13 citations · 35 across the 15 of their papers we have counts for
7 papers · 1 filter
Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking
Hang Dong, Jiaoyan Chen, Yuan He +2
Discovering entity mentions that are out of a Knowledge Base (KB) from texts plays a critical role in KB maintenance, but has not yet been fully explored. The current methods are m…
Joint Open Knowledge Base Canonicalization and Linking
Yinan Liu, Wei Shen, Yuanfei Wang +3
Open Information Extraction (OIE) methods extract a large number of OIE triples (noun phrase, relation phrase, noun phrase) from text, which compose large Open Knowledge Bases (OKB…
Personal Attribute Prediction from Conversations
Yinan Liu, Hu Chen, Wei Shen
Personal knowledge bases (PKBs) are critical to many applications, such as Web-based chatbots and personalized recommendation. Conversations containing rich personal knowledge can…
Multi-View Clustering for Open Knowledge Base Canonicalization
Wei Shen, Yang Yang, Yinan Liu
Open information extraction (OIE) methods extract plenty of OIE triples <noun phrase, relation phrase, noun phrase> from unstructured text, which compose large open knowledge bases…
Entity Linking Meets Deep Learning: Techniques and Solutions
Wei Shen, Yuhan Li, Yinan Liu +3
Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base. EL plays an important role in the fields…
Subjective Bias in Abstractive Summarization
Lei Li, Wei Liu, Marina Litvak +4
Due to the subjectivity of the summarization, it is a good practice to have more than one gold summary for each training document. However, many modern large-scale abstractive summ…
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity Search
Adam Hare, Yu Chen, Yinan Liu +2
Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning…