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You searched for +publisher:"University of Cincinnati" +contributor:("Annexstein, Fred"). Showing records 1 – 13 of 13 total matches.

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University of Cincinnati

1. Nerusupalli, Sathvik. Personalized User Trending Topics.

Degree: MS, Engineering and Applied Science: Computer Science, 2011, University of Cincinnati

 Online Social networks have a cornucopia of interesting information waiting to be tapped and understood. Trending topics is one of the easier ways to understand… (more)

Subjects/Keywords: Computer Science; Twitter; Trending Topics; Personalized; Trends; stop words

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APA (6th Edition):

Nerusupalli, S. (2011). Personalized User Trending Topics. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321888962

Chicago Manual of Style (16th Edition):

Nerusupalli, Sathvik. “Personalized User Trending Topics.” 2011. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321888962.

MLA Handbook (7th Edition):

Nerusupalli, Sathvik. “Personalized User Trending Topics.” 2011. Web. 16 Jun 2019.

Vancouver:

Nerusupalli S. Personalized User Trending Topics. [Internet] [Masters thesis]. University of Cincinnati; 2011. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321888962.

Council of Science Editors:

Nerusupalli S. Personalized User Trending Topics. [Masters Thesis]. University of Cincinnati; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321888962


University of Cincinnati

2. Rathee, Nupur. Attack Detection in Recommender Systems using Clustering Techniques.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

  Expansion of internet has provided people with a plethora of information and choices. It has also brought along with it a problem to sort… (more)

Subjects/Keywords: Computer Science

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APA (6th Edition):

Rathee, N. (2008). Attack Detection in Recommender Systems using Clustering Techniques. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211475789

Chicago Manual of Style (16th Edition):

Rathee, Nupur. “Attack Detection in Recommender Systems using Clustering Techniques.” 2008. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211475789.

MLA Handbook (7th Edition):

Rathee, Nupur. “Attack Detection in Recommender Systems using Clustering Techniques.” 2008. Web. 16 Jun 2019.

Vancouver:

Rathee N. Attack Detection in Recommender Systems using Clustering Techniques. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211475789.

Council of Science Editors:

Rathee N. Attack Detection in Recommender Systems using Clustering Techniques. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211475789


University of Cincinnati

3. Owusu-Kesseh, Daniel. The Relative Security Metric of Information Systems: Using AIMD Algorithms.

Degree: MS, Engineering and Applied Science: Computer Science, 2016, University of Cincinnati

 Security metrics are required to provide a quantitative and objective basis for security operations. The quantitative and objective basis is needed to support decision making,… (more)

Subjects/Keywords: Computer Science; Security Metrics; Additive Increase and Multiplicative Decrease; AIMD algorithm; Security Ranking; Common Vulnerability Scoring System; CVSS and AIMD

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APA (6th Edition):

Owusu-Kesseh, D. (2016). The Relative Security Metric of Information Systems: Using AIMD Algorithms. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857

Chicago Manual of Style (16th Edition):

Owusu-Kesseh, Daniel. “The Relative Security Metric of Information Systems: Using AIMD Algorithms.” 2016. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857.

MLA Handbook (7th Edition):

Owusu-Kesseh, Daniel. “The Relative Security Metric of Information Systems: Using AIMD Algorithms.” 2016. Web. 16 Jun 2019.

Vancouver:

Owusu-Kesseh D. The Relative Security Metric of Information Systems: Using AIMD Algorithms. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857.

Council of Science Editors:

Owusu-Kesseh D. The Relative Security Metric of Information Systems: Using AIMD Algorithms. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857


University of Cincinnati

4. Schmidt, Samuel. A Massively Parallel Algorithm for Cell Classification Using CUDA.

Degree: MS, Engineering and Applied Science: Computer Science, 2015, University of Cincinnati

 In Bioinformatics, cell classification is the act of separating human cells into different groups based on their RNA-seq expression levels. These data can be quite… (more)

Subjects/Keywords: Computer Science; Cell Classification; Parallel Computing; CUDA; Machine Learning; Naive Bayes; CUDA Reduce

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APA (6th Edition):

Schmidt, S. (2015). A Massively Parallel Algorithm for Cell Classification Using CUDA. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873851

Chicago Manual of Style (16th Edition):

Schmidt, Samuel. “A Massively Parallel Algorithm for Cell Classification Using CUDA.” 2015. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873851.

MLA Handbook (7th Edition):

Schmidt, Samuel. “A Massively Parallel Algorithm for Cell Classification Using CUDA.” 2015. Web. 16 Jun 2019.

Vancouver:

Schmidt S. A Massively Parallel Algorithm for Cell Classification Using CUDA. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873851.

