Search Results for author:
Found 8 papers, 1 papers with code
Control in Hybrid Chatbots
Customer data typically is held in database systems, which can be seen as rule-based knowledge base, whereas businesses increasingly want to benefit from the capabilities of large, pre-trained language models.
Data-to-Value: An Evaluation-First Methodology for Natural Language Projects
Big data, i. e. collecting, storing and processing of data at scale, has recently been possible due to the arrival of clusters of commodity computers powered by application-level distributed parallel operating systems like HDFS/Hadoop/Spark, and such infrastructures have revolutionized data mining at scale.
Detecting ESG topics using domain-specific language models and data augmentation approaches
Despite recent advances in deep learning-based language modelling, many natural language processing (NLP) tasks in the financial domain remain challenging due to the paucity of appropriately labelled data.
Topic Grouper: An Agglomerative Clustering Approach to Topic Modeling
In this context, the fact that each word belongs to exactly one topic is not a major limitation; in some scenarios this can even be a genuine advantage, e. g.~a related shopping basket analysis may aid in optimizing groupings of articles in sales catalogs.
attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines
Our experimental results on a text classification task demonstrate that using attr2vec to jointly learn embeddings for words and Part-of-Speech (POS) tags improves results compared to learning the embeddings independently.
A Comparison of Two Paraphrase Models for Taxonomy Augmentation
Our results show that paraphrasing is a viable method to enrich a taxonomy with more terms, and that Moses consistently outperforms the sequence-to-sequence neural model.
Say the Right Thing Right: Ethics Issues in Natural Language Generation Systems
We discuss the ethical implications of Natural Language Generation systems.
Ethical by Design: Ethics Best Practices for Natural Language Processing
While a number of previous works exist that discuss ethical issues, in particular around big data and machine learning, to the authors{'} knowledge this is the first account of NLP and ethics from the perspective of a principled process.
