Demo Data from EDBT 2026 / reviewers in the wild / expert
Anna R. Kimaro
dblp:410/8488
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0003-1197-7530ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021
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 |
Knowledge graphs · 61% Information retrieval · 39% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge graphs
domain-specific knowledge graph |
0.9 | 1 | 2025 | Towards Enhanced Agricultural Information Access in Kiswahili: Integrating Knowledge Graphs and Retrieval-Augmented Generation · SIGIR 2025 |
Knowledge graphs
knowledge graph retrieval |
0.9 | 1 | 2025 | Towards Enhanced Agricultural Information Access in Kiswahili: Integrating Knowledge Graphs and Retrieval-Augmented Generation · SIGIR 2025 |
Information retrieval
retrieval-augmented generation |
0.9 | 1 | 2025 | Towards Enhanced Agricultural Information Access in Kiswahili: Integrating Knowledge Graphs and Retrieval-Augmented Generation · SIGIR 2025 |
Information retrieval › cross-language information retrieval
low-resource language retrieval |
0.3 | 1 | 2025 | Towards Enhanced Agricultural Information Access in Kiswahili: Integrating Knowledge Graphs and Retrieval-Augmented Generation · SIGIR 2025 |
Methods — techniques the papers use, named apart from their topics
retrieval-augmented generation · 0.9knowledge graph · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Towards Enhanced Agricultural Information Access in Kiswahili: Integrating Knowledge Graphs and Retrieval-Augmented GenerationabstractAccess to and consumption of agricultural research findings remains a challenge for Kiswahili-speaking farmers and extension officers in Tanzania due to the predominance of English in agriculture scholarly publications.To address this challenge, the Mkulima repository, a digital collection of over 600 Swahili agricultural publications, was developed at the Sokoine University of Agriculture to provide agricultural knowledge in Kiswahili.However, its current structure limits effective retrieval and accessibility, given the type of its intended audience, smallholder farmers.This work-in-progress aims to improve access to agricultural knowledge in Kiswahili through a hybrid model that integrates a domain-specific Knowledge Graph (KG) with Retrieval-Augmented Generation (RAG), an approach that combines traditional retrieval with generative language models for producing informed answers.The project's findings aim to contribute to AI-driven retrieval systems for low-resource languages, with results targeted for submission as a paper to SIGIR 2026. Joseph P. Telemala, Neema Nicodemus Lyimo, Anna R. Kimaro, Camilius A. Sanga |
SIGIR | 3 |