TASTIER is a joint research project between
Tsinghua University and
UC Irvine. It focuses on efficient
autocompletion, type-ahead search on large data sets of various types,
such as relational data, documents, semi-structured data. "TASTIER" stands for
search techniques in large data sets.
- DBLPSearch: Type-ahead, fuzzy
search on about one
million computer science
- DBLP author search:
Type-ahead, fuzzy search on DBLP authors.
- Haiti Project: Type-ahead,
fuzzy search on missing people in Haiti Earthquake.
- iPubmed: Type-ahead, fuzzy
search on about 19
Interactive, fuzzy search for learning.
- PSearch: Type-ahead, fuzzy
search on the UCI directory.
- UCI-ICS Search: Type-ahead,
fuzzy search on important entries in the School of ICS at UCI. Try the
"Search" box at the top of the school homepage.
- Interactive and fuzzy search: a dynamic way to explore MEDLINE.
Jiannan Wang, Inci Cetindil, Shengyue Ji, Chen Li, Xiaohui Xie, Guoliang Li, Jianhua Feng
- Seaform: Search-As-You-Type in Forms
Hao Wu, Guoliang Li, Chen Li, Lizhu Zhou
VLDB 2010 (Demo).
- Efficient Fuzzy Type-Ahead Search in TASTIER
Guoliang Li, Shengyue Ji, Chen Li, Jiannan Wang, Jianhua Feng
ICDE 2010 (Demo).
- Efficient Type-Ahead Search on Relational Data: a TASTIER
Guoliang Li, Shengyue Ji, Chen Li, and Jianhua Feng
- Automatic URL Completion and Prediction Using Fuzzy
Jiannan Wang, Guoliang Li, Jianhua Feng, Chen Li
SIGIR 2009 (Poster).
- Interactive Search in XML Data
Guoliang Li, Jianhua Feng, Lizhu Zhou
WWW 2009 (Poster).
- Efficient Interactive Fuzzy Keyword Search
Shengyue Ji, Guoliang Li, Chen Li, and Jianhua Feng
This project is partly supported by the National Natural Science Foundation of China under Grant No. 60873065,
the National High Technology Development 863 Program of China under Grant No. 2007AA01Z152, the US NSF
award No. IIS-0742960, and
a Google Research Award.