A Generic Data Model for Schema-Driven Design in Information Retrieval Applications

Abstract

Database technology offers design methodologies to rapidly develop and deploy applications that are easy to understand, document and teach. It can be argued that information retrieval (IR) lacks equivalent methodologies. This poster discusses a generic data model, the Probabilistic Object-Oriented Content Model, that facilitates solving complex IR tasks. The model guides how data and queries are represented and how retrieval strategies are built and customised. Application/task-specific schemas can also be derived from the generic model. This eases the process of tailoring search to a specific task by offering a layered architecture and well-defined schema mappings. Different types of knowledge (facts and content) from varying data sources can also be consolidated into the proposed modelling framework. Ultimately, the data model paves the way for discussing IR-tailored design methodologies.