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Journal articles on the topic 'Trie Tree'

Author: Grafiati

Published: 14 December 2024

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1

Dorokhina, Galina. "Phoneme-by-Phoneme Speech Recognition as a Classification of Series on a Set of Sequences of Elements of Complex Objects Using an Improved Trie-Tree." Informatics and Automation 23, no. 6 (November 7, 2024): 1784–822. http://dx.doi.org/10.15622/ia.23.6.8.

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Sequences, including vector sequences, are applicable in any subject domains. Sequences of scalar values or vectors (series) can be produced by higher-order sequences, for example: a series of states, or elements of complex objects. This academic paper is devoted to the application of an improved trie-tree in the classification of series on a set of sequences of elements of complex objects using the dynamic programming method. The implementation areas of dynamic programming have been considered. It has been shown that dynamic programming is adapted to multi-step operations of calculating additive (multiplicative) similarity/difference measures. It is argued that the improved trie-tree is applicable in the problem of classifying a series on a set of sequences of elements of complex objects using such similarity/difference measures. An analysis of hierarchical representations of sets of sequences has been performed. The advantages of the improved trie-tree over traditional representations of other highly branching trees have been described. A formal description of the improved trie-tree has been developed. An explanation has been given to the previously obtained data on a significant speed gain for operations of adding and deleting sequences in the improved trie-tree relative to the use of an array with an index table (24 and 380 times, respectively). The problem of phoneme-by-phoneme recognition of speech commands has been formulated as a problem of classifying series on a set of sequences of elements of complex objects and a method for its solving has been presented. A method for classifying a series on a set of sequences of elements of complex objects using the improved trie-tree is developed. The method has been studied using the example of phoneme-by-phoneme recognition with a hierarchical representation of the dictionary of speech command classes. In this method, recognition of speech commands is executed traversing the improved trie-tree that stores a set of transcriptions of speech commands – sequences of transcription symbols that denote classes of sounds. Numerical studies have shown that classifying a series as sequences of elements of complex objects increases the frequency of correct classification compared to classifying a series on a set of series, and using the improved trie-tree reduces the time spent on classification.

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SHI, Chang-qiong, Ming TANG, Da-fang ZHANG, and Kai-qing ZHOU. "Hash table based on Trie-tree." Journal of Computer Applications 30, no. 8 (September 7, 2010): 2193–96. http://dx.doi.org/10.3724/sp.j.1087.2010.02193.

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Schmeißer, Josef, Maximilian E. Schüle, Viktor Leis, Thomas Neumann, and Alfons Kemper. "B2-Tree: Page-Based String Indexing in Concurrent Environments." Datenbank-Spektrum 22, no. 1 (February 21, 2022): 11–22. http://dx.doi.org/10.1007/s13222-022-00409-y.

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AbstractRecently proposed index structures, that combine trie-based and comparison-based search mechanisms, considerably improve retrieval throughput for in-memory database systems. However, most of these index structures allocate small memory chunks when required. This stands in contrast to block-based index structures, that are necessary for disk-accesses of beyond main-memory database systems such as Umbra. We therefore present the B2-tree. The outer structure is identical to that of an ordinary B+-tree. It still stores elements in a dense array in sorted order, enabling efficient range scan operations. However, B2-tree is composed of multiple trees, each page integrates another trie-based search tree, which is used to determine a small memory region where a sought entry may be found. An embedded tree thereby consists of decision nodes, which operate on a single byte at a time, and span nodes, which are used to store common prefixes. This architecture usually accesses fewer cache lines than a vanilla B+-tree as shown in our performance evaluation. As a result, the B2-tree answers point queries considerably faster. Concurrent access to B2-tree pages are managed by an optimistic locking protocol which results in high utilization of the available hardware resources. Our evaluation of read-write workloads attests more than competitive performance for the B2-tree compared to a traditional B+-tree.

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CARON, EDDY, FRÉDÉRIC DESPREZ, FRANCK PETIT, and CÉDRIC TEDESCHI. "SNAP-STABILIZING PREFIX TREE FOR PEER-TO-PEER SYSTEMS." Parallel Processing Letters 20, no. 01 (March 2010): 15–30. http://dx.doi.org/10.1142/s012962641000003x.

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Several factors still hinder the deployment of computational grids over large scale platforms. Among them, the resource discovery is one crucial issue. New approaches, based on peer-to-peer technologies, tackle this issue. Because they efficiently allow range queries, Tries (a.k.a., Prefix Trees) appear to be among promising ways in the design of distributed data structures indexing resources. Despite their lack of robustness in dynamic settings, trie-structured approaches outperform other peer-to-peer fashioned technologies by efficiently supporting range queries. Within recent trie-based approaches, the fault-tolerance is handled by preventive mechanisms, intensively using replication. However, replication can be very costly in terms of computing and storage resources and does not ensure the recovery of the system after arbitrary failures. Self-stabilization is an efficient approach in the design of reliable solutions for dynamic systems. It ensures a system to converge to its intended behavior, regardless of its initial state, in a finite time. A snap-stabilizing algorithm guarantees that it always behaves according to its specification, once the protocol is launched. In this paper, we provide the first snap-stabilizing protocol for trie construction. We design particular tries called Proper Greatest Common Prefix (PGCP) Tree. The proposed algorithm arranges the n label values stored in the tree, in average, in O(h + h′) rounds, where h and h′ are the initial and final heights of the tree, respectively. In the worst case, the algorithm requires an O(n) extra space on each node, O(n) rounds and O(n2) actions. However, simulations allow to state that this worst case is far from being reached and to confirm the average complexities, showing the practical efficiency of this protocol.

