Ryuichiro Higashinaka

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Ryuichiro Higashinaka is an author.


Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Creating an extended named entity dictionary from wikipedia Dictionary
Extended named entity
24th International Conference on Computational Linguistics - Proceedings of COLING 2012: Technical Papers English 2012 Automatic methods to create entity dictionaries or gazetteers have used only a small number of entity types (18 at maximum), which could pose a limitation for fine-grained information extraction. This paper aims to create a dictionary of 200 extended named entity (ENE) types. Using Wikipedia as a basic resource, we classify Wikipedia titles into ENE types to create an ENE dictionary. In our method, we derive a large number of features for Wikipedia titles and train a multiclass classifier by supervised learning. We devise an extensive list of features for the accurate classification into the ENE types, such as those related to the surface string of a title, the content of the article, and the meta data provided with Wikipedia. By experiments, we successfully show that it is possible to classify Wikipedia titles into ENE types with 79.63% accuracy. We applied our classifier to all Wikipedia titles and, by discarding low-confidence classification results, created an ENE dictionary of over one million entities covering 182 ENE types with an estimated accuracy of 89.48%. This is the first large scale ENE dictionary. 0 0
"Who is this" quiz dialogue system and users' evaluation Interactive systems
User interfaces
2008 IEEE Workshop on Spoken Language Technology, SLT 2008 - Proceedings English 2008 In order to design a dialogue system that users enjoy and want to be near for a long time, it is important to know the effect of the system's action on users. This paper describes "Who is this" quiz dialogue system and its users' evaluation. Its quiz-style information presentation has been found effective for educational tasks. In our ongoing effort to make it closer to a conversational partner, we implemented the system as a stuffed-toy (or CG equivalent). Quizzes are automatically generated from Wikipedia articles, rather than from hand-crafted sets of biographical facts. Network mining is utilized to prepare adaptive system responses. Experiments showed the effectiveness of person network and the relationship of user attribute and interest level. 0 0
Learning to Rank Definitions to Generate Quizzes for Interactive Information Presentation English 2007 0 0