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Dept: Computer Science  Dates: 2015 – 2019 Language: English

You searched for subject:(Education Data processing ). Showing records 1 – 30 of 416 total matches.

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1. Cao, Xiang. Efficient Data Management and Processing in Big Data Applications.

Degree: PhD, Computer Science, 2017, University of Minnesota

 In today's Big Data applications, huge amount of data are being generated. With the rapid growth of data amount, data management and processing become essential.… (more)

Subjects/Keywords: Big Data; Data Management; Data Processing

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APA (6th Edition):

Cao, X. (2017). Efficient Data Management and Processing in Big Data Applications. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/188863

Chicago Manual of Style (16th Edition):

Cao, Xiang. “Efficient Data Management and Processing in Big Data Applications.” 2017. Doctoral Dissertation, University of Minnesota. Accessed October 14, 2019. http://hdl.handle.net/11299/188863.

MLA Handbook (7th Edition):

Cao, Xiang. “Efficient Data Management and Processing in Big Data Applications.” 2017. Web. 14 Oct 2019.

Vancouver:

Cao X. Efficient Data Management and Processing in Big Data Applications. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/11299/188863.

Council of Science Editors:

Cao X. Efficient Data Management and Processing in Big Data Applications. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/188863


Rutgers University

2. Perry, Jason M. Putting secure computation to work.

Degree: PhD, Computer Science, 2015, Rutgers University

The demand for solutions that enable secure computation in distributed systems is only increasing. However, the current state of secure computation "in the wild'' is… (more)

Subjects/Keywords: Computer security; Electronic data processing – Distributed processing

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APA (6th Edition):

Perry, J. M. (2015). Putting secure computation to work. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/48624/

Chicago Manual of Style (16th Edition):

Perry, Jason M. “Putting secure computation to work.” 2015. Doctoral Dissertation, Rutgers University. Accessed October 14, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/48624/.

MLA Handbook (7th Edition):

Perry, Jason M. “Putting secure computation to work.” 2015. Web. 14 Oct 2019.

Vancouver:

Perry JM. Putting secure computation to work. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2019 Oct 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48624/.

Council of Science Editors:

Perry JM. Putting secure computation to work. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48624/


University of Illinois – Urbana-Champaign

3. Gao, Yihan. Extracting and utilizing hidden structures in large datasets.

Degree: PhD, Computer Science, 2019, University of Illinois – Urbana-Champaign

 The hidden structure within datasets  – capturing the inherent structure within the data not explicitly captured or encoded in the data format  – can often… (more)

Subjects/Keywords: Structure Extraction; Automatic Data Processing

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APA (6th Edition):

Gao, Y. (2019). Extracting and utilizing hidden structures in large datasets. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104764

Chicago Manual of Style (16th Edition):

Gao, Yihan. “Extracting and utilizing hidden structures in large datasets.” 2019. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 14, 2019. http://hdl.handle.net/2142/104764.

MLA Handbook (7th Edition):

Gao, Yihan. “Extracting and utilizing hidden structures in large datasets.” 2019. Web. 14 Oct 2019.

Vancouver:

Gao Y. Extracting and utilizing hidden structures in large datasets. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2019. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/2142/104764.

Council of Science Editors:

Gao Y. Extracting and utilizing hidden structures in large datasets. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104764


Massey University

4. Zhao, Yu. Event based transient notification architecture and NoSQL solution for astronomical data management.

Degree: PhD, Computer Science, 2015, Massey University

 This thesis describes the development of a messaging system for astrophysical transient event notifications, and explores the use of NoSQL databases for astronomical data management.… (more)

Subjects/Keywords: Astronomy; Data processing; Non-relational databases

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APA (6th Edition):

Zhao, Y. (2015). Event based transient notification architecture and NoSQL solution for astronomical data management. (Doctoral Dissertation). Massey University. Retrieved from http://hdl.handle.net/10179/8063

Chicago Manual of Style (16th Edition):

Zhao, Yu. “Event based transient notification architecture and NoSQL solution for astronomical data management.” 2015. Doctoral Dissertation, Massey University. Accessed October 14, 2019. http://hdl.handle.net/10179/8063.

MLA Handbook (7th Edition):

Zhao, Yu. “Event based transient notification architecture and NoSQL solution for astronomical data management.” 2015. Web. 14 Oct 2019.

Vancouver:

Zhao Y. Event based transient notification architecture and NoSQL solution for astronomical data management. [Internet] [Doctoral dissertation]. Massey University; 2015. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/10179/8063.

