Demo Data from VLDB 2026 / reviewers in the wild / expert
Xiaohuo Liu
dblp:68/3179
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Machine translation · 50% Knowledge representation and reasoning · 50% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Machine translation
cross-lingual retrieval |
0.0 | 1 | 1999 | Mixed Language Query Disambiguation · ACL 1999 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology-based query answering
query rewriting |
0.0 | 1 | 1999 | Mixed Language Query Disambiguation · ACL 1999 |
Information retrieval › query understanding
query disambiguation |
0.0 | 1 | 1999 | Mixed Language Query Disambiguation · ACL 1999 |
Information retrieval
query processing |
0.0 | 1 | 1999 | Mixed Language Query Disambiguation · ACL 1999 |
Methods — techniques the papers use, named apart from their topics
nearest neighbor · 0.0contextual word voting · 0.0co-occurrence statistics · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Mixed Language Query DisambiguationabstractWe propose a mixed language query disambiguation approach by using co-occurrence information from monolingual data only. A mixed language query consists of words in a primary language and a secondary language. Our method translates the query into monolingual queries in either language. Two novel features for disambiguation, namely contextual word voting and 1-best contextual word, are introduced and compared to a baseline feature, the nearest neighbor. Average query translation accuracy for the two features are 81.37% and 83.72%, compared to the baseline accuracy of 75.50%. Pascale Fung, Xiaohuo Liu, Chi Shun Cheung |
ACL | 2 |
| 1999 | A monolingual semantic decoder based on word sense disambiguation for mixed language understanding
Xiaohuo Liu, Pascale Fung, Chi Shun Cheung |
EUROSPEECH | 1 |