EDBT 2026 Demo / reviewers in the wild / expert
Ramiya Venkatachalam
dblp:159/4594
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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.
| Human-computer interaction and pervasive computing
1 paper |
User interface design and tools · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
User interface design and tools › visual programming
visual programming environment |
0.2 | 1 | 2015 | VINERy: A Visual IDE for Information Extraction · Proc. VLDB Endow. 2015 |
Methods — techniques the papers use, named apart from their topics
declarative language translation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | VINERy: A Visual IDE for Information ExtractionabstractInformation Extraction (IE) is the key technology enabling analytics over unstructured and semi-structured data. Not surprisingly, it is becoming a critical building block for a wide range of emerging applications. To satisfy the rising demands for information extraction in real-world applications, it is crucial to lower the barrier to entry for IE development and enable users with general computer science background to develop higher quality extractors. In this demonstration 1 , we present VINERy, an intuitive yet expressive visual IDE for information extraction. We show how it supports the full cycle of IE development without requiring a single line of code and enables a wide range of users to develop high quality IE extractors with minimal efforts. The extractors visually built in VINERY are automatically translated into semantically equivalent extractors in a state-of-the-art declarative language for IE. We also demonstrate how the auto-generated extractors can then be imported into a conventional Eclipse-based IDE for further enhancement. The results of our user studies indicate that VINERY is a significant step forward in facilitating extractor development for both expert and novice IE developers. Yunyao Li 0001, Elmer Kim, Marc A. Touchette, Ramiya Venkatachalam |
Proc. VLDB Endow. | 4 |