Artificial Intelligence (AI) has recently proved to accelerate research in many diverse domains. Information Search can benefit from developments in AI in many different ways, such as diversifying the way of search by voice and image, enriching the scenarios of search by incorporating cognitive computing functions. Our research aims at supporting users' search under unfamiliar domains and mitigate the gap between users' knowledge domain and search domain by leveraging novel AI techniques, so as to enhance the performance of information search.


Our research is generic and can be applied to many scenarios, such as,
1. Searching for temporal counterpart across different time periods (e.g., Walkman is 1980s' iPod)
2. Searching for spatial counterpart across different geographical spaces (e.g., tofu is the cheese of Asia)
3. Searching for corresponding relationships across domain (e.g., Skytree in Tokyo is similar to Empire State Building in New York)
4. Query-by-region search mode (e.g., pointing out a square in a map and to find the corresponding one in another geographical space)
These applications can be utilized in Q&A system, recommendation system, knowledge base enrichment etc.


氏名 専攻 研究室 役職/学年
Zhang Yating 社会情報学専攻 田中研究室 研究員
Jatowt Adam 社会情報学専攻 田中研究室 特定准教授
田中 克己 社会情報学専攻 田中研究室 教授