Publications by Thành Tâm Nguyên

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Our modern society is struggling with an unprecedented amount of online misinformation, which does harm to democracy, economics, and cybersecurity. Journalism and politics have been impacted by misinformation on a global scale, with weakened public trust i ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...

Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...

What-if analysis is a data-intensive exploration to inspect how changes in a set of input parameters of a model influence some outcomes. It is motivated by a user trying to understand the sensitivity of a model to a certain parameter in order to reach a se ...

The Web became the central medium for valuable sources of information fusion applications. However, such user-generated resources are often plagued by inaccuracies and misinformation as a result of the inherent openness and uncertainty of the Web. While fi ...

Wildfires are getting more severe and destructive. Due to their fast-spreading nature, wildfires are often detected when already beyond control and consequently cause billion-scale effects in a very short time. Governments are looking for remote sensing me ...

Conceptual models such as database schemas, ontologies or process models have been established as a means for effective engineering of information systems. Yet, for complex systems, conceptual models are created by a variety of stakeholders, which calls fo ...

Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...

Schema matching is the process of establishing correspondences between the attributes of database schemas for data integration purposes. Although several automatic schema matching tools have been developed, their results are often incomplete or erroneous. ...

As the number of scientific papers getting published is likely to soar, most of modern paper management systems (e.g. ScienceWise, Mendeley, CiteULike) support tag-based retrieval. In that, each paper is associated with a set of \emph{tags}, allowing user ...

The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, howev ...

The amount of information available on the Web has been growing dramatically, raising the importance of techniques for searching the Web. Recently, Web Tables emerged as a model, which enables users to search for information in a structured way. However, e ...

Network embedding automatically learns to encode a graph into multi-dimensional vectors. The embedded representation appears to outperform hand-crafted features in many downstream machine learning tasks. There are a plethora of network embedding approaches ...

Crowdsourcing has been widely established as a means to enable human computation at large-scale, in particular for tasks that require manual labelling of large sets of data items. Answers obtained from heterogeneous crowd workers are aggregated to obtain a ...

Graph neural networks take node features and graph structure as input to build representations for nodes and graphs. While there are a lot of focus on GNN models, understanding the impact of node features and graph structure to GNN performance has received ...

As the volumes of AI problems involving human knowledge are likely to soar, crowdsourcing has become essential in a wide range of world-wide-web applications. One of the biggest challenges of crowdsourcing is aggregating the answers collected from crowd wo ...

The open nature of the Web enables users to produce and propagate any content without authentication, which has been exploited to spread thousands of unverified claims via millions of online documents. Maintenance of credible knowledge bases thus has to re ...

Social platforms became a major source of rumours. While rumours can have severe real-world implications, their detection is notoriously hard: Content on social platforms is short and lacks semantics; it spreads quickly through a dynamically evolving netwo ...

Thành Tâm Nguyên

Chat with Graph Search

Debunking Misinformation on the Web: Detection, Validation, and Visualisation

Validating functional redundancy with mixed generative adversarial networks

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration

Maximal fusion of facts on the web with credibility guarantee

Remote Sensing meets Deep Learning: Exploiting Spatio-Temporal-Spectral Satellite Images for Early Wildfire Detection

Reconciling Matching Networks of Conceptual Models

Efficient User Guidance for Validating Participatory Sensing Data

Reconciling Schema Matching Networks Through Crowdsourcing

Tag-based Paper Retrieval: Minimizing User Effort with Diversity Awareness

User Guidance for Efficient Fact Checking

User Guidance for Efficient Fact Checking

Result Selection and Summarization for Web Table Search

A comparison of network embedding approaches

Computing Crowd Consensus with Partial Agreement (Extended Abstract)

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

BATC - A Benchmark for Aggregation Techniques in Crowdsourcing

FactCatch: Incremental Pay-as-You-Go Fact Checking with Minimal User Effort

From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms