Research
Research Agenda
Our research agenda covers the following areas and is conducted within the confines of projects executed with industry partners:
- Database and Big Data technology
- Data Mining, Statistics and Predictive Modeling
- Machine Learning and Graph Analytics
- Information Retrieval and Natural Language Processing
- Business Intelligence and Visual Analytics
- Data Warehousing and Decision Support
- Communication and Visualization of Results
- Privacy, Security and Ethics
- Entrepreneurship and Data Product Design
R&D Projects
This list gets directly filled from ZHAW's project database. Not all projects may show up due to interlinkage aspects.
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DeLLA: Deep-Learning-based speech recognition with limited training material
Speech recognition systems baed on Deep Neural Networks (DNN) currently brake all records and is being applied already in different products. These systems normally are trained with thousands of hours of training material for applications and languages where these amounts of data are available. In this feasibility ...
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DeepScore: Digital Music Stand with Musical Understanding via Active Sheet Technology
_Management AbstractPlaying and enjoying music is amongst the most rewarding recreational activities of humankind for individuals as well as in group settings. Visiting concerts or sending one’s kids to music lessons - thus being enabled to discuss and co-shape the musical part of our culture - are hence important ...
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Complexity 4.0
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SAVE - Smart Alarms & Verified Events
False alarms are a major cost driver for owners of alarm systems. To remedy this problem, we develop a novel alarm verification service by leveraging the power of an alarm data warehouse. By analyzing live streams of alarms, comparing them with historic alarms and enriching them with information from open data, our ...
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EAT-IT
Based on long-standing work and a unique market position, Eaternity successfully distributes a solution for managing CO2 transparency covering the entire value added chain, from food product to full menu. This CTI project enables Eaternity to use the results of its groundwork and turn it into an attractive, scalable ...
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PANOPTES
The new product of ARGUS DATA INSIGHTS Schweiz AG "Real Time Print Media Monitoring" is an automated pipeline. It identifies relevant articles in print media, extracts them and sends them to the customers in real-time. Core of this project is the automated segmentation of full newspaper pages into articles, this is ...
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Roche Business Analytics
In this project we design and implement a prototype for solving a highly challenging business analytics use case at Roche. The prototype is based on state-of-the-art technology in the areas of advanced data management, information retrieval and machine learning.
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Urban Water Research Data Warehouse
In this project we develop a data warehouse for management of environmental sensor data. The idea is to integrate different data sets from various sensor data by leveraging modern data warehousing technology. The data management approach will open up new avenues for novel urban water research. ...
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Market Monitoring
The goal of this project is to develop an innovative market monitoring application for an e-commerce platform. The project is done in collaboration with an industry partner. Unlike traditional e-commerce applications where users need to log into the system and thus leave traces when they search for specific products ...
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A model based three-stage classifier for airborne particles
Computer controlled scanning electron microscopy (CCSEM) is a widely-used method for single airborne particle analysis. It produces large amounts of chemical and morphological data, whose processing and interpretation can be very time consuming. We have developed for Particle Vision GmbH an automated three-stage ...
SNF/NRP project: Bio-SODA
One of the major promises of Big Data lies in the simultaneous mining of multiple sources of data. This is particularly important in life sciences, where different and complementary data are scattered across multiple resources. To overcome this issue, the use of RDF/semantic web technology is emerging, but querying these systems often proves to be too complex for most users—thereby hampering wide development and adoption of these technologies.