Keyword Extraction
25 papers with code • 3 benchmarks • 5 datasets
Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document (Source: Wikipedia).
Benchmarks
These leaderboards are used to track progress in Keyword Extraction
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Datasets
MPQA Opinion Corpus
SemEval-2017 Task-10
Latest papers with no code
PerkwE_COQA: Enhanced Persian Conversational Question Answering by combining contextual keyword extraction with Large Language Models
Conversational query-answering is an emerging approach for user engagement.
Comparative Study of Domain Driven Terms Extraction Using Large Language Models
Keywords play a crucial role in bridging the gap between human understanding and machine processing of textual data.
Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach
To the author's knowledge, this method has not been employed in the Persian language before on Instagram social network.
Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactions
To evaluate our work, we asked 12 volunteers to answer a two-part form in which we first assessed the quality of the taxonomies created and then the tags assigned to merchants based on that taxonomy.
LLM-TAKE: Theme Aware Keyword Extraction Using Large Language Models
We call our LLM-based framework Theme-Aware Keyword Extraction (LLM TAKE).
Automated Annotation of Scientific Texts for ML-based Keyphrase Extraction and Validation
In this paper, we present two novel automated text labeling approaches for the validation of ML-generated metadata for unlabeled texts, with specific applications in environmental genomics.
A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews
The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions.
"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioning
We exploit context by pretraining our model with datasets of three tasks: news image captioning where the news article is the context, contextual visual entailment, and keyword extraction from the context.
Ranking the locations and predicting future crime occurrence by retrieving news from different Bangla online newspapers
There have thousands of crimes are happening daily all around.
Natural language processing on customer note data
Automatic analysis of customer data for businesses is an area that is of interest to companies.