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Abdullah, Zailani, Tutut Herawan, A. Noraziah, and Mustafa Mat Deris. "A Scalable Algorithm for Constructing Frequent Pattern Tree." International Journal of Intelligent Information Technologies 10, no. 1 (January 2014): 42–56. http://dx.doi.org/10.4018/ijiit.2014010103.

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Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

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6

Yang, Wen Chuan, Bei Jia, and Qing Yi Qu. "Research of an Improved Double-Array Trie Tree Algorithm." Advanced Materials Research 945-949 (June 2014): 2401–4. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2401.

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This paper presents an improved algorithm-iDAT, which is based on Double-Array Trie Tree for Chinese Word Segmentation Dictionary. Chinese word segmentation dictionary based on the Double-Array Trie Tree has higher efficiency of search, but the dynamic insertion will consume a lot of time. After initialization the original dictionary. We implement a Hash process to the empty sequence index values for base array. The final Hash table stores the sum of the empty sequence before the current empty sequence. This algorithm adopt Sunday jumps algorithm of Single Pattern Matching. With slightly and reasonable space cost increasing, iDAT reduces the average time complexity of the dynamic insertion process in Trie Tree. Practical results shows it has a good operation performance.

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KATAJAINEN, JYRKI, and ERKKI MÄKINEN. "TREE COMPRESSION AND OPTIMIZATION WITH APPLICATIONS." International Journal of Foundations of Computer Science 01, no. 04 (December 1990): 425–47. http://dx.doi.org/10.1142/s0129054190000291.

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Different methods for compressing trees are surveyed and developed. Tree compression can be seen as a trade-off problem between time and space in which we can choose different strategies depending on whether we prefer better compression results or more efficient operations in the compressed structure. Of special interest is the case where space can be saved while preserving the functionality of the operations; this is called data optimization. The general compression scheme employed here consists of separate linearization of the tree structure and the data stored in the tree. Also some applications of the tree compression methods are explored. These include the syntax-directed compression of program files, the compression of pixel trees, trie compaction and dictionaries maintained as implicit data structures.

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8

LIU, Lixia, and Zhiqiang ZHANG. "Similar string search algorithm based on Trie tree." Journal of Computer Applications 33, no. 8 (November 1, 2013): 2375–78. http://dx.doi.org/10.3724/sp.j.1087.2013.02375.

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Akulich, Mikita, Iztok Savnik, Matjaž Krnc, and Riste Škrekovski. "Multiset-Trie Data Structure." Algorithms 16, no. 3 (March 20, 2023): 170. http://dx.doi.org/10.3390/a16030170.

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This paper proposes a new data structure, multiset-trie, that is designed for storing and efficiently processing a set of multisets. Moreover, multiset-trie can operate on a set of sets without efficiency loss. The multiset-trie structure is a search tree with properties similar to those of a trie. It implements all standard search tree operations together with the multiset containment operations for searching sub-multisets and super-multisets. Suppose that we have a set of multisets S and a multiset X. The multiset containment operations retrieve multisets from S that are either sub-multisets or super-multisets of X. We present the mathematical analysis of a multiset-trie that gives the time complexity of the algorithms and the space complexity of the data structure. Further, the empirical analysis of the data structure is implemented in a series of experiments. The experiments illuminate the time complexity space of the multiset containment operations.

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ALAZEMI, HAMED M. K., and ANTON ČERNÝ. "COUNTING SUBWORDS USING A TRIE AUTOMATON." International Journal of Foundations of Computer Science 22, no. 06 (September 2011): 1457–69. http://dx.doi.org/10.1142/s0129054111008817.

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We use the concept of trie (prefix tree) representation of a prefix-closed finite language L to design a simple nondeterministic automaton. Each computation of this trie automaton corresponds to a subword occurrence of a word from L in the input word. The matrix representation of the trie automaton leads to a fairly general extension of the original concept of the Parikh matrix from [7].

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11

Xiong, Zhibin. "An Algorithm Rapidly Segmenting Chinese Sentences into Individual Words." MATEC Web of Conferences 267 (2019): 04001. http://dx.doi.org/10.1051/matecconf/201926704001.

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This paper proposes an improved Trie tree structure. The tree node records the position information of the characters participating in the word formation, and the child node uses the hash search mechanism. On this basis, the forward maximum matching algorithm of Chinese word segmentation is optimized. In the process of word segmentation, the automaton mechanism is used to judge whether it constitutes the longest word, and the problem that the forward maximum matching algorithm needs to adjust the string according to the word length is solved. The algorithm time complexity is 1.33, and the comparison test results show that there is a fast word segmentation speed. The forward maximum matching algorithm based on the improved Trie tree structure improves the Chinese word segmentation speed, especially when the dictionary structure needs to be updated in real time.

