LAF: a new XML encoding and indexing strategy for keyword-based XML search

摘要

As a large number of corpuses are represented, stored and published in XML format, how to find useful information from XML databases has become an increasingly important issue. Keyword search enables web users to easily access XML data without the need to learn a structured query language or to study complex data schemas. Most existing indexing strategies for XML keyword search are based upon Dewey encoding. In this paper, we proposed a new encoding method called Level Order and Father (LAF) for XML documents. With LAF encoding, we devised a new index structure, called two-layer LAF inverted index, which can greatly decrease the space complexity compared with Dewey encoding-based inverted index. Furthermore, with two-layer LAF inverted index, we proposed a new keyword query algorithm called Algorithm based on Binary Search (ABS) that can quickly find all Smallest Lowest Common Ancestor. We experimentally evaluate two-layer LAF inverted index and ABS algorithm on four real XML data sets selected from Wikipedia. The experimental results prove the advantages of our index method and querying algorithm. The space consumed by two-layer LAF index is less than half of that consumed by Dewey inverted index. Moreover, ABS is about one to two orders of magnitude faster than the classic Stack algorithm.