Now showing items 1-20 of 21

    • OutbreakSum: Automatic Summarization of Texts Relating to Disease Outbreaks 

      Gruss, Richard; Morgado, Daniel; Craun, Nate; Shea-Blymyer, Colin (2014-12)
      The goal of the fall 2014 Disease Outbreak Project (OutbreakSum) was to develop software for automatically analyzing and summarizing large collections of texts pertaining to disease outbreaks. Although our code was tested ...
    • Summarizing Fire Events with Natural Language Processing 

      Plahn, Jordan; Zamani, Michael; Lee, Hayden; Trujillo, Michael (2014-12)
      Throughout this semester, we were driven by one question: how do we best summarize a fire with articles scraped from the internet? We took a variety of approaches to answer it, incrementally constructing a solution to ...
    • Computational Linguistic Analysis of Earthquake Collections 

      Bialousz, Kenneth; Kokal, Kevin; Orleans-Pobee, Kwamina; Wakeley, Chris (2014-12)
      CS4984 is a newly-offered class at Virginia Tech with a unit based, project-problem based learning curriculum. This class style is based on NSF-funded work on curriculum for the field of digital libraries and related topics, ...
    • Exploring the Blacksburg Community Events Collection 

      Antol, Stanislaw; Ayoub, Souleiman; Folgar, Carlos; Smith, Steve (2014-12)
      With the advent of new technology, especially the combination of smart phones and widespread Internet access, people are increasingly becoming absorbed in digital worlds – worlds that are not bounded by geography. As such, ...
    • Computational Linguistics Hurricane Group 

      Crowder, Nicholas; Nguyen, David; Hsu, Andy; Mecklenburg, Will; Morris, Jeff (2014-12)
      The problem-project based learning described in our presentation and report addresses automatic summarization of web content using natural language processing. Initially, we used simple techniques such as word frequencies ...
    • Generating an Intelligent Human-Readable Summary of a Shooting Event from a Large Collection of Webpages 

      Chandrasekaran, Arjun; Sharma, Saurav; Sulucz, Peter; Tran, Jonathan (2014-12)
      We describe our approach to generating summaries of a shooting event from a large collection of webpages. We work with two separate events - a shooting at a school in Newtown, Connecticut and another at a mall in Tucson, ...
    • Natural Language Processing: Generating a Summary of Flood Disasters 

      Acanfora, Joseph; Evangelista, Marc; Keimig, David; Su, Myron (2014-12)
      In the event of a natural disaster like a flood, news outlets are in a rush to produce coverage for the general public. People may want a clear, concise summary of the event without having to read through hundreds of ...
    • Big Data Text Summarization: Using Deep Learning to Summarize Theses and Dissertations 

      Ahuja, Naman; Bansal, Ritesh; Ingram, William A.; Jude, Palakh; Kahu, Sampanna; Wang, Xinyue (Virginia Tech, 2018-12-05)
      Team 16 in the fall 2018 course "CS 4984/5984 Big Data Text Summarization," in partnership with the University Libraries and the Digital Library Research Laboratory, prepared a corpus of electronic theses and dissertations ...
    • Automatic Summarization of News Articles about Hurricane Florence 

      Wanye, Frank; Ganguli, Samit; Tuckman, Matt; Zhang, Joy; Zhang, Fangzheng (Virginia Tech, 2018-12-07)
      We present our approach for generating automatic summaries from a collection of news articles acquired from the World Wide Web relating to Hurricane Florence. Our approach consists of 10 distinct steps, at the end of which ...
    • Big Data Text Summarization for the NeverAgain Movement 

      Arora, Anuj; Miller, Chreston; Fan, Jixiang; Liu, Shuai; Han, Yi (Virginia Tech, 2018-12-10)
      When you are browsing social media websites such as Twitter and Facebook, have you ever seen hashtags like #NeverAgain and #EnoughIsEnough? Do you know what they mean? Never Again is an American student-led political ...
    • Abstractive Text Summarization of the Parkland Shooting Collection 

