D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. of 5th SODA, pp. 251--259, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....by Minsky and Papert in 1969 [10] in which they asked if there is a data structure that supports fast d queries. The cases of small d and large d for this problem seem to require different techniques for their solutions. The case when d is small was studied by Yao and Yao [14] Dolev et al. [5, 6] and Greene et al. 7] have made some progress when d is relatively large. There are efficient algorithms only when d = 1; proposed by Brodal and Venkadesh [3] Yao and Yao [14] and Brodal and Gasieniec [2] The small d case has applications in password security [9] Searching biological sequence ....

D. Dolev, Y. Harari, N. Linial, N. Nisan and M. Parnas. Neighborhood preserving hashing and approximate queries. Proceedings of the Fifth ACM SODA, 1994.

....work was done while visiting BRICS at the University of Aarhus. Preprint submitted to Elsevier Preprint 9 May 2000 query string q, determine if there is a string in S within Hamming distance d of q. To date, no ecient solutions are known for this problem for arbitrary n; m and d. Dolev et al. [3,4] and Greene, Parnas and Yao [6] made some progress on the problem for the case when d is large. Manber and Wu [8] considered applications to password security and spellchecking of large les. The theoretical study of the problem for small d was started by Yao and Yao [12] who considered the case ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. 5th ACM-SIAM Symposium on Discrete Algorithms, pages 251-259, 1994.

....of Technology and Computer Science, Tata Institute of Fundamental Research, Mumbai 400005, India, email: venkat tcs.tifr.res.in. This work was done while visiting BRICS at the University of Aarhus. 1 To date, no e#cient solutions are known for this problem for arbitrary n, m and d. Dolev et al. [2, 3] and Greene, Parnas and Yao [5] made some progress on the problem for the case when d is large. Manber and Wu [7] considered applications to password security and spellchecking of large files. The theoretical study of the problem for small d was started by Yao and Yao [11] who considered the ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. 5th ACM-SIAM Symposium on Discrete Algorithms, pages 251--259, 1994.

....it imposes on the way that the data can be represented and manipulated. It is not clear for example that this model can be used for the representation of hashing schemes. 8. 3 The bucketing model A model oriented towards the study of hashing schemes is the model introduced by Dolev et al. [35, 34], which we shall refer to as the bucketing model. Let D be a set of words (dictionary) of length d over an alphabet Sigma. The authors consider algorithms that map the dictionary D onto a set of m buckets fB 1 ; B 2 ; Bm g, such that each word is mapped onto one or more buckets. We consider ....

....the same bucket; therefore, the bucket contains many irrelevant words, resulting in large query time. In the extreme cases the authors show that if TA = O(1) then SA = Omega Gamma N ) and if SA = O(1) then TA = Omega Gamma p N ) The last lower bound is improved to Omega Gamma N =4 ) in [34]. The proof uses the idea of ( k) coloring: we try to color the vertices of the cube Sigma d , such that the neighborhood of any point is colored using at most k colors. Each color corresponds to a bucket. The bound on the number of colors gives a bound on the size of the sequence S q . The ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proceedings of the fifth annual ACM-SIAM Symposium on Discrete Algorithms, pages 251--259, 1994.

....the Grigoriev lower bound is not applicable for the case of finite domains such as the Hamming cube. A model which does capture hashing and more combinatorial settings is introduced in Rivest [43] and further developed in Dolev, Harari and Parnas [19] and Dolev, Harari, Linial, Nisan and Parnas [20]. Rivest studies the all partial match problem and Dolev et al. study the all neighbor problem where for each problem all database points satisfying the query must be found. In this model, each database point is hashed to a bucket and interesting tradeoffs are established between the number of ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. of 5th SODA, pp. 251--259, 1994.

....log n, and another algorithm with preprocessing polynomial in d, ffl, and n but with query time O(n d log 3 n) The latter improves the O(dn) time bound of the brute force algorithm. For the Hamming space f0; 1g d , Dolev, Harari, and Parnas [25] and Dolev, Harari, Linial, Nisan, and Parnas [24] gave algorithms for retrieving all points within distance r of the query q. Unfortunately, for arbitrary r, these algorithms are exponential either in query time or preprocessing. Greene, Parnas, and Yao [38] present a scheme which, for binary data chosen uniformly at random, retrieves all ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In: Proceedings of the Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 1994, pp. 251--259.

