Demo Data from VLDB 2026 / reviewers in the wild / expert
Jiyu Komiya
dblp:205/2529
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1
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 |
Knowledge representation and reasoning · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Query processing and optimization · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge acquisition › knowledge extraction
declarative information extraction |
0.3 | 1 | 2018 | Koko: A System for Scalable Semantic Querying of Text · Proc. VLDB Endow. 2018 |
Methods — techniques the papers use, named apart from their topics
surface syntax conditions · 0.7dependency parse tree · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Koko: A System for Scalable Semantic Querying of TextabstractK oko is a declarative information extraction system that incorporates advances in natural language processing techniques in its extraction language. K oko 's extraction language supports simultaneous specification of conditions over the surface syntax and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions. Furthermore, the K oko extraction language allows for aggregating evidence from an input document and supports conditions that are tolerant of linguistic variation of expressing concepts. In this demo, we outline the design of K oko , a system for extracting information and understanding the results of the extraction. K oko provides an interactive interface that allows participants to write queries, understand the input and results of the queries. In particular, the user can customize the input text, visualize the input text's dependency parse trees, and understand the correspondences between query components, dependency tree nodes, text tokens, and the computation and associated scores that led to an extraction. Xiaolan Wang 0001, Jiyu Komiya, Yoshihiko Suhara, Aaron Feng, Behzad Golshan, Alon Y. Halevy, Wang Chiew Tan |
Proc. VLDB Endow. | 2 |