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 favour semantically local data, giving results th ....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 favour 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.Read moreRead less
Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Hig ....Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Higher query throughput and reduced storage load will benefit providers though reduced hardware and electricity costs, and will benefit society through better access to information, enhanced opportunities to connect and collaborate, and greater long-term scalability as on-line resources continue to multiply.Read moreRead less
Mining multi-typed and dynamic graphs. Large volumes of data collected nowadays from real-world applications are often represented as graphs. The nodes and the edges of such graphs represent different types of entities and interactions, and they have time information. This project will develop algorithms that mine efficiently such multi-typed and dynamic graphs.