....problem of answering d queries, i.e. for a binary query string ff of length m to decide if there is a string in W with at most Hamming distance d of ff. Minsky and Papert originally raised this problem in [80] Recently a sequence of papers have considered how to solve this problem efficiently [41, 42, 59, 74, 112]. Manber and Wu [74] considered the application of approximate dictionary queries to password security and spelling correction of bibliographic files. Dolev et al. 41, 42] and Greene, Parnas and Yao [59] considered approximate dictionary queries for the case where d is large. The initial effort ....

....raised this problem in [80] Recently a sequence of papers have considered how to solve this problem efficiently [41, 42, 59, 74, 112] Manber and Wu [74] considered the application of approximate dictionary queries to password security and spelling correction of bibliographic files. Dolev et al. [41, 42] and Greene, Parnas and Yao [59] considered approximate dictionary queries for the case where d is large. The initial effort towards a theoretical study of the small d case was given by Yao and Yao in [112] They present for the case d = 1 a data structure supporting queries in time O(m log log ....

[Article contains additional citation context not shown here]

Danny Dolev, Yuval Harari, Nathan Linial, Noam Nisan, and Michael Parnas. Neighborhood preserving hashing and approximate queries. In Proc. 5th ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 251--259, 1994.

....that increase the distance by some bounded amount (d or p d depending on the metric) These results are not useful for approximate nearest neighbor search as they can increase a very small distance ffi to something which is much larger than (1 ffl)ffi. The constructions of Dolev et al. [13, 12] map all elements at distance at most to close images. This is also not useful for us, as the construction time is exponential in . Our methods. Our data structure and search algorithm for the hypercube is based on an inner product test. Similar ideas have been used in a cryptographic context ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. Proc. of 5th SODA, pp. 251--259, 1994.

....the Grigoriev lower bound is not applicable for the case of finite domains such as the Hamming cube. A model which does capture hashing and more combinatorial settings is introduced in Rivest [41] and further developed in Dolev, Harari and Parnas [18] and Dolev, Harari, Linial, Nisan and Parnas [19]. Rivest studies the all partial match problem and Dolev et al. study the all neighbor problem where for each problem all database points satisfying the query must be found. In this model, each database point is hashed to a bucket and interesting tradeoffs are established between the number of ....

D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. of 5th SODA, pp. 251--259, 1994.

....in answering d queries, i.e. for any query string ff 2 f0; 1g m to decide if there is a string w i in W with at most Hamming distance d of ff. Minsky and Papert originally raised this problem in [12] Recently a sequence of papers have considered how to solve this problem efficiently [4, 5, 9, 11, 15]. Manber and Wu [11] considered the application of approximate dictionary queries to password security and spelling correction of bibliographic files. Their method is based on Bloom filters [2] and uses hashing techniques. Dolev et al. 4, 5] and Greene, Parnas and Yao [9] considered approximate ....

....how to solve this problem efficiently [4, 5, 9, 11, 15] Manber and Wu [11] considered the application of approximate dictionary queries to password security and spelling correction of bibliographic files. Their method is based on Bloom filters [2] and uses hashing techniques. Dolev et al. [4, 5] and Greene, Parnas and Yao [9] considered approximate dictionary queries for the case where d is large. The initial effort towards a theoretical study of the small d case was given by Yao and Yao in [15] They present for the case d = 1 a data structure supporting queries in time O(m log log n) ....

Danny Dolev, Yuval Harari, Nathan Linial, Noam Nisan, and Michael Parnas. Neighborhood preserving hashing and approximate queries. In Proc. 5th ACMSIAM Symposium on Discrete Algorithms (SODA), pages 251--259, 1994.

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Dolev D., Harari Y., Linial N., Nisan N., Parnas M., Neighborhood preserving hashing and approximate queries, 5th ACM Symposium on Discrete Algorithms, 1994.

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D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. In Proc. of 5th SODA, pp. 251--259, 1994.

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D. Dolev, Y. Harari, N. Linial, N. Nisan, and M. Parnas. Neighborhood preserving hashing and approximate queries. Proc. of 5th SODA, pp. 251--259, 1994.

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D. Dolev, Y. Harari, N. Linial, N. Nisan and M. Parnas. Neighborhood preserving hashing and approximate queries. 5th ACM Symposium on Discrete Algorithm, 1994.

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