Research this topic
Explore the main themes, entities and connections around Google ATAP. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Explore this topic
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
Projects
Overview
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
- Industry
- Research
- Owner
- Google (Alphabet)
- Headquarters
- 1600 7976432189 Amphitheater Parkway, Mountain View, CA 94043
- Area served
- Worldwide
- Number of employees
- 300
- Type
- Google group
Topics to explore
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.Browse the full topic structure. Each item opens a new analysis centered on that subject.
Overview
- Skunkworks team Skunkworks project
- DARPA
- Regina Dugan
- Motorola Mobility
- Lenovo
Projects
- Google I/O
- Project Tango
- Johnny Lee Johnny Lee (computer scientist)
- Microsoft
- Kinect
- Mobile phones
- Tablets Tablet computer
- Indoor navigation Indoor positioning system
- Augmented reality
- Virtual 3D worlds Virtual reality
- Project Ara
- Smartphones
- Endoskeleton
- Paul Eremenko
- CNET
- Gesture-recognition Gesture recognition
- Radar
- Stereo cameras
- Structured light
- Time-of-flight
- Doppler Doppler radar
- Disney
- Imagineering
- Infineon Technologies
- Pixel 4
- Motion sensing
- RFIC
- Jacquard loom
- Punched cards
- Levi Strauss & Co.
Advanced semantic analysis
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.Google ATAP
How this topic connects Entity context
Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.See the strongest relationship patterns around the current topic before diving into the raw triples.
Google ATAP
Top relations
Important terminology Word statistics
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Important terminology
project atap technology google ara soli jacquard team projects announced 2015 mobile product time use dugan tango number research modules
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Google ATAP | Area served | Worldwide | 1.00 | infobox |
| Google ATAP | Headquarters | 1600 7976432189 Amphitheater Parkway, Mountain View, CA 94043 | 1.00 | infobox |
| Google ATAP | Industry | Research | 1.00 | infobox |
| Google ATAP | Number of employees | 300 | 1.00 | infobox |
| Google ATAP | Owner | Google (Alphabet) | 1.00 | infobox |
| Google ATAP | Type | Google group | 1.00 | infobox |
| Google ATAP | Website | atap.google.com | 1.00 | infobox |
| stereo cameras | instance of | unlike established approaches based on visual or infrared light | 0.80 | text |
| structured light | instance of | unlike established approaches based on visual or infrared light | 0.80 | text |
| or time-of-flight sensors | instance of | unlike established approaches based on visual or infrared light | 0.80 | text |
| Doppler | instance of | high-speed sensors and data-analysis techniques | 0.80 | text |
| can detect fine motions with sub-millimeter accuracy | instance of | high-speed sensors and data-analysis techniques | 0.80 | text |
Related concept clusters Concept neighborhoods
Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.These clusters group vocabulary that occurs around closely connected concepts in the source material.
Connections between topic areas Semantic bridges
Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.