Search for dissertations about: "thesis on clustering methods in data mining"

Showing result 1 - 5 of 12 swedish dissertations containing the words thesis on clustering methods in data mining.

2. 1. Data Stream Mining and Analysis : Clustering Evolving Data

   Author : Christian Nordahl; Håkan Grahn; Veselka Boeva; Marie Netz; Plamen Angelov; Blekinge Tekniska Högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Data Stream Mining; Clustering; Data Streams; Data Mining; Computer Science; Datavetenskap;

   Abstract : Streaming data is becoming more prevalent in our society every day. With the increasing use of technologies such as the Internet of Things (IoT) and 5G networks, the number of possible data sources steadily increases. Therefore, there is a need to develop algorithms that can handle the massive amount of data we now generate. READ MORE

4. 2. Everyday mining : Exploring sequences in event-based data

   Author : Katerina Vrotsou; Matthew Cooper; Anders Ynnerman; Kajsa Ellegård; Andrew S. Harvey; Linköpings universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Event-based data; activity diary data; event-sequences; interactive exploration; sequence identification; visual data mining; Computer science; Datavetenskap;

   Abstract : Event-based data are encountered daily in many disciplines and are used for various purposes. They are collections of ordered sequences of events where each event has a start time and a duration. READ MORE

5. 3. Mining Speech Sounds : Machine Learning Methods for Automatic Speech Recognition and Analysis

   Author : Giampiero Salvi; Björn Granström; Torbjørn Svendsen; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; speech; machine learning; data mining; signal processing; Computer science; Datavetenskap;

   Abstract : This thesis collects studies on machine learning methods applied to speech technology and speech research problems. The six research papers included in this thesis are organised in three main areas. The first group of studies were carried out within the European project Synface. READ MORE

6. 4. Data Mining Approaches for Outlier Detection Analysis

   Author : Shahrooz Abghari; Niklas Lavesson; Håkan Grahn; Veselka Boeva; Olga Fink; Blekinge Tekniska Högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; outlier detection; data modelling; machine learning; clustering analysis; data stream mining; Computer Science; Datavetenskap;

   Abstract : Outlier detection is studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging task that can reveal system faults, fraud, and save people's lives. READ MORE

7. 5. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users

   Author : Dong Wang; Mats Tysklind; Johan Trygg; Lili Jiang; Venkat Venkatasubramanian; Umeå universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wastewater treatment; Process analytics; Big data; Machine learning; Interpretable AI; Power plants; Failure analysis; Data mining; Buildings; Energy consumption; Anomaly detection;

   Abstract : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. READ MORE