Matching Items (5)
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- All Subjects: Semantic Web
- All Subjects: Educational technology
- All Subjects: Graph Search
- Creators: Lindquist, Timothy
Description
The processing of large volumes of RDF data require an efficient storage and query processing engine that can scale well with the volume of data. The initial attempts to address this issue focused on optimizing native RDF stores as well as conventional relational databases management systems. But as the volume of RDF data grew to exponential proportions, the limitations of these systems became apparent and researchers began to focus on using big data analysis tools, most notably Hadoop, to process RDF data. Various studies and benchmarks that evaluate these tools for RDF data processing have been published. In the past two and half years, however, heavy users of big data systems, like Facebook, noted limitations with the query performance of these big data systems and began to develop new distributed query engines for big data that do not rely on map-reduce. Facebook's Presto is one such example.
This thesis deals with evaluating the performance of Presto in processing big RDF data against Apache Hive. A comparative analysis was also conducted against 4store, a native RDF store. To evaluate the performance Presto for big RDF data processing, a map-reduce program and a compiler, based on Flex and Bison, were implemented. The map-reduce program loads RDF data into HDFS while the compiler translates SPARQL queries into a subset of SQL that Presto (and Hive) can understand. The evaluation was done on four and eight node Linux clusters installed on Microsoft Windows Azure platform with RDF datasets of size 10, 20, and 30 million triples. The results of the experiment show that Presto has a much higher performance than Hive can be used to process big RDF data. The thesis also proposes an architecture based on Presto, Presto-RDF, that can be used to process big RDF data.
This thesis deals with evaluating the performance of Presto in processing big RDF data against Apache Hive. A comparative analysis was also conducted against 4store, a native RDF store. To evaluate the performance Presto for big RDF data processing, a map-reduce program and a compiler, based on Flex and Bison, were implemented. The map-reduce program loads RDF data into HDFS while the compiler translates SPARQL queries into a subset of SQL that Presto (and Hive) can understand. The evaluation was done on four and eight node Linux clusters installed on Microsoft Windows Azure platform with RDF datasets of size 10, 20, and 30 million triples. The results of the experiment show that Presto has a much higher performance than Hive can be used to process big RDF data. The thesis also proposes an architecture based on Presto, Presto-RDF, that can be used to process big RDF data.
ContributorsMammo, Mulugeta (Author) / Bansal, Srividya (Thesis advisor) / Bansal, Ajay (Committee member) / Lindquist, Timothy (Committee member) / Arizona State University (Publisher)
Created2014
Description
Graph theory is a critical component of computer science and software engineering, with algorithms concerning graph traversal and comprehension powering much of the largest problems in both industry and research. Engineers and researchers often have an accurate view of their target graph, however they struggle to implement a correct, and efficient, search over that graph.
To facilitate rapid, correct, efficient, and intuitive development of graph based solutions we propose a new programming language construct - the search statement. Given a supra-root node, a procedure which determines the children of a given parent node, and optional definitions of the fail-fast acceptance or rejection of a solution, the search statement can conduct a search over any graph or network. Structurally, this statement is modelled after the common switch statement and is put into a largely imperative/procedural context to allow for immediate and intuitive development by most programmers. The Go programming language has been used as a foundation and proof-of-concept of the search statement. A Go compiler is provided which implements this construct.
To facilitate rapid, correct, efficient, and intuitive development of graph based solutions we propose a new programming language construct - the search statement. Given a supra-root node, a procedure which determines the children of a given parent node, and optional definitions of the fail-fast acceptance or rejection of a solution, the search statement can conduct a search over any graph or network. Structurally, this statement is modelled after the common switch statement and is put into a largely imperative/procedural context to allow for immediate and intuitive development by most programmers. The Go programming language has been used as a foundation and proof-of-concept of the search statement. A Go compiler is provided which implements this construct.
