{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/11"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"}],"enrichment":{"capability":"Extracts keyphrases from text documents using part-of-speech patterns and produces document-keyphrase matrices compatible with scikit-learn's vectorizer interface.","skillfed_tags":["nlp-text-processing","keyphrase-extraction","unsupervised-learning"],"use_cases":["Extract grammatically coherent keywords from research papers or documents for indexing and retrieval.","Build document-keyphrase matrices for topic modeling with BERTopic or other unsupervised clustering.","Combine with KeyBERT using PatternRank to rank candidate keyphrases by semantic similarity.","Preprocess multilingual document collections where n-gram ranges fail to capture meaningful phrases.","Replace standard CountVectorizer in NLP pipelines when grammatical accuracy matters more than coverage."],"what_it_does":"KeyphraseVectorizers wraps scikit-learn's CountVectorizer and TfidfVectorizer to extract keyphrases based on part-of-speech patterns rather than fixed n-gram ranges. It uses spaCy to tag words grammatically, then filters them by regex patterns (e.g., adjectives followed by nouns) to identify semantically meaningful phrases. The result is a document-keyphrase matrix where rows are documents and columns are unique keyphrases, with cell values representing keyphrase frequency or TF-IDF scores.\n\nThe package is designed for unsupervised keyphrase extraction across multiple languages and integrates with the PatternRank algorithm and KeyBERT for enhanced keyword discovery. It depends on numpy, spacy, scikit-learn, scipy, nltk, and related libraries. The codebase originated from research on the PatternRank paper and has remained stable but dormant since mid-2024.","worth_installing":"Yes, if you need POS-pattern-based keyphrase extraction and accept dormant maintenance. The package is stable, has no known vulnerabilities, and integrates cleanly with scikit-learn and spaCy. Install friction is low. However, do not expect active development or rapid bug fixes; treat it as a research tool rather than a production library with ongoing support."},"id":"keyphrase-vectorizers","links":{"html":"https://skillfed.io/packages/keyphrase-vectorizers","md":"https://skillfed.io/packages/keyphrase-vectorizers.md","pypi":"https://pypi.org/project/keyphrase-vectorizers/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-05-02","license_spdx":null,"license_treatment":"permissive","name":"keyphrase-vectorizers","python_support":"supports_current","summary":"Set of vectorizers that extract keyphrases with part-of-speech patterns from a collection of text documents and convert them into a document-keyphrase matrix."},"popularity":{"monthly_downloads":87242,"position":13808,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.13"}