Multi-attribute lexicon generation by hyperlinked embedded access structure

Providing a lexicon for all possible postal addresses can support decision making for handwritten address interpretation. The possibility of uncertainty can be reduced by choosing the highest confident record in the provided lexicon as the target postal address. For a large database with multi-attribute records, traditional access methods are not efficient enough to generate the lexicon. This paper proposes a hyperlinked embedded access structure (HEAS) which combines the features of inverted file structure and doubly-chained tree structure with unique data compression schemes. The raw United State Postal Service (USPS) database is organized according to the proposed access structure, and the organized database serves as a knowledge base for interpreting handwritten addresses. The organization cost, storage requirement, and query cost are analyzed and compared to conventional inverted file and doubly-chained tree structures