Name
Abstract | ||
|---|---|---|
Knowledge bases (KBs) have attracted increasing attention due to its great success in various areas, such as Web and mobile search.Existing KBs are restricted to objective factual knowledge, such as city population or fruit shape, whereas,subjective knowledge, such as big city, which is commonly mentioned in Web and mobile queries, has been neglected. Subjective knowledge differs from objective knowledge in that it has no documented or observed ground truth. Instead, the truth relies on peopleu0027s dominant opinion. Thus, we can use the crowdsourcing technique to get opinion from the crowd. In our work, we propose a system, called crowdsourced subjective knowledge acquisition (CoSKA),for subjective knowledge acquisition powered by crowdsourcing and existing KBs. The acquired knowledge can be used to enrich existing KBs in the subjective dimension which bridges the gap between existing objective knowledge and subjective queries.The main challenge of CoSKA is the conflict between large scale knowledge facts and limited crowdsourcing resource. To address this challenge, in this work, we define knowledge inference rules and then select the seed knowledge judiciously for crowdsourcing to maximize the inference power under the resource constraint. Our experimental results on real knowledge base and crowdsourcing platform verify the effectiveness of CoSKA system. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Databases | Data science,Data mining,Population,Inference,Crowdsourcing,Computer science,Ground truth,Knowledge base,Rule of inference,Knowledge acquisition |
DocType | Volume | Citations |
Journal | abs/1705.05720 | 0 |
PageRank | References | Authors |
0.34 | 20 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Meng | 1 | 48 | 3.35 |
| Hao Xin | 2 | 1 | 0.94 |
| Lei Chen | 3 | 6239 | 395.84 |
| Yangqiu Song | 4 | 2045 | 103.29 |