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A sequence of queries submitted by a database user within a short period of time may have a single, illuminating explanation. In this paper we consider se- quences of single-record queries, and attempt to guess what information their authors may be trying to accumulate. Query sequences may reflect clandes- tine intentions, where users attempt to avoid direct queries which may disclose their true interests, preferring instead to obtain the same information by means of sequences of smaller, less conspicuous, queries. Sequences of queries may also reflect attempts to circumvent retrieval restrictions, where users attempt to approximate information which is inaccessible, with sequences of legitimate re- quests (in the latter case, our explanations may lead database owners to either tighten access, or, conversely, to reorganize their interfaces to facilitate access). Because the true objective of a sequence may be clouded by the retrieval of spu- rious records, our approach considers all the possible aggregates that a user may accumulate with a sequence, and to rank them, search-engine style, according to their plausibility as retrieval objectives. Our method is probabilistic in nature and postulates that the likelihood that a set of records is the true objective of the user is inverse proportional to the likelihood that this set results from random selection. Our method is shown to have good performance even in the presence of noise (spurious records) as high as 40-50%.

Why is This User Asking So Many Questions? Explaining Sequences of Queries