Data Mining - Concepts and Techniques.

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Social Network Analysis

Emotion and Adaptation

In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and semantic dependency relations An initial investigation is then done using a Naive Bayesian Classifier and some handcrafted rules The results show that the algorithms and proposed approach are effective at determining semantic dependency structure automatically The Naive Bayesian Classifier makes a good baseline algorithm for future research

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A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese.

This paper introduces a method of constructing a semantic dictionary automatically from the keywords and classify relations of the web encyclopedia Chinese WikiPedia. Semantic units, which are affixes (core/modifier) shared between many phrased-keywords, are selected using statistic method and string affix matching, also with other units to explain the semantic meanings. Then the result are used to mark the semantic explanations for most WikiPedia keywords by analyzing surface text or upper classes. The feature form ' structure or advantages comparing to other semantic resource are also concerned.

A Method of Semantic Dictionary Construction from On-line Encyclopedia Classifications

This paper proposes a query expansion method for cooking question answering system based on pragmatic analysis. In our approach, the results of question analysis is used. The original queries are generated by means of the question subject, then the query terms are expanded based on pragmatic function. When submitting the expended queries to Google search engine to retrieve related passages, we get an overall improvement of 36.2% on the mean average precision.

Pragmatic analysis based query expansion for Chinese cuisine QA service system

With the increasing popularity of Twitter in recent years, many people are using Twitter to communicate on a daily basis. Recent research suggests that a large part of the texts posted by Twitter users contain various emotions, which can further be used for the Web marketing and information recommendation systems. However, because the language usage habits differ among Twitter users, the research of emotion analysis on Twitter texts has been considered to be a difficult problem. In addition, the number of Twitter texts is so large that it is impossible to analyze all of them. In this paper we propose to create a high-quality Japanese Tweet Emotion corpus by using active learning and employ a Transformers language model to improve the emotion analysis. Experiment results suggest that a fine-tuned Transformer language model tuns better than the previous model in both Twitter emotion analysis and Twitter emotion corpus creation.

Fuji Ren

Papers

A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese.

A Method of Semantic Dictionary Construction from On-line Encyclopedia Classifications

Pragmatic analysis based query expansion for Chinese cuisine QA service system

Improvement of Japanese Text Emotion Analysis by Active Learning Using Transformers Language Model

A Boltzmann Machine with Non-rejective Move