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# Search Engine Algorithm Basics

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Among the topics you need to understand about Search Engine Algorithm Basics are the complex mathematical formulas, Boolean operators, Synonyms, Relevance feedback, and more. You may also be confused about how the algorithm interprets the user’s previous searches. The following article will cover these topics in detail. Hopefully, by the time you are done reading this article, you will understand these concepts.

## Complex mathematical formulas

Search engines use complex mathematical formulas to determine the placement of search results in SERP (Search Engine Results Page). These algorithms take into account the title, keyword density, and content of a web page and use these metrics to decide where to place the results. Every search engine uses a different algorithm, which means the criteria for optimizing a site should be determined through trial and error and observation. But the complexity of search engine algorithms makes them an invaluable resource.

## Boolean operators

Search engines use a series of mathematical formulas to find relevant results when you use a certain phrase or keyword. Some of these operators are known as Boolean, and they are used to refine searches by separating two or more terms. A good example of a Boolean search is “How to write an assignment”; you would have to type the phrase in quotation marks, not single quotes. However, this is not necessary – you can also use “AND” and “OR” operators in your search.

One problem with a Boolean search engine is that it requires specialized syntax to use it effectively. A search query such as “iron curtain” would require quotation marks around it, which would tell the search engine that the phrase should be treated as a keyword. Otherwise, you’d find documents about mining iron ore instead of interior decorating. Using Boolean search engine algorithms is not difficult, but it’s important to understand that they are not ideal for every situation.

## Synonyms

Graph modeling is another technique that can help determine the relationship between synonyms. Similar terms are grouped together on a graph according to their probability. This means that the query “new york city cheap hotels” has more chance of bringing a positive result than the generic term “new york city”.

## Relevance feedback

Relevance feedback is a feature in some information retrieval systems that gathers user input about the usefulness of retrieved information. Relevance feedback can be implicit, explicit, or blind. Explicit feedback is obtained from the users who judge the relevance of the returned items. The system then reformulates the query based on the feedback. The result is a set of improved results. The process is repeated if the user provides the same feedback.

Explicit relevance feedback is difficult to implement because it requires too much work on the part of the searcher. Even if the searcher is delighted with the results he receives, he won’t feel motivated to provide explicit feedback. If he receives irrelevant results, he or she is likely to try another query or another search engine, resulting in even more wasted effort. Another problem with explicit relevance feedback is familiarity bias. Developers are often wary of unfamiliar interfaces as they may negatively affect engagement.

## Indexing

The process of indexing in search engine algorithms is fundamental to making search results as relevant as possible. Indexing is the method by which search engines collect, categorize, and store information on online pages. It is used to produce super-fast results by giving algorithms easy access to contextual information. While Google does not rely on Bing’s index to produce search results, Bing relies heavily on it to determine the order of listing results.

The indexing process consists of two steps. The first step is to parse the content that is crawled by a search engine. The parser recognizes structural elements and text and tries to connect words to topics or entities. During parsing, there might be errors. Regardless of the errors, the entire process is important and makes search results more relevant and accurate. If indexing isn’t done properly, the results will be useless to users.

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