Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Zhipeng Xue 0003

dblp:188/5957-3 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2021
0009-0005-9086-4041ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Knowledge representation and reasoning · 100%
Databases, data mining, and information retrieval
1 paper
Knowledge graphs · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › commonsense reasoning
commonsense knowledge base
0.512021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021
Knowledge, reasoning and agents › Knowledge representation and reasoning
commonsense reasoning
0.512021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021
Knowledge graphs
knowledge base integration
0.512021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021
Knowledge graphs
knowledge graph construction
0.512021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021
Knowledge, reasoning and agents › Knowledge representation and reasoning › semantic representation
frame-based representation
0.112021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology
0.112021
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge · AAAI 2021

Methods — techniques the papers use, named apart from their topics

crowdsourced annotation · 1.0automated labeling · 1.0
YearPublicationVenuePosition
2021 CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge
abstract
In this paper, we present CogNet, a knowledge base (KB) dedicated to integrating three types of knowledge: (1) linguistic knowledge from FrameNet, which schematically describes situations, objects and events. (2) world knowledge from YAGO, Freebase, DBpedia and Wikidata, which provides explicit knowledge about specific instances. (3) commonsense knowledge from ConceptNet, which describes implicit general facts. To model these different types of knowledge consistently, we introduce a three-level unified frame-styled representation architecture. To integrate free-form commonsense knowledge with other structured knowledge, we propose a strategy that combines automated labeling and crowdsourced annotation. At present, CogNet integrates 1,000+ semantic frames from linguistic KBs, 20,000,000+ frame instances from world KBs, as well as 90,000+ commonsense assertions from commonsense KBs. All these data can be easily queried and explored on our online platform, and free to download in RDF format for utilization under a CC-BY-SA 4.0 license. The demo and data are available at http://cognet.top/.
Chenhao Wang 0004, Yubo Chen 0001, Zhipeng Xue 0003, Jun Zhao 0001
AAAI3