21 citations · 87 across the 21 of their papers we have counts for
22 papers
Question Decomposition Tree for Answering Complex Questions over Knowledge Bases
Xiang Huang, Sitao Cheng, Yiheng Shu +2
Knowledge base question answering (KBQA) has attracted a lot of interest in recent years, especially for complex questions which require multiple facts to answer. Question decompos…
PaTeCon: A Pattern-Based Temporal Constraint Mining Method for Conflict Detection on Knowledge Graphs
Jianhao Chen, Junyang Ren, Wentao Ding +1
Temporal facts, the facts for characterizing events that hold in specific time periods, are attracting rising attention in the knowledge graph (KG) research communities. In terms o…
DyRRen: A Dynamic Retriever-Reranker-Generator Model for Numerical Reasoning over Tabular and Textual Data
Xiao Li, Yin Zhu, Sichen Liu +3
Numerical reasoning over hybrid data containing tables and long texts has recently received research attention from the AI community. To generate an executable reasoning program co…
TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Bases
Yiheng Shu, Zhiwei Yu, Yuhan Li +4
Pre-trained language models (PLMs) have shown their effectiveness in multiple scenarios. However, KBQA remains challenging, especially regarding coverage and generalization setting…
Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs
Wentao Ding, Hao Chen, Huayu Li +1
Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years. In the generation of temporal queries, existing KG…
AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension
Xiao Li, Gong Cheng, Ziheng Chen +2
Recent machine reading comprehension datasets such as ReClor and LogiQA require performing logical reasoning over text. Conventional neural models are insufficient for logical reas…
When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions
Zixian Huang, Ao Wu, Yulin Shen +2
Scenario-based question answering (SQA) requires retrieving and reading paragraphs from a large corpus to answer a question which is contextualized by a long scenario description.…
Automatic Rule Generation for Time Expression Normalization
Wentao Ding, Jianhao Chen, Jinmao Li +1
The understanding of time expressions includes two sub-tasks: recognition and normalization. In recent years, significant progress has been made in the recognition of time expressi…
TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs
Zequn Sun, Jiacheng Huang, Wei Hu +3
Learning knowledge graph (KG) embeddings has received increasing attention in recent years. Most embedding models in literature interpret relations as linear or bilinear mapping fu…
SPARQA: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Bases
Yawei Sun, Lingling Zhang, Gong Cheng +1
Semantic parsing transforms a natural language question into a formal query over a knowledge base. Many existing methods rely on syntactic parsing like dependencies. However, the a…
DeepLENS: Deep Learning for Entity Summarization
Qingxia Liu, Gong Cheng, Yuzhong Qu
Entity summarization has been a prominent task over knowledge graphs. While existing methods are mainly unsupervised, we present DeepLENS, a simple yet effective deep learning mode…
ESBM: An Entity Summarization BenchMark
Qingxia Liu, Gong Cheng, Kalpa Gunaratna +1
Entity summarization is the problem of computing an optimal compact summary for an entity by selecting a size-constrained subset of triples from RDF data. Entity summarization supp…
Crowdsourced Collective Entity Resolution with Relational Match Propagation
Jiacheng Huang, Wei Hu, Zhifeng Bao +1
Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution (ER) aims to identify entities in KBs which refer to the same real-world object. Recent stu…
Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
Zequn Sun, Chengming Wang, Wei Hu +4
Graph neural networks (GNNs) have emerged as a powerful paradigm for embedding-based entity alignment due to their capability of identifying isomorphic subgraphs. However, in real…
Entity Summarization: State of the Art and Future Challenges
Qingxia Liu, Gong Cheng, Kalpa Gunaratna +1
The increasing availability of semantic data has substantially enhanced Web applications. Semantic data such as RDF data is commonly represented as entity-property-value triples. T…
Towards More Usable Dataset Search: From Query Characterization to Snippet Generation
Jinchi Chen, Xiaxia Wang, Gong Cheng +2
Reusing published datasets on the Web is of great interest to researchers and developers. Their data needs may be met by submitting queries to a dataset search engine to retrieve r…
Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering
Jiwei Ding, Wei Hu, Qixin Xu +1
Formal query generation aims to generate correct executable queries for question answering over knowledge bases (KBs), given entity and relation linking results. Current approaches…
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level
Zixian Huang, Yulin Shen, Xiao Li +5
Scenario-based question answering (SQA) has attracted increasing research attention. It typically requires retrieving and integrating knowledge from multiple sources, and applying…
A Framework for Evaluating Snippet Generation for Dataset Search
Xiaxia Wang, Jinchi Chen, Shuxin Li +4
Reusing existing datasets is of considerable significance to researchers and developers. Dataset search engines help a user find relevant datasets for reuse. They can present a sni…
Multi-view Knowledge Graph Embedding for Entity Alignment
Qingheng Zhang, Zequn Sun, Wei Hu +3
We study the problem of embedding-based entity alignment between knowledge graphs (KGs). Previous works mainly focus on the relational structure of entities. Some further incorpora…
DSKG: A Deep Sequential Model for Knowledge Graph Completion
Lingbing Guo, Qingheng Zhang, Weiyi Ge +2
Knowledge graph (KG) completion aims to fill the missing facts in a KG, where a fact is represented as a triple in the form of . Current KG completion…
Graph-based Ontology Summarization: A Survey
Seyedamin Pouriyeh, Mehdi Allahyari, Qingxia Liu +4
Ontologies have been widely used in numerous and varied applications, e.g., to support data modeling, information integration, and knowledge management. With the increasing size of…