      Kingery, Ryan; Yellapantula, Sudha Ravali; Xu, Chao; Huang, Li Jun; Ye, Jiacheng (Virginia Tech, 2018-12-12)
      We analyze various ways to perform abstractive text summarization on an entire collection of news articles. We specifically seek to summarize the collection of web-archived news articles relating to the 2018 shooting at ...
    • Big Data Text Summarization - Hurricane Harvey 

      Geissinger, Jack; Long, Theo; Jung, James; Parent, Jordan; Rizzo, Robert (Virginia Tech, 2018-12-12)
      Natural language processing (NLP) has advanced in recent years. Accordingly, we present progressively more complex generated text summaries on the topic Hurricane Harvey. We utilized TextRank, which is an unsupervised ...
    • Summarization of Maryland Shooting Collection 

      Khawas, Prapti; Banerjee, Bipasha; Zhao, Shuqi; Fan, Yiyang; Kim, Yoonjin (Virginia Tech, 2018-12-12)
      The goal of this work is to generate summaries of two Maryland shooting events from a large collection of web pages related to a shooting at Great Mills High School and another at the Capital Gazette newsroom. Since our ...
    • Big Data Text Summarization - Hurricane Irma 

      Chava, Raja Venkata Satya Phanindra; Dhar, Siddharth; Gaur, Yamini; Rambhakta, Pranavi; Shetty, Sourabh (Virginia Tech, 2018-12-13)
      With the increased rate of content generation on the Internet, there is a pressing need for making tools to automate the process of extracting meaningful data. Big data analytics deals with researching patterns or implicit ...
    • Generating Text Summaries for the Facebook Data Breach with Prototyping on the 2017 Solar Eclipse 

      Hamilton, Leah; Robb, Esther; Fitzpatrick, April; Goel, Akshay; Nandigam, Ramya (Virginia Tech, 2018-12-13)
      Summarization is often a time-consuming task for humans. Automated methods can summarize a larger volume of source material in a shorter amount of time, but creating a good summary with these methods remains challenging. ...
    • Big Data: New Zealand Earthquakes Summary 

      Bochel, Alexander; Edmisten, William; Lee, Jun; Chandalura, Rohit (Virginia Tech, 2018-12-14)
      The purpose of this Big Data project was to create a computer generated text summary of a major earthquake event in New Zealand. The summary was to be created from a large webpage dataset supplied for our team. This dataset ...
    • Hybrid Summarization of Dakota Access Pipeline Protests (NoDAPL) 

      Chen, Xiaoyu; Wang, Haitao; Mehrotra, Maanav; Chhikara, Naman; Sun, Di (Virginia Tech, 2018-12-14)
      Dakota Access Pipeline Protests (known with the hashtag #NoDAPL) are grassroots movements that began in April 2016 in reaction to the approved construction of Energy Transfer Partners’ Dakota Access Pipeline in the northern ...
    • Hurricane Matthew Summarization 

      Goldsworthy, Michael; Tran, Thoang; Asif, Areeb; Gregos, Brendan (Virginia Tech, 2018-12-14)
      The report, presentation, and code for our project for the course CS 4984/5984: Big Data Text Summarization are included in this submission. Our team had to explore methods of text summarization for two datasets, and report ...
    • CS4984/CS5984: Big Data Text Summarization Team 10 ETDs 

      Baghudana, Ashish; Li, Guangchen; Liu, Beichen; Lasky, Stephen (Virginia Tech, 2018-12-14)
      Automatic text summarization is the task of creating accurate and succinct summaries of text documents. These documents can vary from newspaper articles to more academic content such as theses and dissertations. The two ...
    • Big Data Text Summarization - Attack Westminster 

      Gallagher, Colm; Dyer, Jamie; Liebold, Jeanine; Becker, Aaron; Yang, Limin (Virginia Tech, 2018-12-14)
      Automatic text summarization, a process of distilling the most important information from a text document, is to create an abridged summary with software. Basically, in this task, we can regard the "summarization" as a ...