entity resolution

    Flexible and Efficient Distributed Resolution of Large Entities

    Entity resolution (ER) is a computationally hard problem of data integration scenarios, where database records have to be grouped according to the real-world entities they belong to. In practice these entities may consist of only a few records from different data sources with typos or historical data. In other cases they may contain significantly more records, especially when we search for entities on a higher level of a concept hierarchy than records.

    Entity Resolution with Heavy Indexing

    Entity resolution (ER), or deduplication is a computationally hard problem with O(n2 ) time complexity. We reformulate ER as a search problem, and develop algorithms using efficient indices. Indices can enhance algorithm scalability, facilitate distributed processing, but require additional storage space. We study the performance and tradeoffs between index update and search in ER algorithms, and show that significant performance gain can be obtained by using indices.

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