Google Research Blog
The latest news from Research at Google
OpenHTMM Released
Sunday, September 23, 2007
Posted by Ashok C. Popat, Research Scientist
Statistical methods of text analysis have become increasingly sophisticated over the years. A good example is automated topic analysis using latent models, two variants of which are
Probabilistic latent semantic analysis
and
Latent Dirichlet Allocation
.
Earlier this year,
Amit Gruber
, a Ph.D. student at the Hebrew University of Jerusalem, presented a technique for analyzing the topical content of text at the
Eleventh International Conference on Artificial Intelligence and Statistics
in Puerto Rico.
Gruber's approach, dubbed
Hidden Topic Markov Models (HTMM)
, was developed in collaboration with
Michal Rosen-Zvi
and
Yair Weiss
. It differs notably from others in that, rather than treat each document as a single "bag of words," it imposes a temporal Markov structure on the document. In this way, it is able to account for shifting topics within a document, and in so doing, provides a topic segmentation within the document, and also seems to effectively distinguish among multiple senses that the same word may have in different contexts within the same document.
Amit is currently a doing graduate internship at Google. As part of his project, he has developed a fresh implementation of his method in C++. We are pleased to release it as the
OpenHTMM
package to the research community under the Apache 2 license, in the hopes that it will be of general interest and facilitate further research in this area.
The Sky is Open
Wednesday, September 19, 2007
Posted by Jeremy Brewer
We've gotten an incredible amount of positive feedback about
Sky in Google Earth
, which lets Google Earth users explore the sky above them with hundreds of millions of stars and galaxies taken from astronomy imagery.
From the start though, we have wanted to open the sky up to everyone. As a first step, we've been hard at work developing tools to let astronomers add their own imagery, and we think we've come up with something that does the job nicely. We're pleased to announce the availability of
wcs2kml
, an open source project for importing astronomical imagery into Sky.
Modern telescopes output imagery in the FITS binary format that contains a set of headers known as a World Coordinate System (that's the "wcs" part) specifying the location of the image on the sky. Wcs2kml handles the task of transforming this imagery into the projection system used by Google Earth (the "kml" part) so that it can be viewed directly in Sky. Wcs2kml also includes tools to simplify uploading this data to a web server and sharing it with friends.
We were astounded at the imagery and novel applications people created when we opened the Google Earth API to our users. Now, by opening Sky in Google Earth to the astronomy community, we hope to open a floodgate of new imagery for Sky!
Labels
accessibility
ACL
ACM
Acoustic Modeling
Adaptive Data Analysis
ads
adsense
adwords
Africa
AI
Algorithms
Android
Android Wear
API
App Engine
App Inventor
April Fools
Art
Audio
Augmented Reality
Australia
Automatic Speech Recognition
Awards
Cantonese
Chemistry
China
Chrome
Cloud Computing
Collaboration
Computational Imaging
Computational Photography
Computer Science
Computer Vision
conference
conferences
Conservation
correlate
Course Builder
crowd-sourcing
CVPR
Data Center
Data Discovery
data science
datasets
Deep Learning
DeepDream
DeepMind
distributed systems
Diversity
Earth Engine
economics
Education
Electronic Commerce and Algorithms
electronics
EMEA
EMNLP
Encryption
entities
Entity Salience
Environment
Europe
Exacycle
Expander
Faculty Institute
Faculty Summit
Flu Trends
Fusion Tables
gamification
Gboard
Gmail
Google Accelerated Science
Google Books
Google Brain
Google Cloud Platform
Google Docs
Google Drive
Google Genomics
Google Maps
Google Photos
Google Play Apps
Google Science Fair
Google Sheets
Google Translate
Google Trips
Google Voice Search
Google+
Government
grants
Graph
Graph Mining
Hardware
HCI
Health
High Dynamic Range Imaging
ICLR
ICML
ICSE
Image Annotation
Image Classification
Image Processing
Inbox
India
Information Retrieval
internationalization
Internet of Things
Interspeech
IPython
Journalism
jsm
jsm2011
K-12
KDD
Keyboard Input
Klingon
Korean
Labs
Linear Optimization
localization
Low-Light Photography
Machine Hearing
Machine Intelligence
Machine Learning
Machine Perception
Machine Translation
Magenta
MapReduce
market algorithms
Market Research
Mixed Reality
ML
MOOC
Moore's Law
Multimodal Learning
NAACL
Natural Language Processing
Natural Language Understanding
Network Management
Networks
Neural Networks
Nexus
Ngram
NIPS
NLP
On-device Learning
open source
operating systems
Optical Character Recognition
optimization
osdi
osdi10
patents
Peer Review
ph.d. fellowship
PhD Fellowship
PhotoScan
Physics
PiLab
Pixel
Policy
Professional Development
Proposals
Public Data Explorer
publication
Publications
Quantum AI
Quantum Computing
renewable energy
Research
Research Awards
resource optimization
Robotics
schema.org
Search
search ads
Security and Privacy
Semantic Models
Semi-supervised Learning
SIGCOMM
SIGMOD
Site Reliability Engineering
Social Networks
Software
Speech
Speech Recognition
statistics
Structured Data
Style Transfer
Supervised Learning
Systems
TensorBoard
TensorFlow
TPU
Translate
trends
TTS
TV
UI
University Relations
UNIX
User Experience
video
Video Analysis
Virtual Reality
Vision Research
Visiting Faculty
Visualization
VLDB
Voice Search
Wiki
wikipedia
WWW
YouTube
Archive
2018
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Jul
May
Apr
Mar
Feb
2007
Oct
Sep
Aug
Jul
Jun
Feb
2006
Dec
Nov
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Feed
Google
on
Follow @googleresearch
Give us feedback in our
Product Forums
.