Semi-Automatic Construction of a Domain Ontology for Wind Energy Using Wikipedia Articles

Domain ontologies are important information sources for knowledge-based systems. Yet, building domain ontologies from scratch is known to be a very labor-intensive process. In this study, we present our semi-automatic approach to building an ontology for the domain of wind energy which is an important type of renewable energy with a growing share in electricity generation all over the world. Related Wikipedia articles are first processed in an automated manner to determine the basic concepts of the domain together with their properties and next the concepts, properties, and relationships are organized to arrive at the ultimate ontology. We also provide pointers to other engineering ontologies which could be utilized together with the proposed wind energy ontology in addition to its prospective application areas. The current study is significant as, to the best of our knowledge, it proposes the first considerably wide-coverage ontology for the wind energy domain and the ontology is built through a semi-automatic process which makes use of the related Web resources, thereby reducing the overall cost of the ontology building process

Experiments to Improve Named Entity Recognition on Turkish Tweets

Social media texts are significant information sources for several application areas including trend analysis, event monitoring, and opinion mining. Unfortunately, existing solutions for tasks such as named entity recognition that perform well on formal texts usually perform poorly when applied to social media texts. In this paper, we report on experiments that have the purpose of improving named entity recognition on Turkish tweets, using two different annotated data sets. In these experiments, starting with a baseline named entity recognition system, we adapt its recognition rules and resources to better fit Twitter language by relaxing its capitalization constraint and by diacritics-based expansion of its lexical resources, and we employ a simplistic normalization scheme on tweets to observe the effects of these on the overall named entity recognition performance on Turkish tweets. The evaluation results of the system with these different settings are provided with discussions of these results.Comment: appears in Proceedings of the EACL Workshop on Language Analysis for Social Media, 201

Customer Satisfaction in Participation Banks: A Research in Kastamonu

Interest income is considered as forbidden in Islam. Therefore, in Turkey, conservatives generally don’t prefer general banking and by this way funds can’t be used in economic system. So saving deficit can’t be solved in country and saving of people depreciates against inflation. Participation banks which work according to Islamic rules are set up to bring these funds to economy. Participation banking operates in more than 60 countries today and conservatives generally prefer to work with because they are working to principles of profit instead of interest. To attract and persuade more people, at first participation banks should satisfy their customers. In our study we aim to measure customer satisfaction in participation banks in Kastamonu and to reveal the differences between demographic groups. To this aim we conducted a questionnaire to customers of participation banks in Kastamonu