Profile of Bucket Tries

Introduction Tries (from retrieval) are one of the most practical data structures with a tree construction in computer science. Tries store string data in leaves of tree. They are often used to store such data so that future retrieval can be made efficient. For example, tries are widely used in algo...

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Main Author: Mehri Javanian
Format: Article
Language:fas
Published: Kharazmi University 2020-08-01
Series:پژوهش‌های ریاضی
Subjects:
Online Access:http://mmr.khu.ac.ir/article-1-2661-en.html
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author_facet Mehri Javanian
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description Introduction Tries (from retrieval) are one of the most practical data structures with a tree construction in computer science. Tries store string data in leaves of tree. They are often used to store such data so that future retrieval can be made efficient. For example, tries are widely used in algorithms for automatically correcting words in texts. The number of nodes of the same type, which are at the same distance from the root of a rooted tree, is called profile. The analysis of the profile of a tree is of great importance. Because many of the parameters of a rooted tree can be expressed in terms of its profile. Although profiles represent one of the most fundamental parameters of tries, they have hardly been studied in the past. A generalized version of trie is called bucket trie where each leaf or bucket has a storage capacity of more than one string. Random trie is obtained by defining a random grow rule for trie. We present a detailed study of the limit behavior of the profiles in a random bucket tries.  Material and methods In this paper, the methods we apply to derive recurrences satisfied by the expected profiles and to solve them asymptotically for all possible ranges of the distance from the root, are based on the use of Poissonization, Mellin transform, recurrence equations, generating functions, singularity analysis and saddle-point method. Results and discussion Here, as the number of stored strings in a random bucket trie increases, we investigate the asymptotic expectation, variance and limiting distribution of each of the two internal and bucket profiles (i.e. the number of bucket nodes or leaves, and the number of internal nodes or non-leaves which are at the same distance from the root) in random bucket tries. Both the expectation and variances of the two profiles contain periodic functions, and we show those periodic functions are not zero that this point has not been proven in the paper on the ordinary trie. Also, we examine the amount of asymptotic ratio of the expectations of the bucket and internal profiles. Conclusion In this research, we will generalize the most important part of the results for the ordinary tries and also provide a proof for an unproven point in those results. More precisely, the purpose of this article is to study the internal profile (the number of non-leaf nodes at distance  from the root) and bucket profile (the number of buckets at distance  from the root) in an important data structure called random bucket trie (random trie based on  data and maximum capacity of  data per each leaf). By some methods in complex analysis, we have shown that for every  and some fixed constants  and , if  is in the range , then the expectations and variances of both profiles contain non-zero periodic functions (the non-zero property of these periodic functions has not been proved for the ordinary tries up to now). We also provide a graph of those periodic functions for  by MAPLE. Then we study the ratio of the two profiles for  Finally, by finding the asymptotic expansions of  Poisson generating functions for the probability generating functions of profiles and then using the Cauchy integral formula, we obtain the asymptotic expansions for the probability generating functions, which indicate that the limiting distributions of profiles are normal. ./files/site1/files/62/3Abstract.pdf
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spelling doaj.art-4519313baeda4a3e883fca300d0fe0fb2023-03-13T19:21:58ZfasKharazmi Universityپژوهش‌های ریاضی2588-25462588-25542020-08-0162169182Profile of Bucket TriesMehri Javanian0 Introduction Tries (from retrieval) are one of the most practical data structures with a tree construction in computer science. Tries store string data in leaves of tree. They are often used to store such data so that future retrieval can be made efficient. For example, tries are widely used in algorithms for automatically correcting words in texts. The number of nodes of the same type, which are at the same distance from the root of a rooted tree, is called profile. The analysis of the profile of a tree is of great importance. Because many of the parameters of a rooted tree can be expressed in terms of its profile. Although profiles represent one of the most fundamental parameters of tries, they have hardly been studied in the past. A generalized version of trie is called bucket trie where each leaf or bucket has a storage capacity of more than one string. Random trie is obtained by defining a random grow rule for trie. We present a detailed study of the limit behavior of the profiles in a random bucket tries.  Material and methods In this paper, the methods we apply to derive recurrences satisfied by the expected profiles and to solve them asymptotically for all possible ranges of the distance from the root, are based on the use of Poissonization, Mellin transform, recurrence equations, generating functions, singularity analysis and saddle-point method. Results and discussion Here, as the number of stored strings in a random bucket trie increases, we investigate the asymptotic expectation, variance and limiting distribution of each of the two internal and bucket profiles (i.e. the number of bucket nodes or leaves, and the number of internal nodes or non-leaves which are at the same distance from the root) in random bucket tries. Both the expectation and variances of the two profiles contain periodic functions, and we show those periodic functions are not zero that this point has not been proven in the paper on the ordinary trie. Also, we examine the amount of asymptotic ratio of the expectations of the bucket and internal profiles. Conclusion In this research, we will generalize the most important part of the results for the ordinary tries and also provide a proof for an unproven point in those results. More precisely, the purpose of this article is to study the internal profile (the number of non-leaf nodes at distance  from the root) and bucket profile (the number of buckets at distance  from the root) in an important data structure called random bucket trie (random trie based on  data and maximum capacity of  data per each leaf). By some methods in complex analysis, we have shown that for every  and some fixed constants  and , if  is in the range , then the expectations and variances of both profiles contain non-zero periodic functions (the non-zero property of these periodic functions has not been proved for the ordinary tries up to now). We also provide a graph of those periodic functions for  by MAPLE. Then we study the ratio of the two profiles for  Finally, by finding the asymptotic expansions of  Poisson generating functions for the probability generating functions of profiles and then using the Cauchy integral formula, we obtain the asymptotic expansions for the probability generating functions, which indicate that the limiting distributions of profiles are normal. ./files/site1/files/62/3Abstract.pdfhttp://mmr.khu.ac.ir/article-1-2661-en.htmlbucket triesprofilepoissonizationmellin transformrecursive equationsgenerating functionssingularity analysissaddle point method
spellingShingle Mehri Javanian
Profile of Bucket Tries
پژوهش‌های ریاضی
bucket tries
profile
poissonization
mellin transform
recursive equations
generating functions
singularity analysis
saddle point method
title Profile of Bucket Tries
title_full Profile of Bucket Tries
title_fullStr Profile of Bucket Tries
title_full_unstemmed Profile of Bucket Tries
title_short Profile of Bucket Tries
title_sort profile of bucket tries
topic bucket tries
profile
poissonization
mellin transform
recursive equations
generating functions
singularity analysis
saddle point method
url http://mmr.khu.ac.ir/article-1-2661-en.html
work_keys_str_mv AT mehrijavanian profileofbuckettries