Can network embedding of distributional thesaurus be combined with word vectors for better representation?
Distributed representations of words learned from text have proved to be successful in
various natural language processing tasks in recent times. While some methods represent …
various natural language processing tasks in recent times. While some methods represent …
From vision to content: Construction of domain-specific multi-modal knowledge graph
X Zhang, X Sun, C Xie, B Lun - IEEE Access, 2019 - ieeexplore.ieee.org
Knowledge graphs are usually constructed to describe the various concepts that exist in real
world as well as the relationships between them. There are many knowledge graphs in …
world as well as the relationships between them. There are many knowledge graphs in …
Explainable Graph-Based Search for Lessons-Learned Documents in the Semiconductor Industry
Industrial processes produce a considerable volume of data and thus information. Whether it
is structured sensory data or semi-to unstructured textual data, the knowledge that can be …
is structured sensory data or semi-to unstructured textual data, the knowledge that can be …
A Visually Enhanced Neural Encoder for Synset Induction
G Chen, F Feng, G Zhang, X Li, R Li - Electronics, 2023 - mdpi.com
The synset induction task is to automatically cluster semantically identical instances, which
are often represented by texts and images. Previous works mainly consider textual parts …
are often represented by texts and images. Previous works mainly consider textual parts …
Network embeddings from distributional thesauri for improving static word representations
Word representations obtained from text using the distributional hypothesis have proved to
be useful for various natural language processing tasks. To prepare vector representation …
be useful for various natural language processing tasks. To prepare vector representation …
A text extraction-based smart knowledge graph composition for integrating lessons learned during the microchip design
The production of microchips is a complex and thus well documented process. Therefore,
available textual data about the production can be overwhelming in terms of quantity. This …
available textual data about the production can be overwhelming in terms of quantity. This …
Cross-modal knowledge transfer: Improving the word embedding of apple by looking at oranges
Capturing knowledge via learned latent vector representations of words, images and
knowledge graph (KG) entities has shown state-of-the-art performance in computer vision …
knowledge graph (KG) entities has shown state-of-the-art performance in computer vision …
Domain adaptation of word embeddings through the exploitation of in-domain corpora and knowledge bases
H El Boukkouri - 2021 - theses.hal.science
There are, at the basis of most NLP systems, numerical representations that enable the
machine to process, interact with and—to some extent—understand human language …
machine to process, interact with and—to some extent—understand human language …
Knowledge fusion via joint tensor and matrix factorization
We consider the task of knowledge fusion, an important aspect of cognitive intelligence, with
the goal of combining part-of knowledge drawn from different sources. For this, entities and …
the goal of combining part-of knowledge drawn from different sources. For this, entities and …
Multimodal tag synset induction
M Xu, B Sun, J Jiang, F Feng - 7th International Symposium on …, 2022 - spiedigitallibrary.org
Most previous works in synset induction generally ignore the visual data, which contains
important semantic information. Instead, in this paper, we present an effective multi-modal …
important semantic information. Instead, in this paper, we present an effective multi-modal …