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GloVe: Global Vectors For Word Representation - Stanford University

GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space.

Actived: Thursday Sep 29, 2022

Detail: https://nlp.stanford.edu/projects/glove/

Evaluation of clustering - Stanford University

(53 years ago) where, again, the second equation is based on maximum likelihood estimates of the probabilities. in Equation 184 measures the amount of information by which our knowledge about the classes increases when we are told what the clusters are. The minimum of is 0 if the clustering is random with respect to class membership. In that case, knowing that a document is in a particular …

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Stanford TACRED Homepage

(53 years ago) Introduction. TACRED is a large-scale relation extraction dataset with 106,264 examples built over newswire and web text from the corpus used in the yearly TAC Knowledge Base Population (TAC KBP) challenges.Examples in TACRED cover 41 relation types as used in the TAC KBP challenges (e.g., per:schools_attended and org:members) or are labeled as no_relation if no …

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Software - The Stanford Natural Language Processing Group

(53 years ago) The Stanford NLP Group makes some of our Natural Language Processing software available to everyone! We provide statistical NLP, deep learning NLP, and rule-based NLP tools for major computational linguistics problems, which can be incorporated into applications with human language technology needs.

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Single-Link, Complete-Link & Average-Link Clustering

(53 years ago) There is now an updated and expanded version of this page in form of a book chapter. Single-Link, Complete-Link & Average-Link Clustering. Hierarchical clustering treats each data point as a singleton cluster, and then successively merges clusters until all points have been merged into a single remaining cluster.

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The Stanford Natural Language Processing Group

(53 years ago) The Stanford NLP Group Welcome to the Natural Language Processing Group at Stanford University! We are a passionate, inclusive group of students and faculty, postdocs and research engineers, who work together on algorithms that allow computers to process, generate, and understand human languages.

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Introduction to Information Retrieval - Stanford University

(53 years ago) Introduction to Information Retrieval. This is the companion website for the following book. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.. You can order this book at CUP, at your local bookstore or on the internet.The best search term to use is the ISBN: 0521865719.

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Foundations of Statistical Natural Language Processing

(53 years ago) This is the companion website for the following book. Chris Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing, MIT Press.Cambridge, MA: May 1999. Interested in buying the book? Some more information about …

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An Introduction to Logistic Regression - Stanford University

(53 years ago) An Introduction to Logistic Regression JohnWhitehead Department of Economics East Carolina University Outline Introduction and Description Some Potential Problems and Solutions Writing Up the Results Introduction and Description Why use logistic regression?

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The Stanford Natural Language Processing Group

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