recommending structure in collaborative semistructured information systems
Semistructured data provides the users of a community-based information system with the flexibility to store information without having to adhere to any predefined, rigid schema. However, such flexibility needs to be used with caution as it can lead to a very heterogeneous data structure and is therefore not feasible in terms of unified data access and search functionality. We present an approach which avoids such proliferation of substructures and provides the inserting user with recommendations, which are responsible for the creation of a commonly used structure. The presented recommendation algorithm adapts the recommendations to the stored information and its structure created by the community.
recommendations structure semistructured data human interaction rdf