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Xu, Ke, Jianping Wu, Zhongchao Yu, and Mingwei Xu. "A non-collision hash trie-tree based fast IP classification algorithm." Journal of Computer Science and Technology 17, no. 2 (March 2002): 219–26. http://dx.doi.org/10.1007/bf02962215.

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13

Aguech, Rafik, Nabil Lasmar, and Hosam Mahmoud. "Limit distribution of distances in biased random tries." Journal of Applied Probability 43, no. 2 (June 2006): 377–90. http://dx.doi.org/10.1239/jap/1152413729.

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The trie is a sort of digital tree. Ideally, to achieve balance, the trie should grow from an unbiased source generating keys of bits with equal likelihoods. In practice, the lack of bias is not always guaranteed. We investigate the distance between randomly selected pairs of nodes among the keys in a biased trie. This research complements that of Christophi and Mahmoud (2005); however, the results and some of the methodology are strikingly different. Analytical techniques are still useful for moments calculation. Both mean and variance are of polynomial order. It is demonstrated that the standardized distance approaches a normal limiting random variable. This is proved by the contraction method, whereby the limit distribution is shown to approach the fixed-point solution of a distributional equation in the Wasserstein metric space.

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Lim, Hyesook, Youngju Choe, Miran Shim, and Jungwon Lee. "A Quad-Trie Conditionally Merged with a Decision Tree for Packet Classification." IEEE Communications Letters 18, no. 4 (April 2014): 676–79. http://dx.doi.org/10.1109/lcomm.2014.013114.132384.

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15

Wei, Xian Min. "Routing Lookup Algorithm Performance Analysis and Research." Advanced Materials Research 181-182 (January 2011): 109–12. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.109.

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This paper describes several current routing lookup algorithms, to study and analysize the complexity and operating practical performance of these routing lookup algorithms. The results show that although the binary search algorithm is not greatly improved in the searching performance, but in IPv6 environment, because searching performance of multi-branch Trie tree will decrease greatly, thus the superiority of binary search algorithm will be reflected better.

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Aguech, Rafik, Nabil Lasmar, and Hosam Mahmoud. "Limit distribution of distances in biased random tries." Journal of Applied Probability 43, no. 02 (June 2006): 377–90. http://dx.doi.org/10.1017/s0021900200001704.

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Thetrieis a sort of digital tree. Ideally, to achieve balance, the trie should grow from an unbiased source generating keys of bits with equal likelihoods. In practice, the lack of bias is not always guaranteed. We investigate the distance between randomly selected pairs of nodes among the keys in a biased trie. This research complements that of Christophi and Mahmoud (2005); however, the results and some of the methodology are strikingly different. Analytical techniques are still useful for moments calculation. Both mean and variance are of polynomial order. It is demonstrated that the standardized distance approaches a normal limiting random variable. This is proved by the contraction method, whereby the limit distribution is shown to approach the fixed-point solution of a distributional equation in the Wasserstein metric space.

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17

Pittel, Boris. "Paths in a random digital tree: limiting distributions." Advances in Applied Probability 18, no. 1 (March 1986): 139–55. http://dx.doi.org/10.2307/1427240.

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We study a rule of growing a sequence {tn} of finite subtrees of an infinite m-ary tree T. Independent copies {ω (n)} of a Bernoulli-type process ω on m letters are used to trace out a sequence of paths in T. The tree tn is obtained by cutting each , at the first node such that at most σ paths out of , pass through it. Denote by Hn the length of the longest path, hn the length of the shortest path, and Ln the length of the randomly chosen path in tn. It is shown that, in probability, Hn – logan = O(1), hn – logb (n/log n) = 0(1), (or hn – logb (n/log log n) = O(1)), and that is asymptotically normal. The parameters a, b, c depend on the distribution of ω and, in case of a, also on σ. These estimates describe respectively the worst, the best and the typical case behavior of a ‘trie’ search algorithm for a dictionary-type information retrieval system, with σ being the capacity of a page.

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Pittel, Boris. "Paths in a random digital tree: limiting distributions." Advances in Applied Probability 18, no. 01 (March 1986): 139–55. http://dx.doi.org/10.1017/s0001867800015603.

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We study a rule of growing a sequence {tn } of finite subtrees of an infinite m-ary tree T. Independent copies {ω (n)} of a Bernoulli-type process ω on m letters are used to trace out a sequence of paths in T. The tree tn is obtained by cutting each , at the first node such that at most σ paths out of , pass through it. Denote by Hn the length of the longest path, hn the length of the shortest path, and Ln the length of the randomly chosen path in tn. It is shown that, in probability, Hn – loga n = O(1), hn – log b (n/log n) = 0(1), (or hn – log b (n/log log n) = O(1)), and that is asymptotically normal. The parameters a, b, c depend on the distribution of ω and, in case of a, also on σ. These estimates describe respectively the worst, the best and the typical case behavior of a ‘trie’ search algorithm for a dictionary-type information retrieval system, with σ being the capacity of a page.

