Trust Rank Algorithm is all about to combat the web spam. Web Spam denotes those web pages that are the result of spamming.
Any deliberate action solely in order to boost a web page's position in search engine results, incommensurate with page's real value is called spamming.
Web Spam Taxonomy contains:

a) Boosting Techniques
b) Hiding Techniques

Boosting Technique of spamming further divided into:
(i) Term spamming
(ii) Link spamming

Term spamming - Manipulating the text of web pages in order to appear relevant to queries. The target are for term spamming are Body of web page, Title, URL, HTML Meta tags, Anchor text.

Term Spamming
- Repetition of one or a few specific terms e.g., free, cheap, Viagra.Goal is to subvert TF.IDF ranking schemes
- Dumping of a large number of unrelated terms e.g., copy entire dictionaries
- Weaving Copy legitimate pages and insert spam terms at random positions
- Phrase Stitching Glue together sentences and phrases from different sources


Link spamming - Creating link structures that boost page rank or hubs and authorities scores. There are three kinds of web pages from a spammer's point of view
1. Inaccessible pages
2. Accessible pages e.g., web log comments pages spammer can post links to his pages
3. Own pages, Completely controlled by spammer. May span multiple domain names

Spammer's goal : Maximize the page rank of target page t

Technique :

- Get as many links from accessible pages as possible to target page t
- Construct “link farm” to get page rank multiplier effect

Structure of one of the most common and effective organizations for a link farm:



Hiding Technique

Content hiding - Use same color for text and page background
Cloaking - Return different page to crawlers and browsers
Redirection - Alternative to cloaking. Redirects are followed by browsers but not crawlers

Idea Behind Trust Rank

- Basic principle: approximate isolation - It is rare for a “good” page to point to a “bad” (spam) page
- Sample a set of “seed pages” from the web
- Have an oracle (human) identify the good pages and the spam pages in the seed set
Expensive task, so must make seed set as small as possible.
- Call the subset of seed pages that are identified as “good” the “trusted pages”
- Set trust of each trusted page to 1
- Propagate trust through links : Each page gets a trust value between 0 and 1
- Use a threshold value and mark all pages below the trust threshold as spam

Download the original Paper from here..