Council of Science Editors:

Zhao Y. Event based transient notification architecture and NoSQL solution for astronomical data management. [Doctoral Dissertation]. Massey University; 2015. Available from: http://hdl.handle.net/10179/8063


Rutgers University

5. Manousakis, Ioannis, 1988-. Cooling provisioning and reliability implications for cost-efficient datacenters.

Degree: PhD, Computer Science, 2018, Rutgers University

 Today and for the foreseeable future, demand for datacenter capacity is constantly increasing worldwide, primarily driven by cloud computing. Large cloud providers such as Amazon,… (more)

Subjects/Keywords: Data processing service centers – Design and construction; Data processing service centers – Energy consumption

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APA (6th Edition):

Manousakis, Ioannis, 1. (2018). Cooling provisioning and reliability implications for cost-efficient datacenters. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/57657/

Chicago Manual of Style (16th Edition):

Manousakis, Ioannis, 1988-. “Cooling provisioning and reliability implications for cost-efficient datacenters.” 2018. Doctoral Dissertation, Rutgers University. Accessed October 14, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/57657/.

MLA Handbook (7th Edition):

Manousakis, Ioannis, 1988-. “Cooling provisioning and reliability implications for cost-efficient datacenters.” 2018. Web. 14 Oct 2019.

Vancouver:

Manousakis, Ioannis 1. Cooling provisioning and reliability implications for cost-efficient datacenters. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2019 Oct 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57657/.

Council of Science Editors:

Manousakis, Ioannis 1. Cooling provisioning and reliability implications for cost-efficient datacenters. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57657/


Vanderbilt University

6. Yan, Wei. A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms.

Degree: PhD, Computer Science, 2015, Vanderbilt University

 In the era of âBig Dataâ, a variety of data processing and analysis frameworks (such as MapReduce/Hadoop, Dremel/Impala, and Storm) have emerged as a solution… (more)

Subjects/Keywords: Resource management; large-scale; data processing; data profiling; MapReduce/Hadoop

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APA (6th Edition):

Yan, W. (2015). A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-07172015-094917/ ;

Chicago Manual of Style (16th Edition):

Yan, Wei. “A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms.” 2015. Doctoral Dissertation, Vanderbilt University. Accessed October 14, 2019. http://etd.library.vanderbilt.edu/available/etd-07172015-094917/ ;.

MLA Handbook (7th Edition):

Yan, Wei. “A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms.” 2015. Web. 14 Oct 2019.

Vancouver:

Yan W. A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms. [Internet] [Doctoral dissertation]. Vanderbilt University; 2015. [cited 2019 Oct 14]. Available from: http://etd.library.vanderbilt.edu/available/etd-07172015-094917/ ;.

Council of Science Editors:

Yan W. A Data-Driven Approach to Optimal Resource Management for Large-Scale Data Processing Platforms. [Doctoral Dissertation]. Vanderbilt University; 2015. Available from: http://etd.library.vanderbilt.edu/available/etd-07172015-094917/ ;


University of California – Berkeley

7. Sun, Liwen. Skipping-oriented Data Design for Large-Scale Analytics.

Degree: Computer Science, 2017, University of California – Berkeley

 As data volumes continue to expand, analytics approaches that require exhaustively scanning data sets become untenable. For this reason, modern analytics systems employ data skipping… (more)

Subjects/Keywords: Computer science; big data; database design; data skipping; data warehousing; indexing; query processing

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APA (6th Edition):

Sun, L. (2017). Skipping-oriented Data Design for Large-Scale Analytics. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/1sq519hz

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sun, Liwen. “Skipping-oriented Data Design for Large-Scale Analytics.” 2017. Thesis, University of California – Berkeley. Accessed October 14, 2019. http://www.escholarship.org/uc/item/1sq519hz.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sun, Liwen. “Skipping-oriented Data Design for Large-Scale Analytics.” 2017. Web. 14 Oct 2019.

Vancouver:

Sun L. Skipping-oriented Data Design for Large-Scale Analytics. [Internet] [Thesis]. University of California – Berkeley; 2017. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/1sq519hz.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sun L. Skipping-oriented Data Design for Large-Scale Analytics. [Thesis]. University of California – Berkeley; 2017. Available from: http://www.escholarship.org/uc/item/1sq519hz

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – Riverside

8. Vora, Keval. Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing.

Degree: Computer Science, 2017, University of California – Riverside

 While various iterative graph algorithms can be expressed via asynchronous parallelism, lack of its proper understanding limits the performance benefits that can be achieved via… (more)

Subjects/Keywords: Computer science; Asynchronous Processing; Big Data; Distributed Computing; Graph Processing; Parallel Computing

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APA (6th Edition):

Vora, K. (2017). Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/6x33d81c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vora, Keval. “Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing.” 2017. Thesis, University of California – Riverside. Accessed October 14, 2019. http://www.escholarship.org/uc/item/6x33d81c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vora, Keval. “Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing.” 2017. Web. 14 Oct 2019.

