Knowledge graphs constantly evolve with new entities emerging, existing definitions being revised, and entity relationships changing. These changes lead to temporal degradation in entity linking models, characterized as a decline in model performance ...

Knowledge acquisition passage retrieval is a task that captures search in a learning or educational setting, where users seek to find key educational information within their field of interest. Traditional relevance assessments used in ad-hoc ...

Low-resource Complex Named Entity Recognition aims to detect entities with the form of any linguistic constituent under scenarios with limited manually annotated data. Existing studies augment the text through the substitution of same type entities or ...

Cross-domain Named Entity Recognition (NER) transfers knowledge learned from a rich-resource source domain to improve the learning in a low-resource target domain. Most existing works are designed based on the sequence labeling framework, defining entity ...

Cross-lingual Named Entity Recognition (NER) aims to address the challenge of data scarcity in low-resource languages by leveraging knowledge from high-resource languages. Most current work relies on general multilingual language models to represent text,...

This work proposes a new technical foundation for demonstrating Probably Approximately Correct (PAC) learning with multiagent epistemic logics, using implicit learning to incorporate observations into the background knowledge. We explore the sample ...

Since the beginning of the century, research on ontology learning has gained popularity. Automatically extracting and structuring knowledge relevant to a domain of interest from unstructured textual data is a major scientific challenge. After ...

Design knowledge is critical to creating ideas in the conceptual design stage of product development for innovation. Fragmentary design data, massive multidisciplinary knowledge call for the development of a novel knowledge acquisition approach for ...

In this study, a multi-dimensional self-regulated learning (MSRL) model is proposed. The model has been applied to a long-term and large-scale promotion program in Taiwan for helping school teachers guide students to be self-regulated learners from the ...

The task of POI attribute acquisition, which aims at completing missing attributes (e.g., POI name, address, status, phone, and open/close time) for a point of interest (POI) or updating existing attribute values of a POI, plays an essential role in ...

Cross-domain Named Entity Recognition (NER) aims to transfer knowledge from the source domain to the target, alleviating expensive labeling costs in the target domain. Most prior studies acquire domain-invariant features under the end-to-end sequence-...

The existence of an anomaly detection method that is optimal for all domains is a myth. Thus, there exists a plethora of anomaly detection methods which increases every year for a wide variety of domains. But a strength can also be a weakness; given this ...

Biometrics is vital to recognise and confirm the identity of human beings by estimating and distinguishing the natural qualities that include iris, retinal, face recognition, fingerprint, palm detection and others. Numerous biometric designs and ...

Knowledge has emerged as a key commodity in smart manufacturing and as a critical resource for innovation and entrepreneurship in Industry 4.0. Innovative firms develop competitive advantages through knowledge exploitation and exploration, whether ...

Crowdsourcing has been a helpful mechanism to leverage human intelligence to acquire useful knowledge. However, when we aggregate the crowd knowledge based on the currently developed voting algorithms, it often results in common knowledge that may ...

This paper presents a technique to assist a reader. We aim to reduce manual efforts of the reader by leveraging the state-of-the-art document summarization techniques and providing summaries about unclear descriptions for each reader. Our system acts as ...

Recent work achieved remarkable results in training neural machine translation (NMT) systems in a fully unsupervised way, with new and dedicated architectures that only rely on monolingual corpora. However, previous work also showed that unsupervised ...

Online discussion forums can be used for reflecting on the overall user experience of a system. If a user forum is well‐structured, it can be a valuable source of requirements‐related information, which can potentially be accommodated in the requirements ...

When performing task in open-ended environment, a robot may not have access to conventional tools required in the task. In such case, an ideal response for the robot would be to find a suitable substitute. In this paper, we present an approach to tool ...