Subjective Knowledge Acquisition and Enrichment Powered By Crowdsourcing
Rui Meng, Hao Xin, Lei Chen, Yangqiu Song

TL;DR
This paper introduces CoSKA, a system leveraging crowdsourcing to acquire and enrich subjective knowledge in knowledge bases, addressing the challenge of limited resources through inference rules and strategic seed selection.
Contribution
It presents a novel framework for subjective knowledge acquisition that combines crowdsourcing with inference rules to efficiently enhance knowledge bases.
Findings
CoSKA effectively enriches subjective knowledge in KBs.
Strategic seed selection improves inference power under resource constraints.
Experimental results validate the system's effectiveness.
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 people's 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…
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Taxonomy
TopicsMobile Crowdsensing and Crowdsourcing · Domain Adaptation and Few-Shot Learning · Expert finding and Q&A systems
