Search Engines and Algorithms: MetaSearch Engines, A Tool for SEO - Types: Raw, Database, Classification, Semantics
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1. The Raw MetaSearch Engine
This MetaSearch engine presents raw results from queried engines, presented in separate groups. Usually, in this type of MetaSearch engine, no results are being stored in a database; rather, results are simply being scraped from other top search engines, like Google, Yahoo, MSN, AOL Search, and AskJeeves.
Dogpile used to be a good example of the Raw MetaSearch engine, although it has been newly remodeled to become more of the next type of search: database MetaSearch. Mamma.com is also another Raw MetaSearch. In showing results side by side, it calculates site popularity from duplicates it returns. Even though it eliminates the duplicate entries, it counts the duplicates as “votes” for the results, then placing the site with the most duplicates at the top of its SERPs. Mamma.com is one of the oldest MetaSearches known to the Internet.
2. Database MetaSearch Engine
This is a type of search engine where results are processed, filtered and merged together, kept in a database of the MetaSearch Engine, either textual or virtual.
MetaCrawler is a good example of this type of MetaSearch engine. MetaCrawler is one of the oldest search engines, began in July 1995 at the University of Washington. MetaCrawler was purchased by InfoSpace, an online content provider, in Feb. 1997. Dogpile is now considered a Database MetaSearch engine, as it merges the results of its scans, and keeps them in a virtual database.
3. The Classification Engine
A Classification MetaSearch Engine is one that provides results that are processed and automatically categorized into specific categories.
Vivisimo has an example of a Classification Engine called Clusty. It uses the term “Cluster Engine”. Vivisimo tells us that the problem of not being able to find information in a search query has now been replaced by the presence of too much information to sort through. They claim “…categorization of all this data has been the obvious solution to enable users to better deal with this ‘information overload’. Traditional approaches to categorization involving taxonomies, however, are too expensive, time-consuming and complex for most organizations.” Clustering enables users to have the ability to view categorized results without the time and expense of taxonomy building.
Infonetware RealTerm Search, another Classification Engine, is primarily designed to demonstrate its “Infogistics” classification technology. While it's a meta search engine, and it does topical categorization of results, like Vivisimo; it is unique in that you can select several different topics, then choose to see results from all of them, rather than being restricted to the results from only one topic.
4. The Semantics Engine
The Semantics MetaSearch Engine is one that attempts to make sense of the results of a search query in a contextual format. One could argue that a Semantics Engine is nothing more than a complicated version of a Classification Engine. Currently, the use of the sense engine is being used to provide advertising, but eventually we’d like to see this concept used in a free search engine.
Textonomy Advance, patented by Crystal Semantics, is one of the few Semantics Engines to date. This search tool “…operates by applying human “senses” and concepts that current algorithms, semantic systems and other statistical techniques cannot match. Carefully built by human experts, Crystal Semantics’ unique semantic network provides an understanding of the “senses” of words and terms and the true linguistic relationship between them,” as they say on their website.
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