Anchors
| Anchor text | Ref. domains ▾ | Top DR | Ref. pages | Links to target | Dofollow links |
|---|---|---|---|---|---|
| Autostitch | 10 | — | 0 | 12 | 11 91.7% |
| Tamara Munzner | 8 | — | 0 | 8 | 7 87.5% |
| University of British Columbia | 7 | — | 0 | 15 | 15 100% |
| 6 | — | 0 | 25 | 25 100% | |
| UBC | 5 | — | 0 | 5 | 5 100% |
| David Lowe | 5 | — | 0 | 5 | 4 80% |
| Visualization Analysis and Design | 4 | — | 0 | 5 | 5 100% |
| AutoStitch | 4 | — | 0 | 5 | 5 100% |
| http://www.cs.ubc.ca/~mbrown/autostitch/autostitch.html | 4 | — | 0 | 4 | 2 50% |
| Department of Computer Science | 4 | — | 0 | 6 | 4 66.7% |
| here | 4 | — | 0 | 4 | 3 75% |
| Holger Hoos | 3 | — | 0 | 3 | 3 100% |
| UBC Computer Science | 3 | — | 0 | 3 | 3 100% |
| Machine Learning: A Probabilistic Perspective | 3 | — | 0 | 3 | 3 100% |
| Ivan Beschastnikh | 3 | — | 0 | 4 | 4 100% |
| Pre-print | 3 | — | 0 | 10 | 10 100% |
| A Brief Introduction to Graphical Models and Bayesian Networks | 3 | — | 0 | 3 | 2 66.7% |
| Cristina Conati | 3 | — | 0 | 3 | 3 100% |
| Machine Learning: a Probabilistic Perspective | 3 | — | 0 | 5 | 1 20% |
| Michiel van de Panne | 3 | — | 0 | 9 | 9 100% |
| Computer Science | 3 | — | 0 | 5 | 5 100% |
| GPT-1 | 2 | — | 0 | 6 | 1 16.7% |
| Wetzstein, G., Luebke, D., and Heidrich, W., "Optical Image Processing Using Light Modulation Displays", Computer Graphics Forum (Journal), Volume 29, Issue 6, pages 1934-1944, 2010 | 2 | — | 0 | 2 | 2 100% |
| Adam Scibior | 2 | — | 0 | 2 | 2 100% |
| Mark Schmidt | 2 | — | 0 | 2 | 2 100% |
| Wetzstein, G., Ihrke, I., Lanman, D., Heidrich, W. "State of the Art in Computational Plenoptic Imaging", Eurographics (EG) STAR 2011 | 2 | — | 0 | 2 | 2 100% |
| Machine Learning: A Probabilistic Approach | 2 | — | 0 | 5 | 5 100% |
| Jim Little | 2 | — | 0 | 2 | 1 50% |
| Dr. Ivan Beschastnikh | 2 | — | 0 | 2 | 2 100% |
| Mylar | 2 | — | 0 | 2 | 2 100% |
| Wetzstein, G., Ihrke, I., Heidrich, W., "Sensor Saturation in Fourier Multiplexed Imaging", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010 | 2 | — | 0 | 2 | 2 100% |
| cs.ubc.ca | 2 | — | 0 | 2 | 1 50% |
| homepage | 2 | — | 0 | 2 | 2 100% |
| "Computational Plenoptic Imaging", Eurographics 2011 State of the Art Report and Tutorial (Organizer and Co-Instructor) | 2 | — | 0 | 2 | 2 100% |
| Wetzstein, G., Raskar, R., Heidrich, W. "Hand-Held Schlieren Photography with Light Field Probes", IEEE International Conference on Computational Photography (ICCP) 2011, Best Paper Award! | 2 | — | 0 | 2 | 2 100% |
| Vista | 2 | — | 0 | 2 | 1 50% |
| https://cs.ubc.ca/~rtholmes | 2 | — | 0 | 2 | 2 100% |
| CCCG 2009 | 2 | — | 0 | 2 | 2 100% |
| https://www.cs.ubc.ca/~alexsumm/ | 2 | — | 0 | 2 | 2 100% |
| knot theory | 2 | — | 0 | 2 | 2 100% |
| Leonid Sigal | 2 | — | 0 | 2 | 2 100% |
| http://www.cs.ubc.ca/~lowe/keypoints | 2 | — | 0 | 15 | 15 100% |
| 2 | — | 0 | 3 | 3 100% | |
| SATLIB | 2 | — | 0 | 2 | 1 50% |
| Alan Mackworth | 2 | — | 0 | 3 | 3 100% |
| Anne Condon | 2 | — | 0 | 5 | 5 100% |
| Mark Greenstreet | 2 | — | 0 | 2 | 2 100% |
| Laks V.S. Lakshmanan | 2 | — | 0 | 4 | 4 100% |
| F. Heide, J. Gregson, G. Wetzstein, R. Raskar, W. Heidrich "Compressive multi-mode superresolution display", OSA Optics Express 2014 | 2 | — | 0 | 2 | 2 100% |
| a multibody mechanics simulation | 2 | — | 0 | 2 | 0 0% |
Frequently Asked Questions
What anchor texts are used to link to cs.ubc.ca?
This page shows all anchor texts found in backlinks pointing to cs.ubc.ca, sorted by the number of referring domains using each anchor. Anchor texts range from branded terms (like the domain name itself) to keyword-rich phrases that describe the linked content. The distribution of anchor texts reveals how other websites perceive and describe cs.ubc.ca.
What is anchor text?
Anchor text is the visible, clickable text in a hyperlink. Search engines use anchor text as a signal to understand what the linked page is about. For example, if many sites link to a page using the anchor text "best running shoes," search engines infer that the page is relevant to that topic. Anchor text appears in several forms: exact-match (contains target keywords), branded (uses the company or domain name), generic (like "click here"), and naked URLs.
Why is anchor text analysis important for SEO?
Anchor text analysis helps identify potential SEO risks and opportunities. A natural backlink profile has diverse anchor texts including branded terms, generic phrases, and topic-relevant keywords. Over-optimization, where too many backlinks use the same exact-match keyword anchor, can trigger search engine penalties. Conversely, understanding which anchors drive the most authority (measured by referring domain count and DR) helps prioritize link building efforts.
How many unique anchor texts does cs.ubc.ca have?
The anchor text report for cs.ubc.ca displays all distinct anchor texts grouped by their hash. Each row shows how many unique referring domains use that anchor, the total number of links, and the dofollow percentage. A high number of unique anchors generally indicates a healthy, natural backlink profile with diverse link sources.