1721891
Lempel–Ziv Factorization Using Less Time & Space
Abstract.For 30 years the Lempel–Ziv factorization LZx of a string x = x[1..n] has been a fundamental data structure of string processing, especially valuable for string compression and for computing all the repetitions (runs) in x. Traditionally the standard method for computing LZx was based on Θ(n)-time (or, depending on the measure used, O(n log n)-time) processing of the suffix tree STx of x. Recently Abouelhoda et al. proposed an efficient Lempel–Ziv factorization algorithm based on an “enhanced” suffix array – that is, a suffix array SAx together with supporting data structures, principally an “interval tree”. In this paper we introduce a collection of fast space-efficient algorithms for LZ factorization, also based on suffix arrays, that in theory as well as in many practical circumstances are superior to those previously proposed; one family out of this collection achieves true Θ(n)-time alphabet-independent processing in the worst case by avoiding tree structures altogether.
1767089
Fast and Practical Algorithms for Computing All the Runs in a String
A repetition in a string x is a substring w = ue of x, maximum e ≥ 2, where u is not itself a repetition in w. A run in x is a substring w = ueu* of "maximal periodicity", where ue is a repetition and u* a maximum-length possibly empty proper prefix of u. A run may encode as many as |u| repetitions. The maximum number of repetitions in any string x = x[1..n] iswell known to be Θ(n log n). In 2000 Kolpakov & Kucherov showed that the maximum number of runs in x is O(n); they also described a Θ(n)-time algorithm, based on Farach's Θ(n)-time suffix tree construction algorithm (STCA), Θ(n)-time Lempel-Ziv factorization, and Main's Θ(n)-time leftmost runs algorithm, to compute all the runs in x. Recently Abouelhoda et al. proposed a Θ(n)-time Lempel-Ziv factorization algorithm based on an "enhanced" suffix array -- a suffix array together with other supporting data structures. In this paper we introduce a collection of fast space-efficient algorithms for computing all the runs in a string that appear in many circumstances to be superior to those previously proposed.
34970822
Mining Frequent Patterns in an Arbitrary Sliding Window over Data Streams
This paper proposes a method for mining the frequent patterns in an arbitrary sliding window of data streams. As streams flow, the contents of which are captured with SWP-tree by scanning the stream only once, and the obsolete and infrequent patterns are deleted by periodically pruning the tree. To differentiate the patterns of recently generated transactions from those of historic transactions, a time decaying model is also applied. The experimental results show that the proposed method is efficient and scalable, and it is superior to other analogous algorithms.
7865354
Modifying the DPClus algorithm for identifying protein complexes based on new topological structures
BackgroundIdentification of protein complexes is crucial for understanding principles of cellular organization and functions. As the size of protein-protein interaction set increases, a general trend is to represent the interactions as a network and to develop effective algorithms to detect significant complexes in such networks.ResultsBased on the study of known complexes in protein networks, this paper proposes a new topological structure for protein complexes, which is a combination of subgraph diameter (or average vertex distance) and subgraph density. Following the approach of that of the previously proposed clustering algorithm DPClus which expands clusters starting from seeded vertices, we present a clustering algorithm IPCA based on the new topological structure for identifying complexes in large protein interaction networks. The algorithm IPCA is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm IPCA recalls more known complexes than previously proposed clustering algorithms, including DPClus, CFinder, LCMA, MCODE, RNSC and STM.ConclusionThe proposed algorithm based on the new topological structure makes it possible to identify dense subgraphs in protein interaction networks, many of which correspond to known protein complexes. The algorithm is robust to the known high rate of false positives and false negatives in data from high-throughout interaction techniques. The program is available at http://netlab.csu.edu.cn/bioinformatics/limin/IPCA.
12333144
Query Triggered Crawling Strategy: Build a Time Sensitive Vertical Search Engine
In today's information society, it is important to retrieve fresh information. Many of the vertical search results are valid to users in only a short period of time. But due to resource constraints, it is not possible to keep the entire local storage synchronized with the Web. We implemented a TSVS (time sensitive vertical search engine) prototype named Velocisaurus focused on time-critical airfare discount information search to investigate the time critical requirements of vertical search and proposed a QTC (query triggered crawling) strategy to coordinate the crawling systems by real-time user queries and solve this problem. Experiment shows that QTC driven crawlers significantly improves the freshness of the search results and utilizes the resources more efficiently compared to regular search engine crawlers..
24158595
A Fractal Watermark Solution for Product Data
Copyright and integrity protection over product data is becoming an urgent requirement, because in a Distributed Networked Manufacturing environment, enterprises have to interact with each other to share product data. In this paper, we introduce a novel watermarking solution for product data based on the idea of fractal, which classifies product data watermarks into three tiers: fractal watermark, tree-structure watermark, and tree-node watermark. It embeds watermarks not only in value-carrying nodes but also in product structures that "glue" all the nodes together by embedding multiple structure watermarks in product data. Simulation results show that the proposed technique is robust against various forms of malicious attacks of product data, and naturally immune from structure transformation attacks and subtractive (sub-tree) attacks. Moreover, the solution can protect tree-structure data whose knowledge is mainly embodied in the tree structure efficiently. It is very easy to implement and popularize.
6814190
Adapting to Application Workflow in Processing Data Integration Queries
Data integration has evolved to provide efficient data management across distributed and heterogeneous data sources in grid environment. However, existing works in data integration consider little knowledge about the above applications. In such settings, queries from the same application are processed independently. In this paper, application properties are noticed in order to improve query performance for data integration. We present a general-purpose and well-modular architecture for addressing data integration in grid (DIG) environment first, the modules of which can be flexibly deployed to adapt specific application. Moreover, special attention has been paid on query processing to accommodate application workflow with the component of query flow processor. It introduces multi-query optimization techniques to speed up overall response time for DIG.