Querying large treebanks : benchmarking GrETEL indexing

The amount of data that is available for research grows rapidly, yet technology to efficiently interpret and excavate these data lags behind. For instance, when using large treebanks for linguistic research, the speed of a query leaves much to be desired. GrETEL Indexing, or GrInding, tackles this issue. The idea behind GrInding is to make the search space as small as possible before actually starting the treebank search, by pre-processing the treebank at hand. We recursively divide the treebank into smaller parts, called subtree-banks, which are then converted into database files. All subtree-banks are organized according to their linguistic dependency pattern, and labeled as such. Additionally, general patterns are linked to more specific ones. By doing so, we create millions of databases, and given a linguistic structure we know in which databases that structure can occur, leading up to a significant efficiency boost. We present the results of a benchmark experiment, testing the effect of the GrInding procedure on the SoNaR-500 treebank

An XML Query Engine for Network-Bound Data

XML has become the lingua franca for data exchange and integration across administrative and enterprise boundaries. Nearly all data providers are adding XML import or export capabilities, and standard XML Schemas and DTDs are being promoted for all types of data sharing. The ubiquity of XML has removed one of the major obstacles to integrating data from widely disparate sources –- namely, the heterogeneity of data formats. However, general-purpose integration of data across the wide area also requires a query processor that can query data sources on demand, receive streamed XML data from them, and combine and restructure the data into new XML output -- while providing good performance for both batch-oriented and ad-hoc, interactive queries. This is the goal of the Tukwila data integration system, the first system that focuses on network-bound, dynamic XML data sources. In contrast to previous approaches, which must read, parse, and often store entire XML objects before querying them, Tukwila can return query results even as the data is streaming into the system. Tukwila is built with a new system architecture that extends adaptive query processing and relational-engine techniques into the XML realm, as facilitated by a pair of operators that incrementally evaluate a query’s input path expressions as data is read. In this paper, we describe the Tukwila architecture and its novel aspects, and we experimentally demonstrate that Tukwila provides better overall query performance and faster initial answers than existing systems, and has excellent scalability

Parallel Suffix Tree Construction for Genome Sequence Using Hadoop

Indexing the genome is the basis for many of the bioinformatics applications. Read mapping (sequence alignment) is one such application to align millions of short reads against reference genome. Several tools like BLAST, SOAP, BOWTIE, Cloudburst, and Rapid Parallel Genome Indexing with MapReduce use indexing technique for aligning short reads. Many of the contemporary alignment techniques are time consuming, memory intensive and cannot be easily scaled to larger genomes. Suffix tree is a popular data structure which can be used to overcome the demerits of other alignment techniques. However, constructing the suffix tree is highly memory intensive and time consuming. In this thesis, a MapReduce based parallel construction of the suffix tree is proposed. The performance of the algorithm is measured on the hadoop framework over commodity cluster with each node having 8GB of primary memory. The results show a significantly less time for constructing suffix tree for a big data like human genome

Performance comparison of point and spatial access methods

In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

Introduction in IND and recursive partitioning

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, and lists the manual pages for the routines and instructions on installation

Wrapper Maintenance: A Machine Learning Approach

The proliferation of online information sources has led to an increased use of wrappers for extracting data from Web sources. While most of the previous research has focused on quick and efficient generation of wrappers, the development of tools for wrapper maintenance has received less attention. This is an important research problem because Web sources often change in ways that prevent the wrappers from extracting data correctly. We present an efficient algorithm that learns structural information about data from positive examples alone. We describe how this information can be used for two wrapper maintenance applications: wrapper verification and reinduction. The wrapper verification system detects when a wrapper is not extracting correct data, usually because the Web source has changed its format. The reinduction algorithm automatically recovers from changes in the Web source by identifying data on Web pages so that a new wrapper may be generated for this source. To validate our approach, we monitored 27 wrappers over a period of a year. The verification algorithm correctly discovered 35 of the 37 wrapper changes, and made 16 mistakes, resulting in precision of 0.73 and recall of 0.95. We validated the reinduction algorithm on ten Web sources. We were able to successfully reinduce the wrappers, obtaining precision and recall values of 0.90 and 0.80 on the data extraction task

Introduction to IND and recursive partitioning, version 1.0

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, lists the manual pages for the routines, and instructions on installation

Research into the design of distributed directory services

Distributed, computer based communication is becoming established within many working environments. Furthermore, the near future is likely to see an increase in the scale, complexity and usage of telecommunications services and distributed applications. As a result, there is a critical need for a global Directory service to store and manage communication information and therefore support the emerging world-wide telecommunications environment. This thesis describes research into the design of distributed Directory services. It addresses a number of Directory issues ranging from the abstract structure of information to the concrete implementation of a prototype system. In particular, it examines a number of management related issues concerning the management of communication information and the management of the Directory service itself. The following work develops models describing different aspects of Directory services. These include data access control and data integrity control models concerning the abstract structure and management of information as well as knowledge management, distributed operation and replication models concerning the realisation of the Directory as a distributed system. In order to clarify the relationships between these models, a layered directory architecture is proposed. This architecture provides a framework for the discussion of directory issues and defines the overall structure of this thesis. This thesis also describes the implementation of a prototype Directory service, supported by software tools typical of those currently available within many environments. It should be noted that, although this thesis emphasises the design of abstract directory models, development of the prototype consumed a large amount of time and effort and prototyping activities accounted for a substantial portion of this research. Finally, this thesis reaches a number of conclusions which are applied to the emerging ISO/CCITT X. 500 standard for Directory services, resulting in possible input for the 1988-92 study period