Vancouver:

Vora K. Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing. [Internet] [Thesis]. University of California – Riverside; 2017. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/6x33d81c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vora K. Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing. [Thesis]. University of California – Riverside; 2017. Available from: http://www.escholarship.org/uc/item/6x33d81c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


UCLA

9. Vu, Thuy. Feature Representation in Mining and Language Processing.

Degree: Computer Science, 2017, UCLA

 Feature representation has been one of the most important factors for the success of machine learning algorithms. Since 2006, deep learning has been widely considered… (more)

Subjects/Keywords: Computer science; data mining; feature representation; large scale data processing; machine learning; natural language processing; neural network

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APA (6th Edition):

Vu, T. (2017). Feature Representation in Mining and Language Processing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/9g54h388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vu, Thuy. “Feature Representation in Mining and Language Processing.” 2017. Thesis, UCLA. Accessed October 14, 2019. http://www.escholarship.org/uc/item/9g54h388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vu, Thuy. “Feature Representation in Mining and Language Processing.” 2017. Web. 14 Oct 2019.

Vancouver:

Vu T. Feature Representation in Mining and Language Processing. [Internet] [Thesis]. UCLA; 2017. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/9g54h388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vu T. Feature Representation in Mining and Language Processing. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/9g54h388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – Irvine

10. Bu, Yingyi. On Software Infrastructure for Scalable Graph Analytics.

Degree: Computer Science, 2015, University of California – Irvine

 Recently, there is a growing need for distributed graph processing systems that are capable of gracefully scaling to very large datasets. In the mean time,… (more)

Subjects/Keywords: Computer science; Big Data Analytics; Big Graph Analytics; Database Systems; Parallel Data Processing

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APA (6th Edition):

Bu, Y. (2015). On Software Infrastructure for Scalable Graph Analytics. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/7px2636z

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bu, Yingyi. “On Software Infrastructure for Scalable Graph Analytics.” 2015. Thesis, University of California – Irvine. Accessed October 14, 2019. http://www.escholarship.org/uc/item/7px2636z.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bu, Yingyi. “On Software Infrastructure for Scalable Graph Analytics.” 2015. Web. 14 Oct 2019.

Vancouver:

Bu Y. On Software Infrastructure for Scalable Graph Analytics. [Internet] [Thesis]. University of California – Irvine; 2015. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/7px2636z.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bu Y. On Software Infrastructure for Scalable Graph Analytics. [Thesis]. University of California – Irvine; 2015. Available from: http://www.escholarship.org/uc/item/7px2636z

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Wright State University

11. Marupudi, Surendra Brahma. Framework for Semantic Integration and Scalable Processing of City Traffic Events.

Degree: MS, Computer Science, 2016, Wright State University

 Intelligent traffic management requires analysis of a large volume of multimodal data from diverse domains. For the development of intelligent traffic applications, we need to… (more)

Subjects/Keywords: Computer Science; Lambda Architecture, Traffic data, Semantic Web, Scalable processing

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APA (6th Edition):

Marupudi, S. B. (2016). Framework for Semantic Integration and Scalable Processing of City Traffic Events. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847

Chicago Manual of Style (16th Edition):

Marupudi, Surendra Brahma. “Framework for Semantic Integration and Scalable Processing of City Traffic Events.” 2016. Masters Thesis, Wright State University. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847.

MLA Handbook (7th Edition):

Marupudi, Surendra Brahma. “Framework for Semantic Integration and Scalable Processing of City Traffic Events.” 2016. Web. 14 Oct 2019.

Vancouver:

Marupudi SB. Framework for Semantic Integration and Scalable Processing of City Traffic Events. [Internet] [Masters thesis]. Wright State University; 2016. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847.

Council of Science Editors:

Marupudi SB. Framework for Semantic Integration and Scalable Processing of City Traffic Events. [Masters Thesis]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847


University of California – Irvine

12. Borkar, Vinayak Ravindra. An Efficient Foundation for Big Data Processing on Modern Clusters.

Degree: Computer Science, 2016, University of California – Irvine

 In recent years, the world has seen an explosion in the amount of data being generated. Google proposed the MapReduce framework to allow programmers easily… (more)

Subjects/Keywords: Computer science; big data; database; mapreduce; parallel; query processing; scalable

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APA (6th Edition):

Borkar, V. R. (2016). An Efficient Foundation for Big Data Processing on Modern Clusters. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/9bd8639j

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Borkar, Vinayak Ravindra. “An Efficient Foundation for Big Data Processing on Modern Clusters.” 2016. Thesis, University of California – Irvine. Accessed October 14, 2019. http://www.escholarship.org/uc/item/9bd8639j.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Borkar, Vinayak Ravindra. “An Efficient Foundation for Big Data Processing on Modern Clusters.” 2016. Web. 14 Oct 2019.

