Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

GloVe, which stands for Global Vectors for Word Representation, is an unsupervised learning method introduced by the Stanford NLP Group aimed at creating vector representations for words. By examining the global co-occurrence statistics of words in a specific corpus, it generates word embeddings that form vector spaces where geometric relationships indicate semantic similarities and distinctions between words. One of GloVe's key strengths lies in its capability to identify linear substructures in the word vector space, allowing for vector arithmetic that effectively communicates relationships. The training process utilizes the non-zero entries of a global word-word co-occurrence matrix, which tracks the frequency with which pairs of words are found together in a given text. This technique makes effective use of statistical data by concentrating on significant co-occurrences, ultimately resulting in rich and meaningful word representations. Additionally, pre-trained word vectors can be accessed for a range of corpora, such as the 2014 edition of Wikipedia, enhancing the model's utility and applicability across different contexts. This adaptability makes GloVe a valuable tool for various natural language processing tasks.

Description

Restless Bandit compiles and analyzes tens of millions of resumes and job postings each year to create its statistical Talent Rediscovery models, providing a valuable resource for exploring labor market dynamics. The dataset predominantly includes information from white-collar occupations, with this specific analysis utilizing 19,258,407 individual resumes. To categorize these resumes into industry classifications, the Restless Bandit data science team employed a vector space model to compare companies based on the resumes submitted. By scrutinizing millions of these documents, patterns begin to emerge indicating which companies tend to recruit similar talent. For instance, Eli Lilly frequently hires candidates from a cluster of firms including Merck and Novartis. Companies that exhibit a strong similarity in their hiring patterns are subsequently organized into specific industry segments. While ample data has been collected to assess diversity levels for each Global 2000 company, this report will concentrate solely on industry segments to ensure the confidentiality of corporate information. Additionally, this focused approach allows for a more comprehensive understanding of industry-wide trends without compromising individual company identities.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Greenhouse
Jit

Integrations

Greenhouse
Jit

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Stanford NLP

Country

United States

Website

nlp.stanford.edu/projects/glove/

Vendor Details

Company Name

Restless Bandit

Founded

2014

Country

United States

Website

www.restlessbandit.com

Product Features

Product Features

Recruiting

Assessments
Background Screening
CRM
Interaction Tracking
Internal HR
Interview Management
Job Board Posting
Job Requisition
Onboarding
Recruiting Firms
Reference Checking
Resume Parsing
Self Service Portal

Alternatives

Gensim Reviews

Gensim

Radim Řehůřek

Alternatives

Skima Reviews

Skima

Skima AI
word2vec Reviews

word2vec

Google
LexVec Reviews

LexVec

Alexandre Salle