Council of Science Editors:

Schmidt S. A Massively Parallel Algorithm for Cell Classification Using CUDA. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873851


University of Cincinnati

5. Strunjas, Svetlana. Algorithms and Models for Collaborative Filtering from Large Information Corpora.

Degree: PhD, Engineering : Computer Science, 2008, University of Cincinnati

  In this thesis we propose novel collaborative filtering approaches for large data sets. We also demonstrate how these collaborative approaches can be used for… (more)

Subjects/Keywords: Computer Science; collaborative filtering; collaborative partitioning; clustering; information retrieval

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APA (6th Edition):

Strunjas, S. (2008). Algorithms and Models for Collaborative Filtering from Large Information Corpora. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1220001182

Chicago Manual of Style (16th Edition):

Strunjas, Svetlana. “Algorithms and Models for Collaborative Filtering from Large Information Corpora.” 2008. Doctoral Dissertation, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1220001182.

MLA Handbook (7th Edition):

Strunjas, Svetlana. “Algorithms and Models for Collaborative Filtering from Large Information Corpora.” 2008. Web. 16 Jun 2019.

Vancouver:

Strunjas S. Algorithms and Models for Collaborative Filtering from Large Information Corpora. [Internet] [Doctoral dissertation]. University of Cincinnati; 2008. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1220001182.

Council of Science Editors:

Strunjas S. Algorithms and Models for Collaborative Filtering from Large Information Corpora. [Doctoral Dissertation]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1220001182

6. Chase, Chelsea. Using Design Patterns in User Interface Design.

Degree: MS, Engineering and Applied Science: Computer Science, 2012, University of Cincinnati

 User interface development is a large part of software development and is highly visible to the user. It’s important to create a good user interface… (more)

Subjects/Keywords: Computer Science; User Interface; UI; Interaction; Design; Pattern; Facebook

…when a user who has listed the University of Cincinnati as his school types in “University of… …into the search bar, the University of Cincinnati makes up the top search results because… 

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APA (6th Edition):

Chase, C. (2012). Using Design Patterns in User Interface Design. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342463458

Chicago Manual of Style (16th Edition):

Chase, Chelsea. “Using Design Patterns in User Interface Design.” 2012. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342463458.

MLA Handbook (7th Edition):

Chase, Chelsea. “Using Design Patterns in User Interface Design.” 2012. Web. 16 Jun 2019.

Vancouver:

Chase C. Using Design Patterns in User Interface Design. [Internet] [Masters thesis]. University of Cincinnati; 2012. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342463458.

Council of Science Editors:

Chase C. Using Design Patterns in User Interface Design. [Masters Thesis]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342463458

7. Bhoompally, Rohit. Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs.

Degree: MS, Engineering and Applied Science: Computer Science, 2015, University of Cincinnati

 The aim of this thesis is to analyze algorithms that efficiently rank businesses (restaurants, bars, theatres, cafes etc.) of a social network. In this thesis,… (more)

Subjects/Keywords: Computer Science; Preference pairs; ranking; recommendations; Yelp; ranking comparision; paired preferences

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APA (6th Edition):

Bhoompally, R. (2015). Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308101

Chicago Manual of Style (16th Edition):

Bhoompally, Rohit. “Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs.” 2015. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308101.

MLA Handbook (7th Edition):

Bhoompally, Rohit. “Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs.” 2015. Web. 16 Jun 2019.

Vancouver:

Bhoompally R. Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308101.

Council of Science Editors:

Bhoompally R. Analysis of business ranking for a connected group of Yelp users by aggregating preference pairs. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308101

8. Williams, Garrick J. Abstracting Glicko-2 for Team Games.

Degree: MS, Engineering and Applied Science: Computer Science, 2015, University of Cincinnati

 Research experiments were conducted to further the development of rating player skill withinthe context of online team games with small team sizes. Modern rating systems… (more)

Subjects/Keywords: Computer Science; skill rating; player ranking; algorithms; glicko; online games; team games

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APA (6th Edition):

Williams, G. J. (2015). Abstracting Glicko-2 for Team Games. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427962458

Chicago Manual of Style (16th Edition):

Williams, Garrick J. “Abstracting Glicko-2 for Team Games.” 2015. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427962458.

MLA Handbook (7th Edition):

Williams, Garrick J. “Abstracting Glicko-2 for Team Games.” 2015. Web. 16 Jun 2019.

Vancouver:

Williams GJ. Abstracting Glicko-2 for Team Games. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427962458.

Council of Science Editors:

Williams GJ. Abstracting Glicko-2 for Team Games. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427962458

9. Lautzenheiser, Daniel E. Measuring the Influence of a User on Twitter.

Degree: MS, Engineering and Applied Science: Computer Science, 2013, University of Cincinnati

 This thesis focuses on the problem of measuring the influence of a user on Twitter. Twitter is a micro-blogging service and one of the most… (more)

Subjects/Keywords: Computer Science; twitter influence

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APA (6th Edition):

Lautzenheiser, D. E. (2013). Measuring the Influence of a User on Twitter. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426103

Chicago Manual of Style (16th Edition):

Lautzenheiser, Daniel E. “Measuring the Influence of a User on Twitter.” 2013. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426103.

MLA Handbook (7th Edition):

Lautzenheiser, Daniel E. “Measuring the Influence of a User on Twitter.” 2013. Web. 16 Jun 2019.

Vancouver:

Lautzenheiser DE. Measuring the Influence of a User on Twitter. [Internet] [Masters thesis]. University of Cincinnati; 2013. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426103.