Vancouver:

Borkar VR. An Efficient Foundation for Big Data Processing on Modern Clusters. [Internet] [Thesis]. University of California – Irvine; 2016. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/9bd8639j.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Borkar VR. An Efficient Foundation for Big Data Processing on Modern Clusters. [Thesis]. University of California – Irvine; 2016. Available from: http://www.escholarship.org/uc/item/9bd8639j

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

13. Ahmed, Amr. Kite: A Scalable Microblogs Data Management System.

Degree: PhD, Computer Science, 2017, University of Minnesota

 Developers, researchers, and practitioners have been building a myriad of applications to analyze microblogs data, e.g., tweets, online reviews, and user comments. Examples of such… (more)

Subjects/Keywords: Data; Index; Memory management; Microblogs; Query Processing; Twitter

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ahmed, A. (2017). Kite: A Scalable Microblogs Data Management System. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/190480

Chicago Manual of Style (16th Edition):

Ahmed, Amr. “Kite: A Scalable Microblogs Data Management System.” 2017. Doctoral Dissertation, University of Minnesota. Accessed October 14, 2019. http://hdl.handle.net/11299/190480.

MLA Handbook (7th Edition):

Ahmed, Amr. “Kite: A Scalable Microblogs Data Management System.” 2017. Web. 14 Oct 2019.

Vancouver:

Ahmed A. Kite: A Scalable Microblogs Data Management System. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/11299/190480.

Council of Science Editors:

Ahmed A. Kite: A Scalable Microblogs Data Management System. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/190480


University of Illinois – Urbana-Champaign

14. Peng, Boyang. Elasticity and resource aware scheduling in distributed data stream processing systems.

Degree: MS, Computer Science, 2015, University of Illinois – Urbana-Champaign

 The era of big data has led to the emergence of new systems for real-time distributed stream processing, e.g., Apache Storm is one of the… (more)

Subjects/Keywords: Elasticity; Resource Aware Scheduling; Storm; Distributed Data Stream Processing

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APA (6th Edition):

Peng, B. (2015). Elasticity and resource aware scheduling in distributed data stream processing systems. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Peng, Boyang. “Elasticity and resource aware scheduling in distributed data stream processing systems.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed October 14, 2019. http://hdl.handle.net/2142/78453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Peng, Boyang. “Elasticity and resource aware scheduling in distributed data stream processing systems.” 2015. Web. 14 Oct 2019.

Vancouver:

Peng B. Elasticity and resource aware scheduling in distributed data stream processing systems. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/2142/78453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Peng B. Elasticity and resource aware scheduling in distributed data stream processing systems. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

15. Yu, Hongkun. Multi-theme sentiment analysis with sentiment shifting.

Degree: MS, Computer Science, 2016, University of Illinois – Urbana-Champaign

 Business reviews contain rich sentiment on multiple themes, disclosing more interesting information than the overall polarities of documents. When it comes to fine-grained sentiment analysis,… (more)

Subjects/Keywords: Sentiment Analysis; Multi-theme; Natural language processing (NLP); Data Mining

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APA (6th Edition):

Yu, H. (2016). Multi-theme sentiment analysis with sentiment shifting. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90799

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yu, Hongkun. “Multi-theme sentiment analysis with sentiment shifting.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed October 14, 2019. http://hdl.handle.net/2142/90799.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yu, Hongkun. “Multi-theme sentiment analysis with sentiment shifting.” 2016. Web. 14 Oct 2019.

Vancouver:

Yu H. Multi-theme sentiment analysis with sentiment shifting. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/2142/90799.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yu H. Multi-theme sentiment analysis with sentiment shifting. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90799

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Georgia

16. Cotterell, Michael Edward. Supporting open science in big data frameworks and data science education.

Degree: PhD, Computer Science, 2017, University of Georgia

 As the prevalence of data grows throughout the Big Data era, so does a need to provide and improve tools for the education and application… (more)

Subjects/Keywords: open science; open notebooks; big data frameworks; data science; data science education

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APA (6th Edition):

Cotterell, M. E. (2017). Supporting open science in big data frameworks and data science education. (Doctoral Dissertation). University of Georgia. Retrieved from http://hdl.handle.net/10724/37663

Chicago Manual of Style (16th Edition):

Cotterell, Michael Edward. “Supporting open science in big data frameworks and data science education.” 2017. Doctoral Dissertation, University of Georgia. Accessed October 14, 2019. http://hdl.handle.net/10724/37663.

