Sökning: "twitter data"

Visar resultat 1 - 5 av 28 avhandlingar innehållade orden twitter data.

1. 1. Understanding Human Mobility with Emerging Data Sources: Validation, spatiotemporal patterns, and transport modal disparity

   Författare :Yuan Liao; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; travel mode; data mining; travel time; mobility; social media data; gravity model; Twitter; geographical information systems;

   Sammanfattning : Human mobility refers to the geographic displacement of human beings, seen as individuals or groups, in space and time. The understanding of mobility has broad relevance, e.g., how fast epidemics spread globally. LÄS MER

3. 2. Privacy-awareness in the era of Big Data and machine learning

   Författare :Xuan-Son Vu; Lili Jiang; Erik Elmroth; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Differential Privacy; Machine Learning; Deep Learning; Big Data; datalogi; Computer Science;

   Sammanfattning : Social Network Sites (SNS) such as Facebook and Twitter, have been playing a great role in our lives. On the one hand, they help connect people who would not otherwise be connected before. LÄS MER

4. 3. Extraction and Energy Efficient Processing of Streaming Data

   Författare :Eva García-Martín; Niklas Lavesson; Håkan Grahn; Albert Bifet; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; machine learning; green computing; data mining; data stream mining; green machine learning;

   Sammanfattning : The interest in machine learning algorithms is increasing, in parallel with the advancements in hardware and software required to mine large-scale datasets. Machine learning algorithms account for a significant amount of energy consumed in data centers, which impacts the global energy consumption. LÄS MER

5. 4. Understanding Mobility and Transport Modal Disparities Using Emerging Data Sources: Modelling Potentials and Limitations

   Författare :Yuan Liao; Chalmers tekniska högskola; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; data mining; geographical information systems; mobility models; big trip data; transport modes; traffic data; social media data;

   Sammanfattning : Transportation presents a major challenge to curb climate change due in part to its ever-increasing travel demand. Better informed policy-making requires up-to-date empirical mobility data to model viable mitigation options for reducing emissions from the transport sector. LÄS MER

7. 5. Privacy-guardian : the vital need in machine learning with big data

   Författare :Xuan-Son Vu; Jiang Lili; Erik Elmroth; Stan Matwin; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : Social Network Sites (SNS) such as Facebook and Twitter, play a great role in our lives. On one hand, they help to connect people who would not otherwise be connected. Many recent breakthroughs in AI such as facial recognition [Kow+18], were achieved thanks to the amount of available data on the Internet via SNS (hereafter Big Data). LÄS MER