Abstract
Entity extraction is an important task in text mining and
natural language processing. A popular method for entity extraction is by comparing substrings from free text against a dictionary of entities. In this paper, we present several techniques as a post-processing step for improving the effectiveness of the existing entity extraction technique. These techniques utilise models trained with the web-scale corpora which makes our techniques robust and versatile. Experiments show that our techniques bring a notable improvement on efficiency and effectiveness.
natural language processing. A popular method for entity extraction is by comparing substrings from free text against a dictionary of entities. In this paper, we present several techniques as a post-processing step for improving the effectiveness of the existing entity extraction technique. These techniques utilise models trained with the web-scale corpora which makes our techniques robust and versatile. Experiments show that our techniques bring a notable improvement on efficiency and effectiveness.
| Original language | English |
|---|---|
| Title of host publication | The 31st Australasian Database Conference (ADC) |
| Number of pages | 12 |
| Publication status | Published - 2020 |
| Event | 31st Australasian Database Conference - Swinburne University of Technology, Melbourne, Australia Duration: 4 Feb 2020 → 7 Feb 2020 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=92879©ownerid=155630 |
Conference
| Conference | 31st Australasian Database Conference |
|---|---|
| Abbreviated title | ADC 2020 |
| Country/Territory | Australia |
| City | Melbourne |
| Period | 4/02/20 → 7/02/20 |
| Internet address |