ContributorsHenderson, Christopher (Author) / Bansal, Ajay (Thesis advisor) / Lindquist, Timothy (Committee member) / Acuna, Ruben (Committee member) / Arizona State University (Publisher)
Created2018
Description
Semantic web is the web of data that provides a common framework and technologies for sharing and reusing data in various applications. In semantic web terminology, linked data is the term used to describe a method of exposing and connecting data on the web from different sources. The purpose of linked data and semantic web is to publish data in an open and standard format and to link this data with existing data on the Linked Open Data Cloud. The goal of this thesis to come up with a semantic framework for integrating and publishing linked data on the web. Traditionally integrating data from multiple sources usually involves an Extract-Transform-Load (ETL) framework to generate datasets for analytics and visualization. The thesis proposes introducing a semantic component in the ETL framework to semi-automate the generation and publishing of linked data. In this thesis, various existing ETL tools and data integration techniques have been analyzed and deficiencies have been identified. This thesis proposes a set of requirements for the semantic ETL framework by conducting a manual process to integrate data from various sources such as weather, holidays, airports, flight arrival, departure and delays. The research questions that are addressed are: (i) to what extent can the integration, generation, and publishing of linked data to the cloud using a semantic ETL framework be automated; (ii) does use of semantic technologies produce a richer data model and integrated data. Details of the methodology, data collection, and application that uses the linked data generated are presented. Evaluation is done by comparing traditional data integration approach with semantic ETL approach in terms of effort involved in integration, data model generated and querying the data generated.
ContributorsPadki, Aparna (Author) / Bansal, Srividya (Thesis advisor) / Bansal, Ajay (Committee member) / Lindquist, Timothy (Committee member) / Arizona State University (Publisher)
Created2016
Description
Many organizational course design methodologies feature general guidelines for the chronological and time-management aspects of course design development. Proper course structure and instructional strategy pacing has been shown to facilitate student knowledge acquisition of novel material. These course-scheduling details influencing student learning outcomes implies the need for an effective and tightly coupled component of an instructional module. The Instructional Module Development System, or IMODS, seeks to improve STEM, or ‘science, technology, engineering, and math’, education, by equipping educators with a powerful informational tool that helps guide course design by providing information based on contemporary research about pedagogical methodology and assessment practices. This is particularly salient within the higher-education STEM fields because many instructors come from backgrounds that are more technical and most Ph.Ds. in science fields have traditionally not focused on preparing doctoral candidates to teach. This thesis project aims to apply a multidisciplinary approach, blending educational psychology and computer science, to help improve STEM education. By developing an instructional module-scheduling feature for the Web-based IMODS, Instructional Module Development System, system, we can help instructors plan out and organize their course work inside and outside of the classroom, while providing them with relevant helpful research that will help them improve their courses. This article illustrates the iterative design process to gather background research on pacing of workload and learning activities and their influence on student knowledge acquisition, constructively critique and analyze pre-existing information technology (IT) scheduling tools, synthesize graphical user interface, or GUI, mockups based on the background research, and then implement a functional-working prototype using the IMODs framework.
ContributorsCoomber, Wesley Poblete (Author) / Bansal, Srividya (Thesis director) / Lindquist, Timothy (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Plagiarism is a huge problem in a learning environment. In programming classes especially, plagiarism can be hard to detect as source codes' appearance can be easily modified without changing the intent through simple formatting changes or refactoring. There are a number of plagiarism detection tools that attempt to encode knowledge about the programming languages they support in order to better detect obscured duplicates. Many such tools do not support a large number of languages because doing so requires too much code and therefore too much maintenance. It is also difficult to add support for new languages because each language is vastly different syntactically. Tools that are more extensible often do so by reducing the features of a language that are encoded and end up closer to text comparison tools than structurally-aware program analysis tools.
Kitsune attempts to remedy these issues by tying itself to Antlr, a pre-existing language recognition tool with over 200 currently supported languages. In addition, it provides an interface through which generic manipulations can be applied to the parse tree generated by Antlr. As Kitsune relies on language-agnostic structure modifications, it can be adapted with minimal effort to provide plagiarism detection for new languages. Kitsune has been evaluated for 10 of the languages in the Antlr grammar repository with success and could easily be extended to support all of the grammars currently developed by Antlr or future grammars which are developed as new languages are written.
Kitsune attempts to remedy these issues by tying itself to Antlr, a pre-existing language recognition tool with over 200 currently supported languages. In addition, it provides an interface through which generic manipulations can be applied to the parse tree generated by Antlr. As Kitsune relies on language-agnostic structure modifications, it can be adapted with minimal effort to provide plagiarism detection for new languages. Kitsune has been evaluated for 10 of the languages in the Antlr grammar repository with success and could easily be extended to support all of the grammars currently developed by Antlr or future grammars which are developed as new languages are written.
ContributorsMonroe, Zachary Lynn (Author) / Bansal, Ajay (Thesis advisor) / Lindquist, Timothy (Committee member) / Acuna, Ruben (Committee member) / Arizona State University (Publisher)
Created2020