Name
Abstract | ||
|---|---|---|
ABSTRACTCommonsense knowledge is a foundational cornerstone of artificial intelligence applications. Whereas information extraction and knowledge base construction for instance-oriented assertions, such as Brad Pitt's birth date, or Angelina Jolie's movie awards, has received much attention, commonsense knowledge on general concepts (politicians, bicycles, printers) and activities (eating pizza, fixing printers) has only been tackled recently. In this tutorial we present state-of-the-art methodologies towards the compilation and consolidation of such commonsense knowledge (CSK). We cover text-extraction-based, multi-modal and Transformer-based techniques, with special focus on the issues of web search and ranking, as of relevance to the WSDM community. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3437963.3441664 | WSDM |
DocType | Citations | PageRank |
Conference | 1 | 0.36 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simon Razniewski | 1 | 157 | 27.07 |
| Niket Tandon | 2 | 146 | 17.32 |
| Aparna S. Varde | 3 | 188 | 28.71 |