MLA Handbook (7th Edition):

Cotterell, Michael Edward. “Supporting open science in big data frameworks and data science education.” 2017. Web. 14 Oct 2019.

Vancouver:

Cotterell ME. Supporting open science in big data frameworks and data science education. [Internet] [Doctoral dissertation]. University of Georgia; 2017. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/10724/37663.

Council of Science Editors:

Cotterell ME. Supporting open science in big data frameworks and data science education. [Doctoral Dissertation]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37663


Texas State University – San Marcos

17. Ye, Yuxiang. Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

 Human’s sketch understanding is an important and challenging research problem. It has many applications in human computer interaction, multimedia, and computer vision. Most previous methods… (more)

Subjects/Keywords: Deep learning; Convolutional neural network; Pattern recognition; Computer vision; Optical data processing; Computer graphics; Image processing – Digital techniques

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APA (6th Edition):

Ye, Y. (2016). Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6050

Chicago Manual of Style (16th Edition):

Ye, Yuxiang. “Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed October 14, 2019. https://digital.library.txstate.edu/handle/10877/6050.

MLA Handbook (7th Edition):

Ye, Yuxiang. “Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval.” 2016. Web. 14 Oct 2019.

Vancouver:

Ye Y. Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2019 Oct 14]. Available from: https://digital.library.txstate.edu/handle/10877/6050.

Council of Science Editors:

Ye Y. Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6050


Georgia Tech

18. Sengupta, Dipanjan. System design principles for heterogeneous resource management and scheduling in accelerator-based systems.

Degree: PhD, Computer Science, 2016, Georgia Tech

 Accelerator-based systems are making rapid inroads into becoming platforms of choice for both high end cloud services and processing irregular applications like real-world graph analytics… (more)

Subjects/Keywords: Multi-tenancy; Hierarchical scheduling; Runtime systems; Virtualization; GPU; CUDA; Graph analytics; Big data; Performance optimization; Data movement optimization; Incremental processing

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APA (6th Edition):

Sengupta, D. (2016). System design principles for heterogeneous resource management and scheduling in accelerator-based systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55607

Chicago Manual of Style (16th Edition):

Sengupta, Dipanjan. “System design principles for heterogeneous resource management and scheduling in accelerator-based systems.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 14, 2019. http://hdl.handle.net/1853/55607.

MLA Handbook (7th Edition):

Sengupta, Dipanjan. “System design principles for heterogeneous resource management and scheduling in accelerator-based systems.” 2016. Web. 14 Oct 2019.

Vancouver:

Sengupta D. System design principles for heterogeneous resource management and scheduling in accelerator-based systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/1853/55607.

Council of Science Editors:

Sengupta D. System design principles for heterogeneous resource management and scheduling in accelerator-based systems. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55607


Texas State University – San Marcos

19. Lindquist, Robert Stephenson. Defragmenting Social Networks.

Degree: MS, Computer Science, 2017, Texas State University – San Marcos

 The scale of Online Social Networks, like Facebook, requires splitting users across many servers; unfortunately, this can spread one user's friends across hundreds of servers,… (more)

Subjects/Keywords: Graph Partitioning; Social Networks; High performance computing; Computer algorithms; Social networks; Big data; Graph theory – Data processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lindquist, R. S. (2017). Defragmenting Social Networks. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6928

Chicago Manual of Style (16th Edition):

Lindquist, Robert Stephenson. “Defragmenting Social Networks.” 2017. Masters Thesis, Texas State University – San Marcos. Accessed October 14, 2019. https://digital.library.txstate.edu/handle/10877/6928.

MLA Handbook (7th Edition):

Lindquist, Robert Stephenson. “Defragmenting Social Networks.” 2017. Web. 14 Oct 2019.

Vancouver:

Lindquist RS. Defragmenting Social Networks. [Internet] [Masters thesis]. Texas State University – San Marcos; 2017. [cited 2019 Oct 14]. Available from: https://digital.library.txstate.edu/handle/10877/6928.

