| R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465--476. Elsevier Science, September 1992. |
....character matches P i then we have also the choice of using it and matching P 1: i Gamma1 with the best suffix of T 1: j Gamma1 (the cost is C i Gamma1 ) This algorithm is O(mn) time and O(m) space. 3. A Bit parallel Simulation Bit parallelism is a technique of common use in string matching [2], firstly proposed in [1, 3] The technique consists in taking advantage of the intrinsic parallelism of the bit operations inside a computer word. By using cleverly this fact, the number of operations that an algorithm performs can be cut down by a factor of at most w, where w is the number of ....
R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465--476. Elsevier Science, Sept. 1992.
....: b2b1000. We can also perform arithmetic operations on the bits, such as addition and subtraction, which operate the bits as if they formed a number, for instance b : bx10000 1 = b : bx01111. 2. PREVIOUS WORK Bit parallelism for simple pattern matching The bit parallelism technique [1] consists in taking advantage of the intrinsic parallelism of the bit operations inside a computer word. By using cleverly this fact, the number of operations that an algorithm performs can be cut down by a factor of at most w, where w is the number of bits in the computer word. Since in current ....
R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465-476. Elsevier Science, September 1992.
....is of course Omega (n) for constant m. If the text is large even the fastest on line algorithms are not practical, and preprocessing the text becomes necessary. However, just a few years ago, indexing text for approximate string matching was considered one of the main open problems in this area [27, 3]. Despite some progress in the last years, the indexing schemes for this problem are still rather immature. There are two types of indexing mechanisms for approximate string matching, which we call word retrieving and sequence retrieving . Word retrieving indexes [18, 5, 2] are more oriented ....
R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465--476. Elsevier Science, September 1992.
....Algorithms, Vol. 0 No. 0, pp. 1 35, 0000 c Hermes Science Publications 2 J. of Discrete Algorithms, Vol. 0 No. 0, 0000 cessing the text becomes necessary. However, just a few years ago, indexing text for approximate string matching was considered one of the main open problems in this area [40, 3]. Despite some progress in the last years, the indexing schemes for this problem are still rather immature. The existing indexes do not perform well in practice. Some of them, based on suffix trees, are impractically large (12 to 70 times the text size) do not behave well in secondary memory, ....
R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465--476. Elsevier Science, September 1992.
.... of the dynamic programming matrix [30, 11, 16, 31, 9] Others filter the text to quickly eliminate uninteresting parts [29, 28, 10, 14, 24] some of them being sublinear on average for moderate ff (i.e. they do not inspect all the text characters) Yet other approaches use bit parallelism [3] in a computer word of w bits to reduce the number of operations [33, 35, 34, 6, 19] The problem of approximately searching a set of r patterns (i.e. the occurrences of anyone of them) has been considered only recently. This problem has many applications, for instance This work has been ....
....one error in the text window surger because there are not five letters of the pattern in the text. However, the filter cannot discard the possibility that the pattern appears in the text window yevrus . 3 2. 2 Bit Parallelism Bit parallelism is a technique of common use in string matching [3]. It was first proposed in [2, 4] The technique consists in taking advantage of the intrinsic parallelism of the bit operations inside a computer word. By using cleverly this fact, the number of operations that an algorithm performs can be cut down by a factor of at most w, where w is the number ....
R. Baeza-Yates. Text retrieval: Theory and practice. In 12th IFIP World Computer Congress, volume I, pages 465--476. Elsevier Science, September 1992.
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