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Zhou, Enyuan, Song Guo, Zicong Hong, Christian S. Jensen, Yang Xiao, Dalin Zhang, Jinwen Liang, and Qingqi Pei. "VeriDKG: A Verifiable SPARQL Query Engine for Decentralized Knowledge Graphs." Proceedings of the VLDB Endowment 17, no. 4 (December 2023): 912–25. http://dx.doi.org/10.14778/3636218.3636242.

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The ability to decentralize knowledge graphs (KG) is important to exploit the full potential of the Semantic Web and realize the Web 3.0 vision. However, decentralization also renders KGs more prone to attacks with adverse effects on data integrity and query verifiability. While existing studies focus on ensuring data integrity, how to ensure query verifiability - thus guarding against incorrect, incomplete, or outdated query results - remains unsolved. We propose VeriDKG, the first SPARQL query engine for decentralized knowledge graphs (DKG) that offers both data integrity and query verifiability guarantees. The core of VeriDKG is the RGB-Trie, a new blockchain-maintained authenticated data structure (ADS) facilitating correctness proofs for SPARQL query results. VeriDKG enables verifiability of subqueries by gathering global index information on subgraphs using the RGB-Trie, which is implemented as a new variant of the Merkle prefix tree with an RGB color model. To enable verifiability of the final query result, the RGB-Trie is integrated with a cryptographic accumulator to support verifiable aggregation operations. A rigorous analysis of query verifiability in VeriDKG is presented, along with evidence from an extensive experimental study demonstrating its state-of-the-art query performance on the largeRDFbench benchmark.

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Nayanjyoti Mazumdar, Et al. "Significance of Data Structures and Data Retrieval Techniques on Sequence Rule Mining Efficacy." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (October 30, 2023): 508–18. http://dx.doi.org/10.17762/ijritcc.v11i9.8838.

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Sequence mining intends to discover rules from diverse datasets by implementing Rule Mining Algorithms with efficient data structures and data retrieval techniques. Traditional algorithms struggle in handling variable support measures which may involve repeated reconstruction of the underlying data structures with changing thresholds. To address these issues the premiere Sequence Mining Algorithm, AprioriAll is implemented against an Educational and a Financial Dataset, using the HASH and the TRIE data structures with scan reduction techniques. Primary idea is to study the impact of data structures and retrieval techniques on the rule mining process in handling diverse datasets. Performance Evaluation Matrices- Support, Confidence and Lifts are considered for testing the efficacies of the algorithm in terms of memory requirements and execution time complexities. Results unveil the excellence of Hashing in tree construction time and memory overhead for fixed sets of pre-defined support thresholds. Whereas, TRIE may avoid reconstruction and is capable of handling dynamic support thresholds, leading to shorter rule discovery time but higher memory consumption. This study highlights the effectiveness of Hash and TRIE data structures considering the dataset characteristics during rule mining. It underscores the importance of appropriate data structures based on dataset features, scanning techniques, and user-defined parameters.

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Murali, Pranav. "An Approach to Trie Based Keyword Search for Search Engines." International Journal of Library and Information Services 6, no. 1 (January 2017): 1–16. http://dx.doi.org/10.4018/ijlis.2017010101.

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Search Engines use indexing techniques to minimize the time taken to find the relevant information to a search query. They maintain a keywords list that may reside either in the memory or in the external storage, like a hard disk. While a pure binary search can be used for this purpose, it suffers from performance issue when keywords are stored in the external storage. Some implementations of search engines use a B-tree and sparse indexes to reduce access time. This paper aims at reducing the keyword access time further. It presents a keyword search technique that utilizes a combination of trie data structure and a new keyword prefixing method. Experimental results show good improvement in performance over pure binary search. The merits of incorporating trie based approach into contemporary indexing methods is also discussed. Keyword prefixing method is described and some salient steps in the process of keyword generation are outlined.

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22

HINZE, RALF. "Generalizing generalized tries." Journal of Functional Programming 10, no. 4 (July 2000): 327–51. http://dx.doi.org/10.1017/s0956796800003713.

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A trie is a search tree scheme that employs the structure of search keys to organize information. Tries were originally devised as a means to represent a collection of records indexed by strings over a fixed alphabet. Based on work by C. P. Wadsworth and others, R. H. Connelly and F. L. Morris generalized the concept to permit indexing by elements built according to an arbitrary signature. Here we go one step further, and define tries and operations on tries generically for arbitrary datatypes of first-order kind, including parameterized and nested datatypes. The derivation employs techniques recently developed in the context of polytypic programming and can be regarded as a comprehensive case study in this new programming paradigm. It is well known that for the implementation of generalized tries, nested datatypes and polymorphic recursion are needed. Implementing tries for first-order kinded datatypes places even greater demands on the type system: it requires rank-2 type signatures and second-order nested datatypes. Despite these requirements, the definition of tries is surprisingly simple, which is mostly due to the framework of polytypic programming.

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Zhang, Chen, and Yu Quan Chen. "New Words Identification Based on Ensemble Methods." Applied Mechanics and Materials 602-605 (August 2014): 1626–29. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1626.

