Search Results for author: Miao Fan

Found 17 papers, 3 papers with code

GEDIT: Geographic-Enhanced and Dependency-Guided Tagging for Joint POI and Accessibility Extraction at Baidu Maps

no code implementations20 Aug 2021 Yibo Sun, Jizhou Huang, Chunyuan Yuan, Miao Fan, Haifeng Wang, Ming Liu, Bing Qin

We approach this task as a sequence tagging problem, where the goal is to produce <POI name, accessibility label> pairs from unstructured text.

Graph Convolutional Network

Quantifying the Economic Impact of COVID-19 in Mainland China Using Human Mobility Data

no code implementations6 May 2020 Jizhou Huang, Haifeng Wang, Haoyi Xiong, Miao Fan, An Zhuo, Ying Li, Dejing Dou

While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992.

Reinforced Product Metadata Selection for Helpfulness Assessment of Customer Reviews

no code implementations IJCNLP 2019 Miao Fan, Chao Feng, Mingming Sun, Ping Li

Given a product, a selector (agent) learns from both the keys in the product metadata and one of its reviews to take an action that selects the correct value, and a successive predictor (network) makes the free-text review attend to this value to obtain better neural representations for helpfulness assessment.

Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

no code implementations29 Apr 2019 Mingming Sun, Xu Li, Xin Wang, Miao Fan, Yue Feng, Ping Li

In this paper, we consider the problem of open information extraction (OIE) for extracting entity and relation level intermediate structures from sentences in open-domain.

Open Information Extraction Relation Extraction

Detecting Table Region in PDF Documents Using Distant Supervision

no code implementations29 Jun 2015 Miao Fan, Doo Soon Kim

Extensive evaluations demonstrate that our paradigm is compatible enough to leverage various features and learning models for open-domain table region detection within PDF files.

Table Detection Table Recognition

Distant Supervision for Entity Linking

no code implementations PACLIC 2015 Miao Fan, Qiang Zhou, Thomas Fang Zheng

In this paper, we propose a new paradigm named distantly supervised entity linking (DSEL), in the sense that the disambiguated entities that belong to a huge knowledge repository (Freebase) are automatically aligned to the corresponding descriptive webpages (Wiki pages).

Entity Linking

Probabilistic Belief Embedding for Knowledge Base Completion

no code implementations10 May 2015 Miao Fan, Qiang Zhou, Andrew Abel, Thomas Fang Zheng, Ralph Grishman

This paper contributes a novel embedding model which measures the probability of each belief $\langle h, r, t, m\rangle$ in a large-scale knowledge repository via simultaneously learning distributed representations for entities ($h$ and $t$), relations ($r$), and the words in relation mentions ($m$).

Knowledge Base Completion

Jointly Embedding Relations and Mentions for Knowledge Population

no code implementations RANLP 2015 Miao Fan, Kai Cao, Yifan He, Ralph Grishman

This paper contributes a joint embedding model for predicting relations between a pair of entities in the scenario of relation inference.

Relation Extraction

Large Margin Nearest Neighbor Embedding for Knowledge Representation

no code implementations7 Apr 2015 Miao Fan, Qiang Zhou, Thomas Fang Zheng, Ralph Grishman

Traditional way of storing facts in triplets ({\it head\_entity, relation, tail\_entity}), abbreviated as ({\it h, r, t}), makes the knowledge intuitively displayed and easily acquired by mankind, but hardly computed or even reasoned by AI machines.

Link Prediction

Learning Embedding Representations for Knowledge Inference on Imperfect and Incomplete Repositories

no code implementations27 Mar 2015 Miao Fan, Qiang Zhou, Thomas Fang Zheng

This paper considers the problem of knowledge inference on large-scale imperfect repositories with incomplete coverage by means of embedding entities and relations at the first attempt.

Link Prediction

Errata: Distant Supervision for Relation Extraction with Matrix Completion

no code implementations17 Nov 2014 Miao Fan, Deli Zhao, Qiang Zhou, Zhiyuan Liu, Thomas Fang Zheng, Edward Y. Chang

The essence of distantly supervised relation extraction is that it is an incomplete multi-label classification problem with sparse and noisy features.

General Classification Low-Rank Matrix Completion +2

Cannot find the paper you are looking for? You can Submit a new open access paper.