Adjacency Matrix Based Full-Text Indexing Models

With the rapid growth of online text information and user accesses, query-processing efficiency has become the major bottleneck of information retrieval (IR) systems. This paper proposes two new full-text indexing models to improve query-processing efficiency of IR systems. By using directed graph to represent text string, the adjacency matrix of text string is introduced. Two approaches are proposed to implement the adjacency matrix of text string, which leads to two new full-text indexing models, i.e., adjacency matrix based inverted file and adjacency matrix based PAT array. Query algorithms for the new models are developed and performance comparisons between the new models and the traditional models are carried out. Experiments over real-world text collections are conducted to validate the effectiveness and efficiency of the new models. The new models can improve query-processing efficiency considerably at the cost of much less amount of extra storage overhead compared to the size of original text database, so are suitable for applications of large-scale text databases.