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In order to identify new words in huge Chinese corpus efficiently, this paper comes up with an algorithm based on ensemble methods. At first we perform Chinese word segmenting with Trie and build segment-tree. Then we select words pattern drawing method, frequency filtering, independent word probability and naive Bayes model to be sub-models of ensemble methods and train them independently. At last we integrate results from different sub-models with a multi-layer model. In experiment, this algorithm is proved to be quite fast as well as product precise and high-coverage results.

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Gao, Kai, Er Liang Zhou, Dong Ru Ruan, and Radha Ganesan. "Research on double-array-trie tree-based lexicon and its application on micro-blog content analysing." International Journal of Computer Applications in Technology 52, no. 4 (2015): 277. http://dx.doi.org/10.1504/ijcat.2015.073594.

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Yakovlev, P. A. "Fast trie-based method for multiple pairwise sequence alignment." Доклады Академии наук 484, no. 4 (May 5, 2019): 401–4. http://dx.doi.org/10.31857/s0869-56524844401-404.

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A method for efficient comparison of a symbol sequence with all strings of a set is presented, which performs considerably faster than the naive enumeration of comparisons with all strings in succession. The procedure is accelerated by applying an original algorithm combining a prefix tree and a standard dynamic programming algorithm searching for the edit distance (Levenshtein distance) between strings. The efficiency of the method is confirmed by numerical experiments with arrays consisting of tens of millions of biological sequences of variable domains of monoclonal antibodies.

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Thenmozhi, M., and H. Srimathi. "An Analysis on the Performance of Tree and Trie Based Dictionary Implementations with Different Data Usage Models." Indian Journal of Science and Technology 8, no. 4 (February 1, 2015): 364. http://dx.doi.org/10.17485/ijst/2015/v8i1/59865.

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Li, Danyang, Yahui Zhao, Mengjiang Luo, and Rongyi Cui. "Design and Implementation of a Course Answering System Based on Error Correction and Trie Tree Language Model." Journal of Physics: Conference Series 1621 (August 2020): 012057. http://dx.doi.org/10.1088/1742-6596/1621/1/012057.

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Guo, Hai, Jing Ying Zhao, and Ming Jun Da. "The Research and Implementation of NaXi Pictographs Mobile Phone Dictionary Based on J2ME." Advanced Materials Research 108-111 (May 2010): 1049–54. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.1049.

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As the only still used pictographs in the world, NaXi pictographs has been used in computer information processing. However, the technology of processing minority scripts hasn't been applied on mobile platform. Using Eclipse, this paper has developed a NaXi Pictographs Mobile Phone Dictionary Based on J2ME. Via Fast Searching Algorithm of Trie tree, we achieved the goal of NaXi-Chinese query and online update of the lexicon. To the problem of display NaXi pictographs on the MT (Mobile Terminal), we extracted matrix font of NaXi pictographs. The realization of NaXi Pictographs Mobile Phone Dictionary drew a new page on the history of information processing on Chinese minority scripts mobile, as well as a great reference for information processing on other minority scripts.

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Binna, Robert, Eva Zangerle, Martin Pichl, Günther Specht, and Viktor Leis. "Height Optimized Tries." ACM Transactions on Database Systems 47, no. 1 (March 31, 2022): 1–46. http://dx.doi.org/10.1145/3506692.

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We present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. For a fixed maximum node fanout, the overall tree height is minimal and its structure is deterministically defined. Multiple carefully engineered node implementations using SIMD instructions or lightweight compression schemes provide compactness and fast search and optimize HOT structures for different usage scenarios. Our experiments, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys.

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Rizvee, Redwan Ahmed, Md Shahadat Hossain Shahin, Chowdhury Farhan Ahmed, and Carson K. Leung. "Mining Weighted Patterns from Time Series Databases Based on Sliding Window." Dhaka University Journal of Applied Science and Engineering 8, no. 1 (July 15, 2024): 13–25. http://dx.doi.org/10.3329/dujase.v8i1.72984.

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Data mining has traditionally relied heavily on sliding window-based challenges, which has sparked a variety of studies. For each new window in time series mining, current literature mandates the rebuilding of the underlying structure, Suffix Tree - A trie-based structure representing all the suffixes of a string. However, reconstruction struggles when the window is wide or when sliding happens frequently. As a result, we provide a new technique Dynamic Tree-Based Approach to handle Sliding Windows (DTSW) in time series in this study that dynamically changes the representative suffix tree structure rather than reconstructing it after every alteration or sliding. In addition, we also put forth a different approach to the issue of extracting weighted periodic patterns from time series. To prevent testing pointless patterns, existing studies mostly rely on the weight of the database's highest-weighted item. However, these methods continue to examine numerous patterns. These methods still examine numerous patterns to see whether they can be candidates. Our proposed measure Maximum Possible Weighted Support (MPWS) accelerates the candidate generation process by removing numerous unnecessary patterns in advance. The novelty of MPWS is it considers the maximum weighted average over the maximum weighted item extension by enforcing more constraints. The usefulness of our two techniques in handling sliding windows and trimming redundant candidate patterns is demonstrated by experimental results using a variety of real-world datasets. Our experiments state that our dynamic handling technique significantly improves runtime than the reconstruction in a dynamic sliding window-based environment with simultaneous insertion and deletion actions and MPWS reduces the number of tested patterns resulting in lesser mining time in weighted time series pattern mining. DUJASE Vol. 8 (1) 13-25, 2023 (January)

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Kim, Ju-Chul, and Sang-Joong Lee. "A Lecture Note for Introduction of Steiner (Fermat) Tree to Electrical Engineering Education - Comparison of Path Lengths of Minimum Spanning Tree and Steiner Tree." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 33, no. 6 (June 30, 2019): 9–18. http://dx.doi.org/10.5207/jieie.2019.33.6.009.

