XML retrieval, or XML information retrieval, is the content-based retrieval of documents structured with XML. As such it is used for computing relevance of XML documents.
Queries
Most XML retrieval approaches do so based on techniques from the information retrieval area, e.g. by computing the similarity between a query consisting of keywords and the document. However, in XML-Retrieval the query can also contain structuralhints. So-called "content and structure" queries enable users to specify what structure the requested content can or must have.
Exploiting XML structure
Taking advantage of the self-describing structure of XML documents can improve the search for XML documents significantly. This includes the use of CAS queries, the weighting of different XML elements differently and the focused retrieval of subdocuments.
Ranking
Ranking in XML-Retrieval can incorporate both content relevance and structural similarity, which is the resemblance between the structure given in the query and the structure of the document. Also, the retrieval units resulting from an XML query may not always be entire documents, but can be any deeply nested XML elements, i.e. dynamic documents. The aim is to find the smallest retrieval unit that is highly relevant. Relevance can be defined according to the notion of specificity, which is the extent to which a retrieval unit focuses on the topic of request.
An overview of two potential approaches is available. The INitiative for the Evaluation of XML-Retrieval was founded in 2002 and provides a platform for evaluating such algorithms. Three different areas influence XML-Retrieval:
s such as the W3C standard XQuery supply complex queries, but only look for exact matches. Therefore, they need to be extended to allow for vague search with relevance computing. Most XML-centered approaches imply a quite exact knowledge of the documents' schemas.
Databases
Classic database systems have adopted the possibility to storesemi-structured data and resulted in the development of XML databases. Often, they are very formal, concentrate more on searching than on ranking, and are used by experienced users able to formulate complex queries.
Information retrieval
Classic information retrieval models such as the vector space model provide relevance ranking, but do not include document structure; only flat queries are supported. Also, they apply a static document concept, so retrieval units usually are entire documents. They can be extended to consider structural information and dynamic document retrieval. Examples for approaches extending the vector space models are available: they use document subtrees as dimensions of the vector space.
Data-centric XML datasets
For data-centric XML datasets, the unique and distinctkeyword searchmethod, namely, XDMA for XML databases is designed and developed based dual indexing and mutual summation.
