Highly Heterogeneous XML Collections: How to Retrieve Precise Results?

خوشه‌بندی فراابتکاری اسناد فارسی اِکس‌اِم‌اِل مبتنی بر شباهت ساختاری و محتوایی

Due to the increasing number of documents, XML, effectively organize these documents in order to retrieve useful information from them is essential. A possible solution is performed on the clustering of XML documents in order to discover knowledge. Clustering XML documents is a key issue of how to measure the similarity between XML documents. Conventional clustering of text documents using a do...

Information Retrieval Systems in XML Based Database – A review

XML the eXtensible Markup Language has emerged as a new standard for data representation and exchange over the Internet. It will become a universal format for data exchange on the Web and that in the near future we will find vast amounts of documents in XML format on the Web. As a result, it has become crucial to sort large collections of XML documents and retrieve relevant information from the...

Vague Content and Structure (VCAS) Retrieval for Document-centric XML Collections

Querying document-centric XML collections with structure conditions improves retrieval precisions. The structures of such XML collections, however, are often too complex for users to fully grasp. Thus, for queries regarding such collections, it is more appropriate to retrieve answers that approximately match the structure and content conditions in these queries, a process also known as vague co...

ArHeX: An Approximate Retrieval System for Highly Heterogeneous XML Document Collections

Approximate Tree Embedding for Querying XML Data

Querying heterogeneous collections of data-centric XML documents requires a combination of database languages and concepts used in information retrieval, in particular similarity search and ranking. In this paper we present an approach to find approximate answers to formal user queries. We reduce the problem of answering queries against XML document collections to the well-known unordered tree ...