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Chen, Jian, Jianpeng Chen, Xiangrong She, Jian Mao, and Gang Chen. "Deep Contrast Learning Approach for Address Semantic Matching." Applied Sciences 11, no. 16 (August 19, 2021): 7608. http://dx.doi.org/10.3390/app11167608.

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Address is a structured description used to identify a specific place or point of interest, and it provides an effective way to locate people or objects. The standardization of Chinese place name and address occupies an important position in the construction of a smart city. Traditional address specification technology often adopts methods based on text similarity or rule bases, which cannot handle complex, missing, and redundant address information well. This paper transforms the task of address standardization into calculating the similarity of address pairs, and proposes a contrast learning address matching model based on the attention-Bi-LSTM-CNN network (ABLC). First of all, ABLC use the Trie syntax tree algorithm to extract Chinese address elements. Next, based on the basic idea of contrast learning, a hybrid neural network is applied to learn the semantic information in the address. Finally, Manhattan distance is calculated as the similarity of the two addresses. Experiments on the self-constructed dataset with data augmentation demonstrate that the proposed model has better stability and performance compared with other baselines.

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Anwar, Muhammad, Aboul Ella Hassanien, Václav Snás̃el, and Sameh H. Basha. "Subgraph Query Matching in Multi-Graphs Based on Node Embedding." Mathematics 10, no. 24 (December 19, 2022): 4830. http://dx.doi.org/10.3390/math10244830.

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This paper presents an efficient algorithm for matching subgraph queries in a multi-graph based on features-based indexing techniques. The KD-tree data structure represents these nodes’ features, while the set-trie index data structure represents the multi-edges to make queries effectively. The vertex core number, triangle number, and vertex degree are the eight features’ main features. The densest vertex in the query graph is extracted based on these main features. The proposed model consists of two phases. The first phase’s main idea is that, for the densest extracted vertex in the query graph, find the density similar neighborhood structure in the data graph. Then find the k-nearest neighborhood query to obtain the densest subgraph. The second phase for each layer graph, mapping the vertex to feature vector (Vertex Embedding), improves the proposed model. To reduce the node-embedding size to be efficient with the KD-tree, indexing a dimension reduction, the principal component analysis (PCA) method is used. Furthermore, symmetry-breaking conditions will remove the redundancy in the generated pattern matching with the query graph. In both phases, the filtering process is applied to minimize the number of candidate data nodes of the initiate query vertex. The filtering process is applied to minimize the number of candidate data nodes of the initiate query vertex. Finally, testing the effect of the concatenation of the structural features (orbits features) with the meta-features (summary of general, statistical, information-theoretic, etc.) for signatures of nodes on the model performance. The proposed model is tested over three real benchmarks, multi-graph datasets, and two randomly generated multi-graph datasets. The results agree with the theoretical study in both random cliques and Erdos random graph. The experiments showed that the time efficiency and the scalability results of the proposed model are acceptable.

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Li, Rui, Shili Shu, Shunli Wang, Yang Liu, Yanhao Li, and Mingjun Peng. "DAT-MT Accelerated Graph Fusion Dependency Parsing Model for Small Samples in Professional Fields." Entropy 25, no. 10 (October 12, 2023): 1444. http://dx.doi.org/10.3390/e25101444.

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The rapid development of information technology has made the amount of information in massive texts far exceed human intuitive cognition, and dependency parsing can effectively deal with information overload. In the background of domain specialization, the migration and application of syntactic treebanks and the speed improvement in syntactic analysis models become the key to the efficiency of syntactic analysis. To realize domain migration of syntactic tree library and improve the speed of text parsing, this paper proposes a novel approach—the Double-Array Trie and Multi-threading (DAT-MT) accelerated graph fusion dependency parsing model. It effectively combines the specialized syntactic features from small-scale professional field corpus with the generalized syntactic features from large-scale news corpus, which improves the accuracy of syntactic relation recognition. Aiming at the problem of high space and time complexity brought by the graph fusion model, the DAT-MT method is proposed. It realizes the rapid mapping of massive Chinese character features to the model’s prior parameters and the parallel processing of calculation, thereby improving the parsing speed. The experimental results show that the unlabeled attachment score (UAS) and the labeled attachment score (LAS) of the model are improved by 13.34% and 14.82% compared with the model with only the professional field corpus and improved by 3.14% and 3.40% compared with the model only with news corpus; both indicators are better than DDParser and LTP 4 methods based on deep learning. Additionally, the method in this paper achieves a speedup of about 3.7 times compared to the method with a red-black tree index and a single thread. Efficient and accurate syntactic analysis methods will benefit the real-time processing of massive texts in professional fields, such as multi-dimensional semantic correlation, professional feature extraction, and domain knowledge graph construction.

