Multi-attribute lexicon generation by hyperlinked embedded access structure

Providing lexicon for all possible postal addresses can support the decision making of interpreting hand-written addresses. 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 hand-written addresses. The organization cost, storage requirement, and query cost are analyzed and compared to conventional inverted file and doubly-chained tree structure.