Council of Science Editors:

Lindquist RS. Defragmenting Social Networks. [Masters Thesis]. Texas State University – San Marcos; 2017. Available from: https://digital.library.txstate.edu/handle/10877/6928


University of California – Irvine

20. Oktay, Kerim Yasin. Using Hybrid Clouds for Secure and Efficient Data Processing.

Degree: Computer Science, 2015, University of California – Irvine

 Fueled with the advances in virtualization and high-speed networking, cloud computing has emerged as a dominant computing paradigm. Loss of control over the data due… (more)

Subjects/Keywords: Computer science; cloud computing; efficient; hybrid clouds; mapreduce bigdata; secure data processing; SQL

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Oktay, K. Y. (2015). Using Hybrid Clouds for Secure and Efficient Data Processing. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/8jt2h3h3

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Oktay, Kerim Yasin. “Using Hybrid Clouds for Secure and Efficient Data Processing.” 2015. Thesis, University of California – Irvine. Accessed October 14, 2019. http://www.escholarship.org/uc/item/8jt2h3h3.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Oktay, Kerim Yasin. “Using Hybrid Clouds for Secure and Efficient Data Processing.” 2015. Web. 14 Oct 2019.

Vancouver:

Oktay KY. Using Hybrid Clouds for Secure and Efficient Data Processing. [Internet] [Thesis]. University of California – Irvine; 2015. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/8jt2h3h3.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Oktay KY. Using Hybrid Clouds for Secure and Efficient Data Processing. [Thesis]. University of California – Irvine; 2015. Available from: http://www.escholarship.org/uc/item/8jt2h3h3

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Boston University

21. Meng, Xianrui. Privacy-preserving queries on encrypted databases.

Degree: PhD, Computer Science, 2016, Boston University

 In today's Internet, with the advent of cloud computing, there is a natural desire for enterprises, organizations, and end users to outsource increasingly large amounts… (more)

Subjects/Keywords: Computer science; Cryptography; Database security; Data management; Graph theory; Information security/privacy; Query processing

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APA (6th Edition):

Meng, X. (2016). Privacy-preserving queries on encrypted databases. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/19739

Chicago Manual of Style (16th Edition):

Meng, Xianrui. “Privacy-preserving queries on encrypted databases.” 2016. Doctoral Dissertation, Boston University. Accessed October 14, 2019. http://hdl.handle.net/2144/19739.

MLA Handbook (7th Edition):

Meng, Xianrui. “Privacy-preserving queries on encrypted databases.” 2016. Web. 14 Oct 2019.

Vancouver:

Meng X. Privacy-preserving queries on encrypted databases. [Internet] [Doctoral dissertation]. Boston University; 2016. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/2144/19739.

Council of Science Editors:

Meng X. Privacy-preserving queries on encrypted databases. [Doctoral Dissertation]. Boston University; 2016. Available from: http://hdl.handle.net/2144/19739


University of California – San Diego

22. Lin, Chunbin. Accelerating Analytic Queries on Compressed Data.

Degree: Computer Science, 2018, University of California – San Diego

Data compression techniques (both lossless and lossy compression methods) are widely utilized in big data analytic applications in domains including health-care, transportation, and finance. The… (more)

Subjects/Keywords: Computer science; Analytic queries; Approximate query processing; Column database; Data compression; Time series database

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APA (6th Edition):

Lin, C. (2018). Accelerating Analytic Queries on Compressed Data. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/4rc3108c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Chunbin. “Accelerating Analytic Queries on Compressed Data.” 2018. Thesis, University of California – San Diego. Accessed October 14, 2019. http://www.escholarship.org/uc/item/4rc3108c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Chunbin. “Accelerating Analytic Queries on Compressed Data.” 2018. Web. 14 Oct 2019.

Vancouver:

Lin C. Accelerating Analytic Queries on Compressed Data. [Internet] [Thesis]. University of California – San Diego; 2018. [cited 2019 Oct 14]. Available from: http://www.escholarship.org/uc/item/4rc3108c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin C. Accelerating Analytic Queries on Compressed Data. [Thesis]. University of California – San Diego; 2018. Available from: http://www.escholarship.org/uc/item/4rc3108c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Vanderbilt University

23. Bao, Shunxing. Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing.

Degree: PhD, Computer Science, 2018, Vanderbilt University

 Large-scale medical imaging studies to date have predominantly leveraged in-house, laboratory-based or traditional grid computing resources for their computing needs, where the applications often use… (more)

Subjects/Keywords: cloud computing; grid computing; medical image processing; Apache Hadoop ecosystem; Big data infrastructure

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APA (6th Edition):

Bao, S. (2018). Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-11222018-050053/ ;

Chicago Manual of Style (16th Edition):

Bao, Shunxing. “Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed October 14, 2019. http://etd.library.vanderbilt.edu/available/etd-11222018-050053/ ;.

