Abstract: A new algorithm called Character-Comparison to
Character-Access (CCCA) is developed to test the effect of both: 1)
converting character-comparison and number-comparison into
character-access and 2) the starting point of checking on the
performance of the checking operation in string searching. An
experiment is performed; the results are compared with five
algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Circle.
With the CCCA algorithm, the results suggest that the evaluation
criteria of the average number of comparisons are improved up to
74.0%. Furthermore, the results suggest that the clock time required
by the other algorithms is improved in range from 28% to 68% by the
new CCCA algorithm
Abstract: In this paper, we propose use of convolutional codes
for file dispersal. The proposed method is comparable in complexity
to the information Dispersal Algorithm proposed by M.Rabin and for
particular choices of (non-binary) convolutional codes, is almost as
efficient as that algorithm in terms of controlling expansion in the
total storage. Further, our proposed dispersal method allows string
search.
Abstract: As a structure for processing string problem, suffix
array is certainly widely-known and extensively-studied. But if the
string access pattern follows the “90/10" rule, suffix array can not take
advantage of the fact that we often find something that we have just
found. Although the splay tree is an efficient data structure for small
documents when the access pattern follows the “90/10" rule, it
requires many structures and an excessive amount of pointer
manipulations for efficiently processing and searching large
documents. In this paper, we propose a new and conceptually powerful
data structure, called splay suffix arrays (SSA), for string search. This
data structure combines the features of splay tree and suffix arrays into
a new approach which is suitable to implementation on both
conventional and clustered computers.
Abstract: A new algorithm called Character-Comparison to Character-Access (CCCA) is developed to test the effect of both: 1) converting character-comparison and number-comparison into character-access and 2) the starting point of checking on the performance of the checking operation in string searching. An experiment is performed using both English text and DNA text with different sizes. The results are compared with five algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Cycle. With the CCCA algorithm, the results suggest that the evaluation criteria of the average number of total comparisons are improved up to 35%. Furthermore, the results suggest that the clock time required by the other algorithms is improved in range from 22.13% to 42.33% by the new CCCA algorithm.