SEO Guy completes verbatimsolutions.com

We have just finished the design of our clients site, http://www.verbatimsolutions.com/ over the next few months we will be optimizing their site for keywords such as Translation Services and related terms. We would love comments on the new design and layout, also we welcome those with complementary services to submit to our resources section
Cheers
SEO Guy

Smindsrt releases seo fusion

One of our most active forum members smindsrt an seo consultant has released http://www.seo-fusion.com we wish him the best in this endeavor and would remind anyone when choosing an seo consultant it is best to go with one that is an active member of many seo forums as they are typically the best educated on the most current trends in the search engine landscape.

Support Rizla

He is an awesome SEO Guy member and needs our help to win the SEO contest in his native land.


Please link to him using
לתור מוטור

This will look like
לתור מוטור

Thanks guys

Thanks Google!

After I got hacked my cache was showing just a file tree and I was dropped totally from serps (Duh there is nothing on my site according to my cache) and I wrote Google a letter asking if they could help me flush the cache and get my proper site re-indexed and they were nice enough to reply and they are doing it! Who says google doesnt care :)

Google's reply -

Thank you for your note. We will delete our cached copy of your page in the next three to five days.

After we delete the cached copy of a page, the page's title and URL will continue to display for the same search queries until our robots revisit the site. Users will still be able to visit the live page. Because the information has been removed from the live page, this page will not return as a result for this query after our next crawl. Our robots crawl the web every four to six weeks to update content in our index. We appreciate your patience during this process.

cya lata fat cat

Fryman we will miss ye'

MSN Test for competitive phrase

There is an MSN thread being discussed over at http://www.realestatewebmasters.com where they are choosing a really competitive phrase "online pharmacy" and seeing how easy it is to rank in the new MSN. The thread is located at http://www.realestatewebmasters.com/showthread.php?t=1428&page=3&pp=10 and the website that is targeting the keyword is http://www.online-pharmacy-pharmacy.com stop by and check it out, should be interesting, the New MSN does seem easy to game, this may well prove it.

Google Allegra update thread

There is a very interesting thread over at SEW that is covering this garbage allegra update and the interesting phenomenon of websites not only being dropped for target keywords they are even being dropped for thier business or URL name: Even SEO Guy is not safe, searching Google we barely rank top 50 for "seo guy" without the quotes, now that is a serious google screwup IMO

The thread can be located at http://forums.searchenginewatch.com/showthread.php?t=4082&page=1&pp=20

NEW SEO Guy Forum Design

After the great hacking we recieved from the simien group that had all of our pages looking like

(Thanks Guys) we decided since we are having to redo the entire forum anyways we might as well update the design. Thus SEO Guy V3 was born - we welcome comments and suggestions as it is still very much in development. The goal was to eliminate extra images and code and make it lightning fast while at the same time increasing usibility. Stop by and check it out!

Latent Semantic Indexing

The Latent Semantic Indexing information retrieval model builds upon the prior research in information retrieval and, using the singular value decomposition (SVD) to reduce the dimensions of the term-document space, attempts to solve the synonomy and polysemy problems that plague automatic information retrieval systems. LSI explicitly represents terms and documents in a rich, high-dimensional space, allowing the underlying (``latent''), semantic relationships between terms and documents to be exploited during searching.
LSI relies on the constituent terms of a document to suggest the document's semantic content. However, the LSI model views the terms in a document as somewhat unreliable indicators of the concepts contained in the document. It assumes that the variability of word choice partially obscures the semantic structure of the document. By reducing the dimensionality of the term-document space, the underlying, semantic relationships between documents are revealed, and much of the ``noise'' (differences in word usage, terms that do not help distinguish documents, etc.) is eliminated. LSI statistically analyses the patterns of word usage across the entire document collection, placing documents with similar word usage patterns near each other in the term-document space, and allowing semantically-related documents to be near each other even though they may not share terms LSI differs from previous attempts at using reduced-space models for information retrieval in several ways. Most notably, LSI represents documents in a high-dimensional space. Koll for instance, used only seven dimensions to represent his semantic space. Secondly, both terms and documents are explicitly represented in the same space. Thirdly, unlike Borko and Bernick no attempt is made to interpret the meaning of each dimension. Each dimension is merely assumed to represent one or more semantic relationships in the term-document space. Finally, because of limits imposed mostly by the computational demands of vector-space approaches to information retrieval, previous attempts focused on relatively small document collections. LSI is able to represent and manipulate large data sets, making it viable for real-world applications Compared to other information retrieval techniques, LSI performs surprisingly well. In one test, Dumais found LSI provided more related documents than standard word-based retrieval techniques when searching the standard MED collection. Over five standard document collections, the same study indicated LSI performed an average of better than lexical retrieval techniques. In addition, LSI is fully automatic and easy to use, requiring no complex expressions or syntax to represent the query. Because terms and documents are explicitly represented in the space, relevance feedback can be seamlessly integrated with the LSI model, providing even better overall retrieval performance.