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The Faculty of Languages at the University of Applied Sciences Zwickau has a knowledge
base on critical incidents. Critical incidents capture and structure insights from critical situations in international mobility [Fet15]. With the rapid development of data and information, the
research platform CIs to Go has a clear need for a central search infrastructure that will allow
users to find and discover more relevant critical incidenst (or intercultural experinces as named
in the research platform CIs to Go). The data and information about critical incidents are stored
in open-source relational database management system PostgreSQL.
Nowadays it is inconceivable to use traditional RDBMS tools to analyze the data as they
grow very fast. The amount of information has steadily increased for years. Big Data provides
a solution for analyzing large amounts of data. Many search engine providers offer the solution
for analyzing large volumes of data, and companies are looking for open source solutions that
can quickly and reliably search, analyze, and evaluate large volumes of data. Elasticsearch
is a Lucene based search engine. Elasticsearch uses the concept of indexing to speed up the
search. This search engine provides a variety of options for free text queries, fuzzy matching
and indexing data. First, search engines and NLP toolkits are reviewed. This thesis also defines
the functional requirements of these tools. Then, an evaluation is given by indicating the positive
and negative aspects of the tools.
This thesis presents a complete search engine to be deployed on the research platform CIs
to Go as a new visual tool that helps in the process of searching for and finding intercultural
experiences.