MLA Handbook (7th Edition):

Bao, Shunxing. “Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing.” 2018. Web. 14 Oct 2019.

Vancouver:

Bao S. Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2019 Oct 14]. Available from: http://etd.library.vanderbilt.edu/available/etd-11222018-050053/ ;.

Council of Science Editors:

Bao S. Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://etd.library.vanderbilt.edu/available/etd-11222018-050053/ ;


Vanderbilt University

24. Li, Muqun. Scalable Natural Language De-identification based on Machine Learning Approaches.

Degree: PhD, Computer Science, 2018, Vanderbilt University

 Electronic medical record (EMR) systems have been progressively adopted in numerous aspects of clinical care and healthcare endeavors. As the quantity and diversity of such… (more)

Subjects/Keywords: de-identification; game theory; EMR; active learning; machine learning; natural language processing; data privacy; clustering

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APA (6th Edition):

Li, M. (2018). Scalable Natural Language De-identification based on Machine Learning Approaches. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-03262018-113355/ ;

Chicago Manual of Style (16th Edition):

Li, Muqun. “Scalable Natural Language De-identification based on Machine Learning Approaches.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed October 14, 2019. http://etd.library.vanderbilt.edu/available/etd-03262018-113355/ ;.

MLA Handbook (7th Edition):

Li, Muqun. “Scalable Natural Language De-identification based on Machine Learning Approaches.” 2018. Web. 14 Oct 2019.

Vancouver:

Li M. Scalable Natural Language De-identification based on Machine Learning Approaches. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2019 Oct 14]. Available from: http://etd.library.vanderbilt.edu/available/etd-03262018-113355/ ;.

Council of Science Editors:

Li M. Scalable Natural Language De-identification based on Machine Learning Approaches. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://etd.library.vanderbilt.edu/available/etd-03262018-113355/ ;


University of Illinois – Urbana-Champaign

25. Kim, Minje. Audio computing in the wild: frameworks for big data and small computers.

Degree: PhD, Computer Science, 2016, University of Illinois – Urbana-Champaign

 This dissertation presents some machine learning algorithms that are designed to process as much data as needed while spending the least possible amount of resources,… (more)

Subjects/Keywords: Machine Learning; Signal Processing; Blind Source Separation; Big Data; Deep Learning; Neural Networks

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APA (6th Edition):

Kim, M. (2016). Audio computing in the wild: frameworks for big data and small computers. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90573

Chicago Manual of Style (16th Edition):

Kim, Minje. “Audio computing in the wild: frameworks for big data and small computers.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 14, 2019. http://hdl.handle.net/2142/90573.

MLA Handbook (7th Edition):

Kim, Minje. “Audio computing in the wild: frameworks for big data and small computers.” 2016. Web. 14 Oct 2019.

Vancouver:

Kim M. Audio computing in the wild: frameworks for big data and small computers. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/2142/90573.

Council of Science Editors:

Kim M. Audio computing in the wild: frameworks for big data and small computers. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90573


University of Minnesota

26. Beksi, William. Topological Methods for 3D Point Cloud Processing.

Degree: PhD, Computer Science, 2018, University of Minnesota

 3D point cloud datasets are becoming more common due to the availability of low-cost sensors. Light detection and ranging (LIDAR), stereo, structured light, and time-of-flight… (more)

Subjects/Keywords: Applied Topology; Computational Topology; Computer Vision; Persistent Homology; Point Cloud Processing; Topological Data Analysis

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APA (6th Edition):

Beksi, W. (2018). Topological Methods for 3D Point Cloud Processing. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/201078

Chicago Manual of Style (16th Edition):

Beksi, William. “Topological Methods for 3D Point Cloud Processing.” 2018. Doctoral Dissertation, University of Minnesota. Accessed October 14, 2019. http://hdl.handle.net/11299/201078.

MLA Handbook (7th Edition):

Beksi, William. “Topological Methods for 3D Point Cloud Processing.” 2018. Web. 14 Oct 2019.

Vancouver:

Beksi W. Topological Methods for 3D Point Cloud Processing. [Internet] [Doctoral dissertation]. University of Minnesota; 2018. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/11299/201078.