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Jasmine, Jasmine, Pankaj Bhambri, and Dr O. P. Gupta Dr. O.P. Gupta. "Analyzing the Phylogenetic Trees with Tree- building Methods." Indian Journal of Applied Research 1, no. 7 (October 1, 2011): 83–85. http://dx.doi.org/10.15373/2249555x/apr2012/25.

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S Shevtekar, Sumit, Sayeed Khan, Sanket Jhavar, and Harsh Dhawale. "Bo-Tree: An Efficient Search Tree." International Journal of Science and Research (IJSR) 11, no. 12 (December 5, 2022): 273–77. http://dx.doi.org/10.21275/sr221202123124.

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Schaar, Günter, and Zdzisław Skupień. "Pairs of trees in tree–tree triangulations." Discrete Mathematics 307, no. 11-12 (May 2007): 1499–505. http://dx.doi.org/10.1016/j.disc.2005.11.087.

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Zhang, Hui. "The Analysis of English Sentence Components Based on Decision Tree Classification Algorithm." Highlights in Science, Engineering and Technology 23 (December 3, 2022): 317–20. http://dx.doi.org/10.54097/hset.v23i.3617.

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Decision tree is an important classification method in data excavation technology. It is a predictive analysis model expressed in the form of a tree structure (including binary trees and poly trees). The decision tree method is a more general classification function approximation method. It is an algorithm commonly used in predictive models to find some potentially valuable information by purposefully classifying a large amount of data. In this article, the author tries to analyze the English sentence components based on the decision tree classification algorithm. The author starts with the decision tree, extracts the decision tree rules, and generates a classifier by effectively sorting the decision tree rules, and applies it to classification prediction.

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Holmgren, Cecilia. "A weakly 1-stable distribution for the number of random records and cuttings in split trees." Advances in Applied Probability 43, no. 1 (March 2011): 151–77. http://dx.doi.org/10.1239/aap/1300198517.

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In this paper we study the number of random records in an arbitrary split tree (or, equivalently, the number of random cuttings required to eliminate the tree). We show that a classical limit theorem for the convergence of sums of triangular arrays to infinitely divisible distributions can be used to determine the distribution of this number. After normalization the distributions are shown to be asymptotically weakly 1-stable. This work is a generalization of our earlier results for the random binary search tree in Holmgren (2010), which is one specific case of split trees. Other important examples of split trees include m-ary search trees, quad trees, medians of (2k + 1)-trees, simplex trees, tries, and digital search trees.

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Holmgren, Cecilia. "A weakly 1-stable distribution for the number of random records and cuttings in split trees." Advances in Applied Probability 43, no. 01 (March 2011): 151–77. http://dx.doi.org/10.1017/s0001867800004730.

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In this paper we study the number of random records in an arbitrary split tree (or, equivalently, the number of random cuttings required to eliminate the tree). We show that a classical limit theorem for the convergence of sums of triangular arrays to infinitely divisible distributions can be used to determine the distribution of this number. After normalization the distributions are shown to be asymptotically weakly 1-stable. This work is a generalization of our earlier results for the random binary search tree in Holmgren (2010), which is one specific case of split trees. Other important examples of split trees includem-ary search trees, quad trees, medians of (2k+ 1)-trees, simplex trees, tries, and digital search trees.

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Lee, Sang-gi, and NaiHoon Jung. "HD-Tree: High performance Lock-Free Nearest Neighbor Search KD-Tree." Journal of Korea Game Society 20, no. 5 (October 31, 2020): 53–63. http://dx.doi.org/10.7583/jkgs.2020.20.5.53.

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Williams, Roger A. "Use of Randomized Branch and Importance Sampling to Estimate Loblolly Pine Biomass." Southern Journal of Applied Forestry 13, no. 4 (November 1, 1989): 181–84. http://dx.doi.org/10.1093/sjaf/13.4.181.

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Abstract A previously developed sampling method utilizing randomized branch and importance sampling for the purpose of quickly estimating tree biomass was tested on five loblolly pine (Pinus taeda L.) trees. Results show a wide range of per-tree sampling error, ranging from 5.3 to 28.9%. Largevariation in foliage content among selected branches per treee may be a major source of error. However, the sampling error for the total biomass of the five trees tested was only 3.3%. This sampling method appears to be reliable and efficient in obtaining precise estimates of the total biomassof a population of trees. Increased sampling intensity per tree is necessary to obtain precise estimates of individual tree biomass. South. J. Appl. For. 13(4):181-184.

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Copetti, Dario, Alberto Búrquez, Enriquena Bustamante, Joseph L. M. Charboneau, Kevin L. Childs, Luis E. Eguiarte, Seunghee Lee, et al. "Extensive gene tree discordance and hemiplasy shaped the genomes of North American columnar cacti." Proceedings of the National Academy of Sciences 114, no. 45 (October 23, 2017): 12003–8. http://dx.doi.org/10.1073/pnas.1706367114.

