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The methods most heavily used by search engines to answer conjunctive queries on binary relations (such as one associating keywords with web-pages) are based on computing the intersection of postings lists stored as sorted arrays and using variants of binary search. We show that a succinct representation of the binary relation permits much better results, while using less space than traditional methods. We apply our results not only to conjunctive queries on binary relations, but also to queries on semi-structured documents such as XML documents or file-system indexes, using a variant of an adaptive algorithm used to solve conjunctive queries on binary relations. Crown

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In this paper, we consider several static data structure problems in the deterministic cell probe model. We develop a new technique for proving lower bounds for succinct data structures, where the redundancy in the storage can be small compared to the informationtheoretic minimum. In fact, we succeed in matching (up to constant factors) the lower order terms of the existing data structures with the lower order terms provided by our lower bound. Using this technique, we obtain (i) the first lower bound for the problem of searching and retrieval of a substring in text; (ii) a cell probe lower bound for the problem of representing permutation π with queries π(i) and π −1 (i) that matches the lower order term of the existing data structures, and (iii) a lower bound for representing binary matrices that is also matches upper bounds for some set of parameters. The nature of all these problems is that we are to implement two operations that are in a reciprocal relation to each other (search and retrieval, computing forward and inverse element, operations on rows and columns of a matrix). As far as we know, this paper is the first to provide an insight into such problems.