to obtain, from a partitioning -transformation operation of the initial query, a hierarchical set of preferences path queries which are holistically evaluated in the second phase by an instrumented version of the algorithm TwigStack. The merge phase is the synthesis of the best results.

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Source: https://tomesphere.com/paper/1906.08231