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Found 54 papers, 16 papers with code
Document Set Expansion with Positive-Unlabelled Learning Using Intractable Density Estimation
The Document Set Expansion (DSE) task involves identifying relevant documents from large collections based on a limited set of example documents.
Document Set Expansion with Positive-Unlabeled Learning: A Density Estimation-based Approach
Previous work shows that PU learning is a promising method for this task.
Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review
Technology Assisted Review (TAR) stopping rules aim to reduce the cost of manually assessing documents for relevance by minimising the number of documents that need to be examined to ensure a desired level of recall.
Stopping Methods for Technology Assisted Reviews based on Point Processes
Technology Assisted Review (TAR), which aims to reduce the effort required to screen collections of documents for relevance, is used to develop systematic reviews of medical evidence and identify documents that must be disclosed in response to legal proceedings.
Scalable Label-efficient Footpath Network Generation Using Remote Sensing Data and Self-supervised Learning
The annotation of segmentation tasks, especially labeling remote sensing images with specialized requirements, is very expensive, so we aim to introduce a pipeline requiring less labeled data.
Bio-SIEVE: Exploring Instruction Tuning Large Language Models for Systematic Review Automation
Medical systematic reviews can be very costly and resource intensive.
On the Security Vulnerabilities of Text-to-SQL Models
Although it has been demonstrated that Natural Language Processing (NLP) algorithms are vulnerable to deliberate attacks, the question of whether such weaknesses can lead to software security threats is under-explored.
Urban feature analysis from aerial remote sensing imagery using self-supervised and semi-supervised computer vision
Analysis of overhead imagery using computer vision is a problem that has received considerable attention in academic literature.
Self-Supervision, Remote Sensing and Abstraction: Representation Learning Across 3 Million Locations
However, the performance of such methods on remote sensing imagery domains remains under-explored.
Cross-Lingual Word Embedding Refinement by $\ell_1$ Norm Optimisation
It is therefore recommended that this strategy be adopted as a standard for CLWE methods.
Cross-Lingual Word Embedding Refinement by $\ell_{1}$ Norm Optimisation
It is therefore recommended that this strategy be adopted as a standard for CLWE methods.
Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
Knowledge Graph Embeddings (KGEs) have been intensively explored in recent years due to their promise for a wide range of applications.
UserReg: A Simple but Strong Model for Rating Prediction
We compare the effectiveness of UserReg with three linear CF models that are widely-used as baselines, and with a set of recently proposed complex models that are based on deep learning or graph techniques.
Identifying safe intersection design through unsupervised feature extraction from satellite imagery
The World Health Organization has listed the design of safer intersections as a key intervention to reduce global road trauma.
Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs
It has been shown that word embeddings can exhibit gender bias, and various methods have been proposed to quantify this.
Identifying Automatically Generated Headlines using Transformers
False information spread via the internet and social media influences public opinion and user activity, while generative models enable fake content to be generated faster and more cheaply than had previously been possible.
Automatic Generation of Topic Labels
A topic is usually represented by a list of terms ranked by their probability but, since these can be difficult to interpret, various approaches have been developed to assign descriptive labels to topics.
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts
The Google Patents is one of the main important sources of patents information.
Understanding Linearity of Cross-Lingual Word Embedding Mappings
The technique of Cross-Lingual Word Embedding (CLWE) plays a fundamental role in tackling Natural Language Processing challenges for low-resource languages.
Real-time monitoring of driver drowsiness on mobile platforms using 3D neural networks
Phone applications reduce the need for specialised hardware and hence, enable a cost-effective roll-out of the technology across the driving population.
Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning
To address this problem, we present a new sky pixel detection system demonstrated to produce accurate results using a wide range of outdoor imagery types.
The 'Paris-end' of town? Urban typology through machine learning
A (novel) neural network-based framework is trained with imagery from the largest 1692 cities in the world and the resulting models are used to compare within-city locations from Melbourne and Sydney to determine the closest connections between these areas and their international comparators.
Modelling Stopping Criteria for Search Results using Poisson Processes
Text retrieval systems often return large sets of documents, particularly when applied to large collections.
Streetscape augmentation using generative adversarial networks: insights related to health and wellbeing
Deep learning using neural networks has provided advances in image style transfer, merging the content of one image (e. g., a photo) with the style of another (e. g., a painting).
Re-Ranking Words to Improve Interpretability of Automatically Generated Topics
Making their output interpretable is an important area of research with applications to areas such as the enhancement of exploratory search interfaces and the development of interpretable machine learning models.
HiDE: a Tool for Unrestricted Literature Based Discovery
We introduce HiDE (Hidden Discovery Explorer), an online knowledge browsing tool which allows fast access to hidden knowledge generated from all abstracts in Medline.
Topic or Style? Exploring the Most Useful Features for Authorship Attribution
Approaches to authorship attribution, the task of identifying the author of a document, are based on analysis of individuals{'} writing style and/or preferred topics.
Continuous N-gram Representations for Authorship Attribution
This paper presents work on using continuous representations for authorship attribution.
Improving distant supervision using inference learning
Distant supervision is a widely applied approach to automatic training of relation extraction systems and has the advantage that it can generate large amounts of labelled data with minimal effort.
Matching Cultural Heritage items to Wikipedia
Digitised Cultural Heritage (CH) items usually have short descriptions and lack rich contextual information.
Mapping WordNet synsets to Wikipedia articles
Lexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of language processing tasks.