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Few clades of plants have proven as difficult to classify as cacti. One explanation may be an unusually high level of convergent and parallel evolution (homoplasy). To evaluate support for this phylogenetic hypothesis at the molecular level, we sequenced the genomes of four cacti in the especially problematic tribe Pachycereeae, which contains most of the large columnar cacti of Mexico and adjacent areas, including the iconic saguaro cactus (Carnegiea gigantea) of the Sonoran Desert. We assembled a high-coverage draft genome for saguaro and lower coverage genomes for three other genera of tribe Pachycereeae (Pachycereus,Lophocereus, andStenocereus) and a more distant outgroup cactus,Pereskia. We used these to construct 4,436 orthologous gene alignments. Species tree inference consistently returned the same phylogeny, but gene tree discordance was high: 37% of gene trees having at least 90% bootstrap support conflicted with the species tree. Evidently, discordance is a product of long generation times and moderately large effective population sizes, leading to extensive incomplete lineage sorting (ILS). In the best supported gene trees, 58% of apparent homoplasy at amino sites in the species tree is due to gene tree-species tree discordance rather than parallel substitutions in the gene trees themselves, a phenomenon termed “hemiplasy.” The high rate of genomic hemiplasy may contribute to apparent parallelisms in phenotypic traits, which could confound understanding of species relationships and character evolution in cacti.

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Freilicher, Mollie. "Tree by Tree, Yard by Yard: Replanting Worcester's Trees." Arnoldia 69, no. 1 (2011): 2–13. http://dx.doi.org/10.5962/p.258693.

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GOMBOS, Gergo, János Márk SZALAI-GINDL, István DONKÓ, and Attila KISS. "TOWARDS ON EXPERIMENTAL COMPARISON OF THE M-TREE INDEX STRUCTURE WITH BK-TREE AND VP-TREE." Acta Electrotechnica et Informatica 20, no. 2 (June 30, 2020): 19–26. http://dx.doi.org/10.15546/aeei-2020-0009.

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Sharma, Rani, and Vaibhav Ujjainkar. "A Review on Tree Improvement through Candidate Plus Tree Selection (CPTs) in Indian Butter Tree (Madhuca spp)." International Journal of Science and Research (IJSR) 11, no. 7 (July 5, 2022): 842–45. http://dx.doi.org/10.21275/sr22712230645.

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Park, Jae Hyun, Lee Hee Seok, and Jung Yong gyu. "Analysis of in-Hospital Infection using J48 Tree and AD Tree." Research Society of Language and Literature 3, no. 1 (May 13, 2013): 11–24. http://dx.doi.org/10.21594/itma.2015.3.1.6.

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In 21st century people are increased to look for hospital due to influenza, natural disasters for globally aging population. These hospitals are trying to prevent infection in preliminary research results, such as dropping the credibility and reputation of the hospital. In this paper, the data in the hospital onset CDI Community Onset and CLABSI Coronaty likely to be infected with a staff in the ICU figures are estimates at a university hospital in the United States. We try to analyze the data CLABSI Coronary ICU. CDI Community Onset was found to be almost endemic only about half less. Analysis of the data looked infections observed by comparing the difference between the actual number of infections observed and predicted. Predicted probability of CDI Community Onset is expected about 57%, CLABSI Coronary ICU was confirmed to be about 94%.

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Lee, Jung-Hun. "IRFP-tree: Intersection Rule Based FP-tree." KIPS Transactions on Software and Data Engineering 5, no. 3 (March 31, 2016): 155–64. http://dx.doi.org/10.3745/ktsde.2016.5.3.155.

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Ko, Sang-Ki, Ha-Rim Lee, and Yo-Sub Han. "State Complexity of Regular Tree Languages for Tree Matching." International Journal of Foundations of Computer Science 27, no. 08 (December 2016): 965–79. http://dx.doi.org/10.1142/s0129054116500398.

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We study the state complexity of regular tree languages for tree matching problem. Given a tree t and a set of pattern trees L, we can decide whether or not there exists a subtree occurrence of trees in L from the tree t by considering the new language L′ which accepts all trees containing trees in L as subtrees. We consider the case when we are given a set of pattern trees as a regular tree language and investigate the state complexity. Based on the sequential and parallel tree concatenation, we define three types of tree languages for deciding the existence of different types of subtree occurrences. We also study the deterministic top-down state complexity of path-closed languages for the same problem.

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Finney, Kimberly. "Haiti’s Tree Angels." Psychology & Psychological Research International Journal 9, no. 3 (2024): 1–5. http://dx.doi.org/10.23880/pprij-16000429.

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Haiti has been 97% deforested by Europeans and American businesses for profit. Britannica defines deforestation is defined as the clearing and removal of trees by humans. Deforestation ranks as the largest issue in global land use, historically for agriculture use, fuel, manufacturing, and construction. However, Haiti’s deforestation resulted in the lumber from the trees being exported and nothing being imported or built to replace the trees. Consequently, the ground in Haiti where the trees have been removed has lost its ability to sustain the impact of earthquakes and floods. As such, homes are destroyed and people are displaced following these natural disasters. The aim of Tree Angels for Haiti (TAFH) is to reforest Haiti by planting one tree at a time.

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