Demo Data from EDBT 2026 / reviewers in the wild / expert
Shouichi Futamura
dblp:84/2263
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1986
—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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 75% Data models and query languages · 25% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › document processing
document compression |
0.0 | 1 | 1986 | Efficient Storage and Retrieval of Very Large Document Databases · ICDE 1986 |
Data models and query languages › NoSQL database
document store |
0.0 | 1 | 1986 | Efficient Storage and Retrieval of Very Large Document Databases · ICDE 1986 |
Information retrieval
indexing |
0.0 | 1 | 1986 | Efficient Storage and Retrieval of Very Large Document Databases · ICDE 1986 |
Information retrieval › indexing
inverted file |
0.0 | 1 | 1986 | Efficient Storage and Retrieval of Very Large Document Databases · ICDE 1986 |
Methods — techniques the papers use, named apart from their topics
statistical word occurrence analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1986 | Efficient Storage and Retrieval of Very Large Document DatabasesabstractThe authors have developed an information retrieval system named AIR (Augmented Information Retrieval system), which might be one of the most efficient systems for very large document databases. AIR can store the document data compactly and retrieve them quickly. The techniques bringing AIR to the high efficiency, the data compression, the quick keyword index, and the automatic keyword selection, are discussed. These techniques, which are based on the statistical properties of word occurrence, are fairly simple, so that the information retrieval systems employing them can be implemented with ease. The data compression technique reduces English text by a factor of 4. The quick keyword index decreases the average number of disk accesses to retrieve a keyword to about 0.3. The automatic keyword selection technique roughly halves both the number of different keywords and the size of the inverted file with only 2% loss of retrieval power. Fumihiro Matsuo, Shouichi Futamura, Takeshi Shinohara |
ICDE | 2 |