Council of Science Editors:

Beksi W. Topological Methods for 3D Point Cloud Processing. [Doctoral Dissertation]. University of Minnesota; 2018. Available from: http://hdl.handle.net/11299/201078


Colorado State University

27. Mishra, Sitakanta. Leveraging stream processing engines in support of physiological data processing.

Degree: MS(M.S.), Computer Science, 2018, Colorado State University

 Over the last decade, there has been an exponential growth in unbounded streaming data generated by sensing devices in different settings including the Internet-of-Things. Several… (more)

Subjects/Keywords: Predictive Analytics; Stream Processing Engines; Real time data analysis; Internet of Things

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APA (6th Edition):

Mishra, S. (2018). Leveraging stream processing engines in support of physiological data processing. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/191375

Chicago Manual of Style (16th Edition):

Mishra, Sitakanta. “Leveraging stream processing engines in support of physiological data processing.” 2018. Masters Thesis, Colorado State University. Accessed October 14, 2019. http://hdl.handle.net/10217/191375.

MLA Handbook (7th Edition):

Mishra, Sitakanta. “Leveraging stream processing engines in support of physiological data processing.” 2018. Web. 14 Oct 2019.

Vancouver:

Mishra S. Leveraging stream processing engines in support of physiological data processing. [Internet] [Masters thesis]. Colorado State University; 2018. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/10217/191375.

Council of Science Editors:

Mishra S. Leveraging stream processing engines in support of physiological data processing. [Masters Thesis]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191375


Georgia Tech

28. Maass, Steffen Alexander. Systems abstractions for big data processing on a single machine.

Degree: PhD, Computer Science, 2019, Georgia Tech

 Large-scale internet services, such as Facebook or Google, are using clusters of many servers for problems such as search, machine learning, and social networks. However,… (more)

Subjects/Keywords: Runtime system; Big data; Graph analytics; Performance optimization; Incremental processing; Heterogeneous computing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Maass, S. A. (2019). Systems abstractions for big data processing on a single machine. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61679

Chicago Manual of Style (16th Edition):

Maass, Steffen Alexander. “Systems abstractions for big data processing on a single machine.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 14, 2019. http://hdl.handle.net/1853/61679.

MLA Handbook (7th Edition):

Maass, Steffen Alexander. “Systems abstractions for big data processing on a single machine.” 2019. Web. 14 Oct 2019.

Vancouver:

Maass SA. Systems abstractions for big data processing on a single machine. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/1853/61679.

Council of Science Editors:

Maass SA. Systems abstractions for big data processing on a single machine. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61679


Texas State University – San Marcos

29. Mahant, Vaibhav. Improving Top-N Evaluation of Recommender Systems.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

 Recommender systems are used to provide the user with a list of recommended items to help user find new items they might prefer. One of… (more)

Subjects/Keywords: Recommender Systems; Evaluation; Recommender systems (Information filtering); Management information systems; Artificial intelligence – Data processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mahant, V. (2016). Improving Top-N Evaluation of Recommender Systems. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6309

Chicago Manual of Style (16th Edition):

Mahant, Vaibhav. “Improving Top-N Evaluation of Recommender Systems.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed October 14, 2019. https://digital.library.txstate.edu/handle/10877/6309.

MLA Handbook (7th Edition):

Mahant, Vaibhav. “Improving Top-N Evaluation of Recommender Systems.” 2016. Web. 14 Oct 2019.

Vancouver:

Mahant V. Improving Top-N Evaluation of Recommender Systems. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2019 Oct 14]. Available from: https://digital.library.txstate.edu/handle/10877/6309.

Council of Science Editors:

Mahant V. Improving Top-N Evaluation of Recommender Systems. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6309


Texas State University – San Marcos

30. Kazi, Mohammed Imran Rukmoddin. Exploring Potentially Discriminatory Biases In Book Recommendation.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

 Recent issues which occurred in the field of artificial intelligence present disproportionality based on protected attributes such as sex, race, and ethnicity in their output… (more)

Subjects/Keywords: Recsys; Recommender systems (Information filtering); Management information systems; Artificial intelligence – Data processing

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APA (6th Edition):

Kazi, M. I. R. (2016). Exploring Potentially Discriminatory Biases In Book Recommendation. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6306

Chicago Manual of Style (16th Edition):

Kazi, Mohammed Imran Rukmoddin. “Exploring Potentially Discriminatory Biases In Book Recommendation.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed October 14, 2019. https://digital.library.txstate.edu/handle/10877/6306.

MLA Handbook (7th Edition):

Kazi, Mohammed Imran Rukmoddin. “Exploring Potentially Discriminatory Biases In Book Recommendation.” 2016. Web. 14 Oct 2019.

Vancouver:

Kazi MIR. Exploring Potentially Discriminatory Biases In Book Recommendation. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2019 Oct 14]. Available from: https://digital.library.txstate.edu/handle/10877/6306.

Council of Science Editors:

Kazi MIR. Exploring Potentially Discriminatory Biases In Book Recommendation. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6306

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