Data retrieval from massive information structures
Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favor semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.
Leader: Alistair Moffat
Staff: Alistair Moffat, Anthony Wirth
Sponsors: Australian Research Council
Computing and Information Systems
Networks and data in society
data structures; Information retrieval; knowledge discovery; large-scale systems