Sign in to see all reviews and comparisons. It's Free!
By clicking Sign In with social media, you agree to let PAT RESEARCH store, use and/or disclose your social profile and email address in accordance with the PAT RESEARCH
Privacy Policy
and agree to the
Terms of Use.
Pattern is a web mining module for the Python programming language.
Category
Web Scraping Tools
Features
Data mining tools
Natural language processing
Network analysis
Machine learning
License
Proprietary
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
Company
Pattern
PAT Rating™ ( Beta)
Editor Rating
Aggregated User Rating
Ease of use
9.6
—
Features & Functionality
9.4
—
Advanced Features
9.5
—
Integration
9.5
—
Performance
9.4
—
Training
—
Customer Support
9.6
—
Implementation
—
Renew & Recommend
—
Bottom Line
It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and
9.5
Editor Rating
—
Aggregated User Rating
You have rated this
Pattern is a web mining module for the Python programming language. It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and visualization. The pattern.web module is a web toolkit that contains API's (Google, Gmail, Bing, Twitter, Facebook, Wikipedia, Wiktionary, DBPedia, Flickr, ...), a robust HTML DOM parser and a web crawler. The pattern.en module is a natural language processing (NLP) toolkit for English. Because language is ambiguous (e.g., I can ↔ a can) it uses statistical approaches + regular expressions. This means that it is fast, quite accurate and occasionally incorrect. It has a part-of-speech tagger that identifies word types (e.g., noun, verb, adjective), word inflection (conjugation, singularization) and a WordNet API. The pattern.search module contains a search algorithm to retrieve sequences of words (called n-grams) from tagged text. The search pattern NP be RB?+ important than NP means any noun phrase (NP) followed by the verb to be, followed by zero or more adverbs (RB, e.g., much, more), followed by the words important than, followed by any noun phrase. It will also match "The mobile web will be much less important than mobile apps" and other grammatical variations. The pattern.vector module is a toolkit for machine learning, based on a vector space model of bag-of-words documents with weighted features (e.g., tf-idf) and distance metrics (e.g., cosine similarity, infogain). Models can be used for clustering (k-means, hierarchical), classification (Naive Bayes, Perceptron, k-NN, SVM) and latent semantic analysis (LSA).
We are the movers and shakers of B2B Software & Services. We have been copied by many including the you know who?
Why not get it straight and right from the original source. Join over 40,000+ Executives by subscribing to our newsletter... its FREE ! and get fully confidential personalized recommendations for your software and services search
Privacy Policy: We hate SPAM and promise to keep your email address safe.
By clicking Sign In with social media, you agree to let PAT RESEARCH store, use and/or disclose your social profile and email address in accordance with the PAT RESEARCH Privacy Policy and agree to the Terms of Use.