Systolic Tree Research Articles

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class. This will mitigate the feature vector's dimensionality by eliminating redundant, irrelevant, or noisy data. This work presents a new hybrid recommender system based on optimized feature selection and systolic tree. The features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF), feature selection with the utilization of River Formation Dynamics (RFD), and the Particle Swarm Optimization (PSO) algorithm. The systolic tree is used for pattern mining, and based on this, the recommendations are given. The proposed methods were evaluated using the MovieLens dataset, and the experimental outcomes confirmed the efficiency of the techniques. It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborative filtering, the precision of 0.89 was achieved.

Hybrid Recommender System for Mental Illness Detection in Social Media Using Deep Learning Techniques.

Recommender systems are chiefly renowned for their applicability in e-commerce sites and social media. For system optimization, this work introduces a method of behaviour pattern mining to analyze the person's mental stability. With the utilization of the sequential pattern mining algorithm, efficient extraction of frequent patterns from the database is achieved. A candidate sub-sequence generation-and-test method is adopted in conventional sequential mining algorithms like the Generalized Sequential Pattern Algorithm (GSP). However, since this approach will yield a huge candidate set, it is not ideal when a large amount of data is involved from the social media analysis. Since the data is composed of numerous features, all of which may not have any relation with one another, the utilization of feature selection helps remove unrelated features from the data with minimal information loss. In this work, Frequent Pattern (FP) mining operations will employ the Systolic tree. The systolic tree-based reconfigurable architecture will offer various benefits such as high throughput as well as cost-effective performance. The database's frequently occurring item sets can be found by using the FP mining algorithms. Numerous research areas related to machine learning and data mining are fascinated by feature selection since it will enable the classifiers to be swift, more accurate, and cost-effective. Over the last ten years or so, there have been significant technological advancements in heuristic techniques. These techniques are beneficial because they improve the search procedure's efficiency, albeit at the potential sacrifice of completeness claims. A new recommender system for mental illness detection was based on features selected using River Formation Dynamics (RFD), Particle Swarm Optimization (PSO), and hybrid RFD-PSO algorithm is proposed in this paper. The experiments use the depressive patient datasets for evaluation, and the results demonstrate the improved performance of the proposed technique.

An intelligent feature selection approach with systolic tree structures for efficient association rules in big data environment

Frequent Pattern Mining (FPM) is regularly used in data mining applications for identifying objects of interest that frequent transactional databases. Traditional ARM algorithms work on minimum levels of support and confidence metrics which have to be defined and are subjective. This work attempts to solve this issue by proposing techniques for the automatic determination of these metrics. The Kernel Possibilistic Fuzzy Local Information C-Means (KPFLICM) Clustering and K-means Clustering-based Feature Selection algorithm for Association Rules (KCFSAR) is used where FPMs are based on Systolic Tree Structures (STS). These structures aim to achieve better accuracy by mimicking internal memory structures of the Frequent Pattern Growths (FPG) algorithm. Moreover, Chaotic Butterfly Optimization Method (CBOAs) is used to obtain the optimal support value and CBOA subsequently discovers global optimal solutions. This work's suggested scheme demonstrates its efficacy and superiority in experimental findings when compared to other approaches in terms of feature subset sizes, accuracies, execution times, and memory consumptions.

ENHANCED RECONFIGURABLE WEIGHTED ASSOCIATION RULE MINING FOR FREQUENT PATTERNS OF WEB LOGS

Systolic tree structure is a reconfigurable architecture in Field-programmable gate arrays (FPGA) which provide performance advantages. It is used for frequent pattern mining operations. High throughput and cost effective performance are the highlights of the systolic tree based reconfigurable architecture. Frequent pattern mining algorithms are used to find frequently occurring item sets in databases. However, space and computational time requirements are very high in frequent pattern mining algorithms. In the proposed system, systolic tree based hardware mechanism is employed with Weighted Association Rule Mining (WARM) for frequent item set extraction process of the Web access logs. Weighted rule mining is to mine the items which are assigned with weights based on user’s interest and the importance of the items. In the proposed system, weights are assigned automatically to Web pages that are visited by the users. Hence, systolic tree based rule mining scheme is enhanced for WARM process, which fetches the frequently accessed Web pages with weight values. The dynamic Web page weight assignment scheme uses the page request count and span time values. The proposed system improves the weight estimation process with span time, request count and access sequence details. The user interest based page weight is used to extract the frequent item sets. The proposed system will also improve the mining efficiency on sparse patterns. The goal is to drive the mining focus to those significant relationships involving items with significant weights.

Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining

Frequent pattern mining algorithms are designed to find commonly occurring sets in databases. This class of algorithms is typically very memory intensive, leading to prohibitive runtimes on large databases. A class of reconfigurable architectures has been recently developed that have shown promise in accelerating some data mining applications. In this paper, we propose a new architecture for frequent pattern mining based on a systolic tree structure. The goal of this architecture is to mimic the internal memory layout of the original pattern mining software algorithm while achieving a higher throughput. We provide a detailed analysis of the area and performance requirements of our systolic tree-based architecture, and show that our reconfigurable platform is faster than the original software algorithm for mining long frequent patterns.

Systolic tree [formula omitted]-languages: the operational and the logical view

The class of ω-languages recognized by systolic (binary) tree automata is introduced. This class extends the class of Büchi ω-languages though maintaining the closure under union, intersection and complement and the decidability of emptiness. The class of systolic tree ω-languages is characterized in terms of a (suitable) concatenation of (finitary) systolic tree languages. A generalization of Buc̈hi Theorem is provided which establishes a correspondence between systolic tree ω-languages and a suitable extension of the sequential calculus S1S.

CHOMSKY HIERARCHY AND SYSTOLIC Y-TREE AUTOMATA

We prove that no nonregular deterministic context-free language is accepted by any systolic Y-tree automaton while some of them, but not all, can be accepted by nondeterministic systolic Y-tree automata. We show that weak superstable systolic automata over incomplete Y-tree can accept only regular languages. We also show that the weak superstability and the superstability problems are decidable for deterministic systolic automata over a sparse and superprefix Y-tree. Moreover we prove that the regularity problem is decidable for systolic binary tree automata.

VLSI design and implementation of systolic tree queues

A number of innovative designs have been proposed for hardware implementation of data structures. However, these designs have only been presented at an abstract behavioural level. In this paper, we describe the VLSI design and implementation of a 15-node 8-bit queue based on a systolic tree architecture. A layout methodology and a VLSI CAD environment that facilitate fast and efficient layout of large binary trees are described. The objective of this paper is to illustrate the implementation of tree architectures in VLSI. We demonstrate this by implementing a systolic tree queue.

Completeness results concerning systolic tree automata and E0L languages

Abstract We introduce the notion of rewriting systems for sets, and consider the complexity of two reachability problems for these systems, showing that these problems are PSPACE-complete. Using such problems as bridge between Turing Machine computations and Binary Systolic Tree Automata (BSTA) we are able to prove that a number of important decision problems concerning these automata are PSPACE-complete. Finally, as a consequence, we show that the emptiness problem and the finiteness problem for E0L systems are PSPACE-complete, solving a long standing open problem.

A kleene-like characterization of languages accepted by systolic tree automata

We present a Kleen-like characterization of the class of languages accepted by systolic binary tree automata, L(SBTA). This characterization uses union, intersection, restricted concatenation, restricted concatenation closure, and finite substitution closure. The restrictions we impose on the operator of concatenation are purely in terms of the length of the words to be concatenated.

Classes of systolic Y-tree automata and a comparison with systolic trellis automata

In this paper we study systolic Y-tree automata (SYTA), a class of systolic automata where the communication structure is obtained by adding new edges, and therefore new sons, called adoptive sons, to the nodes of the underlying tree according to some regularity condition. We study SYTA in the more specific case where the tree ist-ary or a tree with base. We show that for eachs≧0 the set of classes of languages accepted by SYTA whose underlying tree is a tree with base withs leaves has a maximum, calledLsSYTA. We study whenLsSYTA is reached depending on number and position of the adoptive sons. We prove that ifs andt are powers of the same base, thenLsSYTA=LtSYTA. We give also a simulation of SYTA on regular and modular systolic trellis automata, strengthening a previous result on simulation of systolic tree automata on systolic trellis automata.

SYSTOLIC TREE WITH BASE AUTOMATA

Different systolic tree automata (STA) with base (T(b)−STA) are compared. This is a subclass of STA with interesting properties of modularity. We give a necessary and sufficient condition for the inclusion between classes of languages accepted by T(b)− STA, (L(T(b)−STA)), as b varies. We focus on T(b)−STA obtained by varying the base b in a natural way. We prove that for every base b within this framework there exists an a such that L(T(a)−STA) is not contained in L(T(b)−STA). We characterize the family of languages accepted by T(b)−STA when the input conditions are relaxed. Moreover we show that the emptiness problem is decidable for T(b)−STA.

