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In the big data era, the relationship between entities becomes more complex. Therefore, graph (or network) data attracts increasing research attention for carrying complex relational information. For a myriad of graph mining/learning tasks, graph neural ...

Instead of mining coherent topics from a given text corpus in a completely unsupervised manner, seed-guided topic discovery methods leverage user-provided seed words to extract distinctive and coherent topics so that the mined topics can better cater to ...

Target-oriented opinion summarization is to profile a target by extracting user opinions from multiple related documents. Instead of simply mining opinion ratings on a target (e.g., a restaurant) or on multiple aspects (e.g., food, service) of a target, ...

Despite substantial interest in applications of neural networks to information retrieval, neural ranking models have mostly been applied to conventional ad-hoc retrieval tasks over web pages and newswire articles. This article proposes a concept-enhanced ...

Temporal Graph Neural Networks are gaining popularity in modeling interactions on dynamic graphs. Among them, Temporal Graph Attention Networks (TGAT) have gained adoption in predictive tasks, such as link prediction, in a range of application domains. ...

This article proposes a novel extension of the Simplex architecture with model switching and model learning to achieve safe velocity regulation of self-driving vehicles in dynamic and unforeseen environments. To guarantee the reliability of autonomous ...

Mutation faults are the core of mutation testing and have been widely used in many other software testing and debugging tasks. Hence, constructing high-quality mutation faults is critical. There are many traditional mutation techniques that construct ...

Adaptive filtering algorithms are pervasive throughout signal processing and have had a material impact on a wide variety of domains including audio processing, telecommunications, biomedical sensing, astrophysics and cosmology, seismology, and many more. ...

Federated learning (FL) is a machine learning paradigm that enables a cluster of decentralized edge devices to collaboratively train a shared machine learning model without exposing users' raw data. However, the intensive model training computation is ...

With the rapid development of text mining, many studies observe that text generally contains a variety of implicit information, and it is important to develop techniques for extracting such information. Named Entity Recognition (NER), the first step of ...

Phones, the segmental units in the International Phonetic Alphabet (IPA), include isolated consonants or vowels; tones, the suprasegemental units, represent pitch and voice quality movements that may span many phones. The timings of tones and phones are ...

Serverless Function-as-a-Service (FaaS) is an emerging cloud computing paradigm that frees application developers from infrastructure management tasks such as resource provisioning and scaling. To reduce the tail latency of functions and improve ...

Text correction on mobile devices usually requires precise and repetitive manual control. In this paper, we present EyeSayCorrect, an eye gaze and voice based hands-free text correction method for mobile devices. To correct text with EyeSayCorrect, the ...

Co-evolving sequences are ubiquitous in a variety of applications, where different sequences are often inherently inter-connected with each other. We refer to such sequences, together with their inherent connections modeled as a structured network, as ...

The proliferation of social media has promoted the spread of misinformation that raises many concerns in our society. This paper focuses on a critical problem of explainable COVID-19 misinformation detection that aims to accurately identify and explain ...

Currently, the most dominant neural code generation modelsare often equipped with a tree-structured LSTM decoder, which outputs a sequence of actions to construct an Abstract Syntax Tree (AST) via pre-order traversal. However, such a decoder has two ...

We present an approach to learn contracts for object-oriented programs where guarantees of correctness of the contracts are made with respect to a test generator. Our contract synthesis approach is based on a novel notion of tight contracts and an ...

Delivering high resolution content is a challenge in the film and games industries due to the cost of photorealistic ray-traced rendering. Image upscaling techniques are commonly used to obtain a high resolution result from a low resolution render. ...

This article uses a machine learning algorithm to demonstrate a proof-of-concept case for moderating and managing online comments as a form of content moderation, which is an emerging area of interest for technical and professional communication (TPC) ...

While scientific collaboration is critical for a scholar, some collaborators can be more significant than others, e.g., lifetime collaborators. It has been shown that lifetime collaborators are more influential on a scholar’s academic performance. However,...