Matching Items (136)

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Second Chance, A Mobile Literacy Application for Unschooled Adults

Description

This project seeks to improve the reading and writing skills of literacy-challenged adults, specifically in developing countries, by designing and developing an interactive tablet application for unschooled adults who are

This project seeks to improve the reading and writing skills of literacy-challenged adults, specifically in developing countries, by designing and developing an interactive tablet application for unschooled adults who are passionate about learning to read. Very often in developing countries, the success rates of the literacy courses are overwhelmingly low. Those who manage to gain some basic literacy skills, often relapse into illiteracy once their program has terminated. The proposed application aims to address this challenge by providing an easy-to-use media environment for independent literacy learning on a lightweight portable device. This also offers opportunity to learn at the time and place convenient to the user, which is additionally supported by motivating and engaging instruction. For this thesis, we focus on the design of the system and have developed a working prototype.

Contributors

Agent

Created

Date Created
  • 2013-05

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GCKEngine - An Algorithm for Automatic Ontology Building

Description

To facilitate the development of the Semantic Web, we propose in this thesis a general automatic ontology-building algorithm which, given a pool of potential terms and a set of relationships

To facilitate the development of the Semantic Web, we propose in this thesis a general automatic ontology-building algorithm which, given a pool of potential terms and a set of relationships to include in the ontology, can utilize information gathered from Google queries to build a full ontology for a certain domain. We utilized this ontology-building algorithm as part of a larger system to tag computer tutorials for three systems with different kinds of metadata, and index the tagged documents into a search engine. Our evaluation of the resultant search engine indicates that our automatic ontology-building algorithm is able to build relatively good-quality ontologies and utilize this ontology to effectively apply metadata to documents.

Contributors

Agent

Created

Date Created
  • 2013-05

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NBA PlayerTrack: A Mobile Application Providing NBA Fans with Statistics, News, and Information about their Favorite Players

Description

Current popular NBA mobile applications do little to provide information about the NBA's players, usually providing limited statistical information or news and completely ignoring players' presence on social media. For

Current popular NBA mobile applications do little to provide information about the NBA's players, usually providing limited statistical information or news and completely ignoring players' presence on social media. For fans, especially fans who are unfamiliar with the NBA, finding this information by themselves can be a daunting task, one which requires extensive knowledge about how the NBA provides media related to its players. NBA PlayerTrack has been designed to centralize player information from a variety of media streams, making it easier for fans to learn about and stay up-to-date with players and enabling fan discussion about those players and the NBA in general. By providing a variety of references to the locations of player information, NBA PlayerTrack also serves as a tool for learning about how and where the NBA presents player-related media, allowing fans to more easily locate information they desire as they become more invested in the NBA.

Contributors

Agent

Created

Date Created
  • 2015-12

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Analysis of the Aftereffects of Terror Attacks on Social Media

Description

Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that

Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that goes beyond the screen and affects behavior. During terror attacks or worldwide crises, people turn to social media as a means of managing their anxiety, a mechanism of Terror Management Theory (TMT). These opinions have distinct impacts on the emotions that people express both online and offline through both positive and negative sentiments. This paper focuses on using sentiment analysis on twitter hash-tags during five major terrorist attacks that created a significant response on social media, which collectively show the effects that 140-character tweets have on perceptions in social media. The purpose of analyzing the sentiments of tweets after terror attacks allows for the visualization of the effect of key-words and the possibility of manipulation by the use of emotional contagion. Through sentiment analysis, positive, negative and neutral emotions were portrayed in the tweets. The keywords detected also portray characteristics about terror attacks which would allow for future analysis and predictions in regards to propagating a specific emotion on social media during future crisis.

Contributors

Created

Date Created
  • 2016-12

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ORTHOGONAL RANK-ONE MATRIX PURSUIT FOR LOW RANK MATRIX COMPLETION

Description

In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend the orthogonal matching pursuit method from the vector case to

In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend the orthogonal matching pursuit method from the vector case to the matrix case. We further propose an economic version of our algorithm by introducing a novel weight updating rule to reduce the time and storage complexity. Both versions are computationally inexpensive for each matrix pursuit iteration and find satisfactory results in a few iterations. Another advantage of our proposed algorithm is that it has only one tunable parameter, which is the rank. It is easy to understand and to use by the user. This becomes especially important in large-scale learning problems. In addition, we rigorously show that both versions achieve a linear convergence rate, which is significantly better than the previous known results. We also empirically compare the proposed algorithms with several state-of-the-art matrix completion algorithms on many real-world datasets, including the large-scale recommendation dataset Netflix as well as the MovieLens datasets. Numerical results show that our proposed algorithm is more efficient than competing algorithms while achieving similar or better prediction performance.

Contributors

Agent

Created

Date Created
  • 2014-11-30

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Developing Inventory Control and Build Management Software for Spacecraft Engineering

Description

Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and

Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and strenuous, software custom-built for such processes can prove essential. The work for this project was developing ICDB, an inventory control and build management system created for spacecraft engineers at ASU to record each step of their engineering processes. In-house development means ICDB is more precisely designed around its users' functionality and cost requirements than most off-the-shelf commercial offerings. By placing a complex relational database behind an intuitive web application, ICDB enables organizations and their users to create and store parts libraries, assembly designs, purchasing and location records for inventory items, and more.

Contributors

Agent

Created

Date Created
  • 2018-05

Predicting Bitcoin Price Trend using Sentiment Analysis

Description

In this paper I defend the argument that public reaction to news headlines correlates with the short-term price direction of Bitcoin. I collected a month's worth of Bitcoin data consisting

In this paper I defend the argument that public reaction to news headlines correlates with the short-term price direction of Bitcoin. I collected a month's worth of Bitcoin data consisting of news headlines, tweets, and the price of the cryptocurrency. I fed this data into a Long Short-Term Memory Neural Network and built a model that predicted Bitcoin price for a new timeframe. The model correctly predicted 75% of test set price trends on 3.25 hour time intervals. This is higher than the 53.57% accuracy tested with a Bitcoin price model without sentiment data. I concluded public reaction to Bitcoin news headlines has an effect on the short-term price direction of the cryptocurrency. Investors can use my model to help them in their decision-making process when making short-term Bitcoin investment decisions.

Contributors

Agent

Created

Date Created
  • 2020-05

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CPR complex pattern ranking for evaluating top-k pattern queries over event streams

Description

Most existing approaches to complex event processing over streaming data rely on the assumption that the matches to the queries are rare and that the goal of the system is

Most existing approaches to complex event processing over streaming data rely on the assumption that the matches to the queries are rare and that the goal of the system is to identify these few matches within the incoming deluge of data. In many applications, such as stock market analysis and user credit card purchase pattern monitoring, however the matches to the user queries are in fact plentiful and the system has to efficiently sift through these many matches to locate only the few most preferable matches. In this work, we propose a complex pattern ranking (CPR) framework for specifying top-k pattern queries over streaming data, present new algorithms to support top-k pattern queries in data streaming environments, and verify the effectiveness and efficiency of the proposed algorithms. The developed algorithms identify top-k matching results satisfying both patterns as well as additional criteria. To support real-time processing of the data streams, instead of computing top-k results from scratch for each time window, we maintain top-k results dynamically as new events come and old ones expire. We also develop new top-k join execution strategies that are able to adapt to the changing situations (e.g., sorted and random access costs, join rates) without having to assume a priori presence of data statistics. Experiments show significant improvements over existing approaches.

Contributors

Agent

Created

Date Created
  • 2011

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Sequence-based web page template detection

Description

Templates are wildly used in Web sites development. Finding the template for a given set of Web pages could be very important and useful for many applications like Web page

Templates are wildly used in Web sites development. Finding the template for a given set of Web pages could be very important and useful for many applications like Web page classification and monitoring content and structure changes of Web pages. In this thesis, two novel sequence-based Web page template detection algorithms are presented. Different from tree mapping algorithms which are based on tree edit distance, sequence-based template detection algorithms operate on the Prüfer/Consolidated Prüfer sequences of trees. Since there are one-to-one correspondences between Prüfer/Consolidated Prüfer sequences and trees, sequence-based template detection algorithms identify the template by finding a common subsequence between to Prüfer/Consolidated Prüfer sequences. This subsequence should be a sequential representation of a common subtree of input trees. Experiments on real-world web pages showed that our approaches detect templates effectively and efficiently.

Contributors

Agent

Created

Date Created
  • 2011