Nonacceptability criteria and closure properties for the class of languages accepted by binary systolic tree automata

In this paper a contribution is given to the solution of the problem of finding an inductive characterization of the class of languages accepted by binary systolic tree automata, L (BSTA), in terms of the closure of a class of languages with respect to certain operations. It is shown that L (BSTA) is closed with respect to some new operations: selective concatenation, restricted concatenation and restricted iteration. The known nonclosure of L (BSTA) with respect to classical language operations, like concatenation and Kleene iteration is proved here by using a new nonacceptability criterion.

SIMULATION OF SYSTOLIC TREE AUTOMATA ON TRELLIS AUTOMATA

The relation between two basic types of systolic automata—tree automata and trellis automata—is investigated. First it is shown that for every natural t>1 there is a simple nonhomogeneous (actually regular and also modular) trellis [Formula: see text] such that any t-ary systolic tree automaton can be simulated in a universal and quite straighforward way on a trellis automaton over [Formula: see text]. This implies that the family of languages accepted by systolic tree automata, which is incomparable with the family of languages accepted by homogeneous systolic trellis automata, is actually contained in the family of languages accepted by trellis automata that are both regular and modular.

Some Structural Properties of Systolic Tree Automata

We prove that the classes of languages accepted by systolic automata over t-ary trees (t-STA) are always either equal or incomparable if one varies t. We introduce systolic tree automata with base (T(b)-STA), a subclass of STA with interesting properties of modularity, and we give a necessary and sufficient condition for the equivalence between a T(b)-STA and a t-STA, for a given base b. Finally, we show that the stability problem for T(b)-ST A is decidible.

Systolic tree implementation of data structures

Systolic tree architectures are presented for data structures such as stacks, queues, dequeues, priority queues, and dictionary machines. The stack, queue, and dequeue have a unit response time and a unit pipeline interval. The priority queue also has a unit response time, but the pipeline interval is 2. The response time and pipeline interval for the dictionary machine are O(log n) and O(1), respectively, where n is the number of data elements currently residing in the tree. In each node of the tree, the mechanism for controlling the transmission and distribution of data is finite state. This feature makes the designs presented here suitable for VLSI. If there are n data elements in the data structure, the depth of the tree is O(log n). >

Syntactic monoids in the construction of systolic tree automata

The acceptance of regular languages by systolic tree automata is analyzed in more detail by investigating the structure of the individual processors needed. Since the processors essentially compute the monoid product, our investigation leads to questions concerning syntactic monoids. Hereby certain properties of monoids turn out to be important. These properties, as well as the language families induced by them, are also studied in the paper.

A characterization of systolic binary tree automata and applications

This paper has two main contributions. The first is a natural and useful characterization of systolic binary tree automata (BTA's) in terms of a simple class of Turing machines. The second is a proof technique for showing that a language is not accepted by a BTA. Various closure properties of languages accepted by BTA's are easily obtained from these two results.

Systolic trellis automatata †

A new type of a systolic automaton, referred to as a systolic trellis automaton, is investigated. It consists of a triangularly shaped system of hexagonally connected processors (functional elements) where the flow of data is uni-directional and there is a fixed delay in all interconnections. Systolic trellis automata can be viewed as a special case of pure systolic systems [3]. Together with systolic tree automata, [6], trellis automata now constitute the most widely studied class of systolic automata, [4],[12]. We describe a variety of programming techniques for trellis automata. The techniques might be of interest for VLSI designers in the sense that a design methodology for VLSI circuits is involved. The power of these techniques is illustrated by several examples. Trellis automata are shown to possess quite surprising 2 capabilities. The languages accepted by trellis automata have time complexity O(n 2)with respect to deterministic Turing machines, and the family of acceptable languages is closed under Boolean operations. Special attention is focused on a subclass of trellis automata with all identical processors, referred to as homogeneous. It has been shown in [2] that the homogeneous trellis automata are exactly equivalent to the real-time one-way cellular automata.

On a family of L languages resulting from systolic tree automata

Recent work on systolic tree automata has given rise to a rather natural subfamily of EOL languages, referred to as systolic EOL languages in this paper. Systolic EOL languages possess some remarkable properties. While their family contains (because of its closure under Boolean operations) intuitively quite complicated languages, it still has decidable equivalence problem. Especially interesting is the fact that similar decision problems for slightly more general families lead to the celebrated open problems concerning Z-rational power series.