2020 Theses
Milanov, Emil: An alternative confusion matrix visualization for PreCall
Kern, Kim: Ideator Types in Electronic Brainstorming
Gnanasegaram, Sajeera: Konzept und Implementierung einer visuellen Methode zur Verbesserung der Interpretierbarkeit der automatisierten Qualitätsbewertung mit ORES in Wikidata
Joppien, Lilli: Result-driven Interactive Visual Support of Parameter Selection for Dimensionality Reduction
Stärk, Luka: Semantic Similarity of Concepts for a Human-Centered Idea Recommendation Feature in the Clustering Application Orchard
Moog, Dominik Schlomo: Spam detection in crowdsourced ideation
Bayram, Ömer: Visualization of Linked Data Entities
Tchilibou, Ingrid: A WordNet based backend for the Interactive Concept Validation (ICV)
Abstract
Summarizing and categorizing a large quantity of ideas to generate new and interesting ideas is a promising process, also called idea synthesis. However, the collected ideas are usually very extensive, which takes a lot of time when categorizing them manually. A Software could help analysts to oversee large quantities in order to categorize faster and better synthesize new ideas. This thesis deals with the question on whether WordNet hypernyms are helpful in categorizing a group of ideas. To use WordNet hypernyms it is necessary to first annotate the ideas with the meaning (synset) of each word contained in an idea (so-called Word-Sense-Disambiguation). For this purpose, a WordNet connection for the existing ICV (Interactive Concept Validation) tool was implemented in this thesis. Furthermore, several possibilities of categorization were implemented and tested in an expert interview. The interview showed that hypernyms cannot be considered in terms of the amount of ideas that are grouped as categories. On the other hand, the interview showed that hypernyms can help in giving an orientation on the main context in the ideas. These observations provide a base for the further development and improvement of WordNet-based categorization approaches.