47 citations · 150 across the 11 of their papers we have counts for
11 papers
TabIQA: Table Questions Answering on Business Document Images
Phuc Nguyen, Nam Tuan Ly, Hideaki Takeda +1
Table answering questions from business documents has many challenges that require understanding tabular structures, cross-document referencing, and additional numeric computations…
Wikidata-lite for Knowledge Extraction and Exploration
Phuc Nguyen, Hideaki Takeda
Wikidata is the largest collaborative general knowledge graph supported by a worldwide community. It includes many helpful topics for knowledge exploration and data science applica…
TabEAno: Table to Knowledge Graph Entity Annotation
Phuc Nguyen, Natthawut Kertkeidkachorn, Ryutaro Ichise +1
In the Open Data era, a large number of table resources have been made available on the Web and data portals. However, it is difficult to directly utilize such data due to the ambi…
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
Ikuya Yamada, Akari Asai, Hiroyuki Shindo +2
Entity representations are useful in natural language tasks involving entities. In this paper, we propose new pretrained contextualized representations of words and entities based…
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
Phuc Nguyen, Natthawut Kertkeidkachorn, Ryutaro Ichise +1
This paper presents the design of our system, namely MTab, for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019). MTab combines the voting algorithm…
Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia
Ikuya Yamada, Akari Asai, Jin Sakuma +4
The embeddings of entities in a large knowledge base (e.g., Wikipedia) are highly beneficial for solving various natural language tasks that involve real world knowledge. In this p…
EmbNum: Semantic labeling for numerical values with deep metric learning
Phuc Nguyen, Khai Nguyen, Ryutaro Ichise +1
Semantic labeling for numerical values is a task of assigning semantic labels to unknown numerical attributes. The semantic labels could be numerical properties in ontologies, inst…
Learning Distributed Representations of Texts and Entities from Knowledge Base
Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda +1
We describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to…
Online learning for Social Spammer Detection on Twitter
Phuc Tri Nguyen, Hideaki Takeda
Social networking services like Twitter have been playing an import role in people's daily life since it supports new ways of communicating effectively and sharing information. The…
Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda +1
Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity mentions in a document to their correct references in a knowledge base (KB) (e.g., Wikipedia…
Using multiple-criteria methods to evaluate community partitions
Remy Cazabet, Rathachai Chawuthai, Hideaki Takeda
Community detection is one of the most studied problems on complex networks. Although hundreds of methods have been proposed so far, there is still no universally accepted formal d…