Abstract
An agent in pursuit of a task may work with a corpus of documents with linked subjective content descriptions. Faced with a new document, an agent has to decide whether to include that document in its corpus or not. Basing the decision on only words, topics, or entities, has shown to not lead to a balanced performance for varying documents. Therefore, this paper presents an approach for an agent to decide if a new document adds value to its existing corpus by combining texts and content descriptions. Furthermore, an agent can use the approach as a starting point for high quality content descriptions for new documents. A case study shows the effectiveness of our approach given varying types of new documents.
| Original language | English |
|---|---|
| Title of host publication | AI 2019: AI 2019: Advances in Artificial Intelligence |
| Editors | Jixue Liu, James Bailey |
| Number of pages | 12 |
| Volume | 11919 LNAI |
| Publisher | Springer, Cham |
| Publication date | 25.11.2019 |
| Pages | 357-368 |
| ISBN (Print) | 978-3-030-35287-5 |
| ISBN (Electronic) | 978-3-030-35288-2 |
| DOIs | |
| Publication status | Published - 25.11.2019 |
| Event | 32nd Australasian Joint Conference on Artificial Intelligence - Adelaide, Australia Duration: 02.12.2019 → 05.12.2019 Conference number: 234489 |
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
- Research Area: Intelligent Systems
DFG Research Classification Scheme
- 409-06 Information Systems, Process and Knowledge Management