Council of Science Editors:

Lautzenheiser DE. Measuring the Influence of a User on Twitter. [Masters Thesis]. University of Cincinnati; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426103

10. Villora, Narasiman C. Distributed degree-constrained application-level multicast tree: A partitioning approach.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

  In this thesis, we present a distributed algorithm for determining a degree-constrained multicast tree in the application layer, which reduces the average latency. We… (more)

Subjects/Keywords: Computer Science; Degree-constrained; Multicast; spanning tree; partitioning

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APA (6th Edition):

Villora, N. C. (2008). Distributed degree-constrained application-level multicast tree: A partitioning approach. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1205964934

Chicago Manual of Style (16th Edition):

Villora, Narasiman C. “Distributed degree-constrained application-level multicast tree: A partitioning approach.” 2008. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1205964934.

MLA Handbook (7th Edition):

Villora, Narasiman C. “Distributed degree-constrained application-level multicast tree: A partitioning approach.” 2008. Web. 16 Jun 2019.

Vancouver:

Villora NC. Distributed degree-constrained application-level multicast tree: A partitioning approach. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1205964934.

Council of Science Editors:

Villora NC. Distributed degree-constrained application-level multicast tree: A partitioning approach. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1205964934

11. Peng, Shuyue. Optimal Semantic Labeling of Social Network Clusters.

Degree: MS, Engineering and Applied Science: Computer Science, 2014, University of Cincinnati

 Twitter is one of the most popular social networking services. By analyzing social network data, meaningful information can be discovered, such as popular topics users… (more)

Subjects/Keywords: Computer Science; clustering; social network; semantic label

…of University of Cincinnati @gobearcats 475 OFFICIAL twitter account of the University… …Cincinnati Bearcats @coachcroninuc 240 Mick Cronin: Head coach of the University of Cincinnati… …mainestory 123 Jermaine Lawrence : Basketball player in University of Cincinnati @TTuberville… …119 Tommy Tuberville: Head Football Coach of University of Cincinnati Bearcats @uofcincy… …100 OFFICIAL twitter account of University of Cincinnati @coachclearyuc 97 Brian Cleary… 

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APA (6th Edition):

Peng, S. (2014). Optimal Semantic Labeling of Social Network Clusters. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821134

Chicago Manual of Style (16th Edition):

Peng, Shuyue. “Optimal Semantic Labeling of Social Network Clusters.” 2014. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821134.

MLA Handbook (7th Edition):

Peng, Shuyue. “Optimal Semantic Labeling of Social Network Clusters.” 2014. Web. 16 Jun 2019.

Vancouver:

Peng S. Optimal Semantic Labeling of Social Network Clusters. [Internet] [Masters thesis]. University of Cincinnati; 2014. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821134.

Council of Science Editors:

Peng S. Optimal Semantic Labeling of Social Network Clusters. [Masters Thesis]. University of Cincinnati; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821134

12. Alluri, Anjaneya Varma. Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence.

Degree: MS, Engineering and Applied Science: Computer Science, 2015, University of Cincinnati

 This thesis focuses on finding the key attributes of a social network of friends that help us to understand and measure the `Susceptibility’ of a… (more)

Subjects/Keywords: Computer Science; Susceptibility; Influence; Yelp; Logistic Regression; friend network; Data Attributes

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APA (6th Edition):

Alluri, A. V. (2015). Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439281364

Chicago Manual of Style (16th Edition):

Alluri, Anjaneya Varma. “Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence.” 2015. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439281364.

MLA Handbook (7th Edition):

Alluri, Anjaneya Varma. “Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence.” 2015. Web. 16 Jun 2019.

Vancouver:

Alluri AV. Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439281364.

Council of Science Editors:

Alluri AV. Empirical Study On Key Attributes of Yelp dataset which Account for Susceptibility of a user to Social Influence. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439281364


University of Cincinnati

13. Jovanovic, Mihajlo A. Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella.

Degree: MS, Engineering : Computer Science, 2001, University of Cincinnati

 The ongoing digital revolution has brought on the emergence of novel network applications such as Gnutella, Freenet, and Napster, intended to facilitate worldwide sharing of… (more)

Subjects/Keywords: Computer Science; network modeling; peer-to-peer; topology discovery; short-circuiting; small-world; power-laws; Gnutella

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APA (6th Edition):

Jovanovic, M. A. (2001). Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin989967592

Chicago Manual of Style (16th Edition):

Jovanovic, Mihajlo A. “Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella.” 2001. Masters Thesis, University of Cincinnati. Accessed June 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin989967592.

MLA Handbook (7th Edition):

Jovanovic, Mihajlo A. “Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella.” 2001. Web. 16 Jun 2019.

Vancouver:

Jovanovic MA. Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella. [Internet] [Masters thesis]. University of Cincinnati; 2001. [cited 2019 Jun 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin989967592.

Council of Science Editors:

Jovanovic MA. Modeling Large-scale Peer-to-Peer Networks and a Case Study of Gnutella. [Masters Thesis]. University of Cincinnati; 2001. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin989967592

.