This lecture introduces systematically into the problem of managing
large data collections in peer-to-peer systems. Search over large
datasets has always been a key problem in peer-to-peer systems and
the peer-to-peer paradigm has incited novel directions in the field
of data management. This resulted in many novel peer-to-peer data
management concepts and algorithms, for supporting data management
tasks in a wider sense, including data integration, document
management and text retrieval. The lecture covers four different
types of peer-to-peer data management systems that are
characterized by the type of data they manage and the search
capabilities they support. The first type are structured
peer-to-peer data management systems which support structured query
capabilities for standard data models. The second type are
peer-to-peer data integration systems for querying of heterogeneous
databases without requiring a common global schema. The third type
are peer-to-peer document retrieval systems that enable document
search based both on the textual content and the document
structure. Finally, we introduce semantic overlay networks, which
support similarity search on information represented in
hierarchically organized and multi-dimensional semantic spaces.
Topics that go beyond data representation and search are summarized
at the end of the lecture. Table of Contents: Introduction /
Structured Peer-to-Peer Databases / Peer-to-peer Data Integration /
Peer-to-peer Retrieval / Semantic Overlay Networks / Conclusion
General
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