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3.6 Conclusion
In this unit, we have only touched upon the basics of search engines and LSI. There are many other concepts that could be covered (including such things as singular value decomposition and the term-document matrix!).
The material we have covered so far, however, has been simplified to a number of main points that have a bearing on the basic principles of SEO. These points should help you form a basic understanding of:
- the methods search engines are beginning to use for information retrieval
- how search engines actually see web pages
- how search engines weight keywords
By now you should have a more in-depth understanding of how search engines are beginning to index documents. It is useful to understand the principles behind LSI as we will refer back to it later in the course. As we will see later, LSI also has direct and practical implications for key areas of the SEO process such as deploying keywords, writing page copy, and constructing anchor text for external links.
SUMMARY:
- In order to return more relevant results for the user, Search Engines like Google are beginning to use Latent Semantic Indexing to retrieve web pages.
- Latent Semantic Analysis is a statistical method for determining the contextual meaning of words.
- Latent Semantic Indexing helps get round the problems of synonymy and polysemy encountered when people search the internet.
- Latent Semantic Indexing can return relevant pages that do not contain the actual terms of a keyword search.
- Search Engines do not read every word on a web page. Instead they focus on content words.
- Web pages are subjected to a complex process of linearisation, tokenisation, filtration, and stemming, whereby Mark-up, punctuation, and a stop list of commonly used words are removed from web pages.
- The content words on web pages are weighted differently according to how frequently they appear on a page and in the collection of documents as a whole.
- Keyword density is not an accurate measure of the importance of keywords on a page. Search engines actually use methods that look at keyword weighting and distribution.
REFLECT:
What do you understand by the following terms?
- Latent Semantic Analysis
- Polysemy and Synonmy
- Content Word
- Linearisation
- Tokenization
- Filtration
- Stop List
- Stemming
- Weighting
- Normalisation
- Keyword Density
Once you feel that you satisfactorily understand the above terms, move on to the next unit of the course
For more information about our Search Engine Optimisation Training Courses contact Syllabus or call +34 693 475 142.